		@@ -5,2 +5,14 @@ # Changelog

		## [3.0.3] - 2026-02-28

		### Fixed

		- `--version` now reads from package.json — Previously hardcoded as `3.0.0`, causing `code-insights --version` to always report `3.0.0` regardless of installed version.

		## [3.0.2] - 2026-02-28

		### Fixed

		- Added missing server runtime dependencies — `hono` and `@hono/node-server` added to CLI package.json so `code-insights dashboard` works for npm-installed users.

		## [3.0.0] - 2026-02-28
		@@ -7,0 +19,0 @@

+1

-1

dashboard-dist/index.html

		@@ -27,3 +27,3 @@ <!DOCTYPE html>
		</script>
		<script type="module" crossorigin src="/assets/index-CuCBzQyQ.js"></script>
		<script type="module" crossorigin src="/assets/index-CUWKxcRo.js"></script>
		<link rel="stylesheet" crossorigin href="/assets/index-BMhL7wL8.css">
		@@ -30,0 +30,0 @@ </head>

+3

-1

dist/index.js

		#!/usr/bin/env node
		import { readFileSync } from 'fs';
		import { Command } from 'commander';
		@@ -14,2 +15,3 @@ import { initCommand } from './commands/init.js';
		import { showTelemetryNoticeIfNeeded } from './utils/telemetry.js';
		const pkg = JSON.parse(readFileSync(new URL('../package.json', import.meta.url), 'utf-8'));
		const program = new Command();
		@@ -19,3 +21,3 @@ program
		.description('AI coding session analytics — sync, stats, and insights')
		.version('3.0.0');
		.version(pkg.version);
		program
		@@ -22,0 +24,0 @@ .command('init')

+1

-1

dist/index.js.map

		@@ -1,1 +0,1 @@
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+1

-1

package.json

		{
		"name": "@code-insights/cli",
		"version": "3.0.2",
		"version": "3.0.3",
		"description": "AI coding session analytics with built-in dashboard",
		@@ -5,0 +5,0 @@ "type": "module",

dashboard-dist/assets/index-CuCBzQyQ.js

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dashboard-dist/dist/assets/index-BMhL7wL8.css

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dashboard-dist/dist/assets/index-CuCBzQyQ.js

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dashboard-dist/dist/assets/index-CUWKxcRo.js

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-4

dashboard-dist/dist/favicon.svg

		<svg xmlns="http://www.w3.org/2000/svg" viewBox="0 0 32 32" fill="none">
		<rect width="32" height="32" rx="6" fill="#18181b"/>
		<path d="M8 22 L12 14 L16 18 L20 10 L24 22" stroke="#a1a1aa" stroke-width="2" stroke-linecap="round" stroke-linejoin="round" fill="none"/>
		</svg>

-33

dashboard-dist/dist/index.html

		<!DOCTYPE html>
		<html lang="en">
		<head>
		<meta charset="UTF-8" />
		<meta name="viewport" content="width=device-width, initial-scale=1.0" />
		<title>Code Insights</title>
		<link rel="icon" type="image/svg+xml" href="/favicon.svg" />
		<!-- FOUC prevention: apply theme class before React renders to avoid flash.
		Wrapped in try/catch so it silently degrades to light mode in
		restricted environments where localStorage access is blocked. -->
		<script>
		(function () {
		try {
		var stored = localStorage.getItem('code-insights-theme');
		var isDark = stored === 'dark';
		var isSystem = !stored \|\| stored === 'system' \|\| (stored !== 'light' && stored !== 'dark');
		var resolved = isDark \|\| (isSystem && window.matchMedia('(prefers-color-scheme: dark)').matches)
		? 'dark'
		: 'light';
		} catch (e) {
		var resolved = 'light';
		}
		document.documentElement.classList.remove('light', 'dark');
		document.documentElement.classList.add(resolved);
		})();
		</script>
		<script type="module" crossorigin src="/assets/index-CUWKxcRo.js"></script>
		<link rel="stylesheet" crossorigin href="/assets/index-BMhL7wL8.css">
		</head>
		<body>
		<div id="root"></div>
		</body>
		</html>

-5

dist/commands/connect.d.ts

		/**
		* Generate and display the dashboard connection URL
		*/
		export declare function connectCommand(): Promise<void>;
		//# sourceMappingURL=connect.d.ts.map

-1

dist/commands/connect.d.ts.map

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-39

dist/commands/connect.js

		import chalk from 'chalk';
		import { isConfigured, loadWebConfig, hasWebConfig } from '../utils/config.js';
		import { trackEvent } from '../utils/telemetry.js';
		import { generateDashboardUrl, validateWebConfig } from '../utils/firebase-json.js';
		/**
		* Generate and display the dashboard connection URL
		*/
		export async function connectCommand() {
		if (!isConfigured()) {
		console.log(chalk.red('\n❌ Code Insights is not configured.'));
		console.log(chalk.gray('The connect command requires Firebase setup.\n'));
		console.log(chalk.white(' To set up Firebase:'));
		console.log(chalk.gray(' code-insights init\n'));
		console.log(chalk.white(' For local-only analytics (no setup needed):'));
		console.log(chalk.gray(' code-insights stats\n'));
		return;
		}
		if (!hasWebConfig()) {
		console.log(chalk.yellow('\n⚠ No web config found.'));
		console.log(chalk.gray('\nRe-run "code-insights init" to add your web config.'));
		console.log(chalk.gray('Or visit the dashboard and configure Firebase manually:'));
		console.log(chalk.white(' https://code-insights.app\n'));
		return;
		}
		const webConfigData = loadWebConfig();
		if (!webConfigData \|\| !validateWebConfig(webConfigData)) {
		console.log(chalk.red('\n❌ Invalid web config stored.'));
		console.log(chalk.gray('Run "code-insights init" to reconfigure.\n'));
		return;
		}
		const webConfig = webConfigData;
		const url = generateDashboardUrl(webConfig);
		console.log(chalk.cyan('\n🔗 Dashboard Connection URL\n'));
		console.log(chalk.white('Open this URL to connect the dashboard to your Firebase:'));
		console.log(chalk.bold.underline(url));
		console.log('');
		trackEvent('connect', true);
		}
		//# sourceMappingURL=connect.js.map

-1

dist/commands/connect.js.map

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-13

dist/commands/insights.d.ts

		import type { InsightType } from '../types.js';
		interface InsightsOptions {
		type?: InsightType;
		project?: string;
		today?: boolean;
		limit?: number;
		}
		/**
		* Display recent insights from Firestore
		*/
		export declare function insightsCommand(options?: InsightsOptions): Promise<void>;
		export {};
		//# sourceMappingURL=insights.d.ts.map

-1

dist/commands/insights.d.ts.map

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-87

dist/commands/insights.js

		import chalk from 'chalk';
		import { format } from 'date-fns';
		import { loadConfig, isConfigured } from '../utils/config.js';
		import { initializeFirebase, getRecentInsights } from '../firebase/client.js';
		/**
		* Display recent insights from Firestore
		*/
		export async function insightsCommand(options = {}) {
		// Check if configured
		if (!isConfigured()) {
		console.log(chalk.red('Not configured. Run `claudeinsight init` first.'));
		process.exit(1);
		}
		// Load config and initialize Firebase
		const config = loadConfig();
		if (!config) {
		console.log(chalk.red('Configuration error.'));
		process.exit(1);
		}
		try {
		initializeFirebase(config);
		}
		catch (error) {
		console.log(chalk.red('Failed to connect to Firebase.'));
		console.error(error instanceof Error ? error.message : 'Unknown error');
		process.exit(1);
		}
		const limit = options.limit \|\| 20;
		// Fetch insights
		const insights = await getRecentInsights(limit, {
		type: options.type,
		project: options.project,
		todayOnly: options.today,
		});
		if (insights.length === 0) {
		console.log(chalk.yellow('\nNo insights found.'));
		if (options.today) {
		console.log(chalk.gray('Try running without --today to see older insights.'));
		}
		return;
		}
		console.log(chalk.cyan(`\n📊 Recent Insights (${insights.length})\n`));
		// Group by type
		const summaries = insights.filter((i) => i.type === 'summary');
		const decisions = insights.filter((i) => i.type === 'decision');
		const learnings = insights.filter((i) => i.type === 'learning');
		const techniques = insights.filter((i) => i.type === 'technique');
		if (summaries.length > 0) {
		console.log(chalk.bold.magenta('📝 Summaries'));
		for (const insight of summaries) {
		printInsight(insight);
		}
		console.log();
		}
		if (decisions.length > 0) {
		console.log(chalk.bold.blue('🎯 Decisions'));
		for (const insight of decisions) {
		printInsight(insight);
		}
		console.log();
		}
		if (learnings.length > 0) {
		console.log(chalk.bold.green('💡 Learnings'));
		for (const insight of learnings) {
		printInsight(insight);
		}
		console.log();
		}
		if (techniques.length > 0) {
		console.log(chalk.bold.yellow('🔧 Techniques'));
		for (const insight of techniques) {
		printInsight(insight);
		}
		console.log();
		}
		}
		function printInsight(insight) {
		const date = insight.timestamp
		? format(new Date(insight.timestamp), 'MMM d')
		: 'Unknown';
		console.log(chalk.white(` • ${insight.title}`));
		console.log(chalk.gray(` ${insight.projectName} \| ${date}`));
		if (insight.content && insight.content.length < 100) {
		console.log(chalk.gray(` ${insight.content}`));
		}
		}
		//# sourceMappingURL=insights.js.map

-1

dist/commands/insights.js.map

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-8

dist/commands/link.d.ts

		export interface LinkOptions {
		qr?: boolean;
		}
		/**
		* Generate and display dashboard link
		*/
		export declare function linkCommand(options: LinkOptions): Promise<void>;
		//# sourceMappingURL=link.d.ts.map

-1

dist/commands/link.d.ts.map

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-39

dist/commands/link.js

		import chalk from 'chalk';
		import qrcode from 'qrcode-terminal';
		import { isConfigured, loadWebConfig, hasWebConfig } from '../utils/config.js';
		import { generateDashboardUrl, validateWebConfig } from '../utils/firebase-json.js';
		/**
		* Generate and display dashboard link
		*/
		export async function linkCommand(options) {
		if (!isConfigured()) {
		console.log(chalk.red('\n❌ Code Insights is not configured.'));
		console.log(chalk.gray('Run "code-insights init" first.\n'));
		return;
		}
		if (!hasWebConfig()) {
		console.log(chalk.yellow('\n⚠ No web config found.'));
		console.log(chalk.gray('\nTo generate a dashboard link, add web config:'));
		console.log(chalk.white(' code-insights init --web-config <path-to-config.json>\n'));
		console.log(chalk.gray('Or visit the dashboard and configure Firebase manually:'));
		console.log(chalk.white(' https://code-insights.app\n'));
		return;
		}
		const webConfigData = loadWebConfig();
		if (!webConfigData \|\| !validateWebConfig(webConfigData)) {
		console.log(chalk.red('\n❌ Invalid web config stored.'));
		console.log(chalk.gray('Run "code-insights init --web-config <path>" to reconfigure.\n'));
		return;
		}
		const webConfig = webConfigData;
		const url = generateDashboardUrl(webConfig);
		console.log(chalk.cyan('\n🔗 Dashboard Link\n'));
		console.log(chalk.white('Open this URL to connect the dashboard:'));
		console.log(chalk.bold.underline(url));
		if (options.qr !== false) {
		console.log(chalk.gray('\n📱 QR Code:\n'));
		qrcode.generate(url, { small: true });
		}
		console.log('');
		}
		//# sourceMappingURL=link.js.map

-1

dist/commands/link.js.map

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-29

dist/commands/stats/data/cache.d.ts

		import type { ParsedSession } from '../../../types.js';
		import type { SessionRow } from './types.js';
		/**
		* Transform the CLI's ParsedSession into the stats SessionRow shape.
		* Uses a module-level cache for projectId to avoid repeated git spawns.
		*/
		export declare function parsedSessionToRow(session: ParsedSession): SessionRow;
		export declare class StatsCache {
		private data;
		private dirty;
		constructor();
		/**
		* Refresh the cache by discovering and parsing sessions from all providers.
		* Returns counts of new and total sessions.
		*/
		refresh(): Promise<{
		newSessions: number;
		totalSessions: number;
		}>;
		/**
		* Return all cached session rows with dates properly deserialized.
		* JSON serialization turns Date objects into ISO strings — reconstruct them.
		*/
		getAllRows(): SessionRow[];
		private load;
		private save;
		private empty;
		}
		//# sourceMappingURL=cache.d.ts.map

-1

dist/commands/stats/data/cache.d.ts.map

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-197

dist/commands/stats/data/cache.js

		// ──────────────────────────────────────────────────────
		// Stats cache — disk-based parsed session store
		//
		// Stores pre-parsed SessionRow[] keyed by source file path
		// with mtime-based invalidation. Lives at:
		// ~/.code-insights/stats-cache.json
		// ──────────────────────────────────────────────────────
		import * as fs from 'fs';
		import * as path from 'path';
		import * as os from 'os';
		import { generateStableProjectId } from '../../../utils/device.js';
		import { ensureConfigDir } from '../../../utils/config.js';
		import { splitVirtualPath } from '../../../utils/paths.js';
		import { getAllProviders } from '../../../providers/registry.js';
		// ──────────────────────────────────────────────────────
		// Constants
		// ──────────────────────────────────────────────────────
		const CACHE_PATH = path.join(os.homedir(), '.code-insights', 'stats-cache.json');
		// ──────────────────────────────────────────────────────
		// Module-level projectId cache — avoids repeated git
		// process spawns for the same project path
		// ──────────────────────────────────────────────────────
		const projectIdCache = new Map();
		function getCachedProjectId(projectPath) {
		const existing = projectIdCache.get(projectPath);
		if (existing)
		return existing;
		const { projectId } = generateStableProjectId(projectPath);
		projectIdCache.set(projectPath, projectId);
		return projectId;
		}
		// ──────────────────────────────────────────────────────
		// Exported helpers
		// ──────────────────────────────────────────────────────
		/**
		* Transform the CLI's ParsedSession into the stats SessionRow shape.
		* Uses a module-level cache for projectId to avoid repeated git spawns.
		*/
		export function parsedSessionToRow(session) {
		const projectId = getCachedProjectId(session.projectPath);
		return {
		// identity
		id: session.id,
		projectId,
		projectName: session.projectName,
		// timing
		startedAt: session.startedAt,
		endedAt: session.endedAt,
		// counts
		messageCount: session.messageCount,
		userMessageCount: session.userMessageCount,
		assistantMessageCount: session.assistantMessageCount,
		toolCallCount: session.toolCallCount,
		// cost / usage (optional)
		estimatedCostUsd: session.usage?.estimatedCostUsd,
		totalInputTokens: session.usage?.totalInputTokens,
		totalOutputTokens: session.usage?.totalOutputTokens,
		cacheCreationTokens: session.usage?.cacheCreationTokens,
		cacheReadTokens: session.usage?.cacheReadTokens,
		// metadata
		primaryModel: session.usage?.primaryModel,
		modelsUsed: session.usage?.modelsUsed,
		generatedTitle: session.generatedTitle ?? undefined,
		customTitle: session.customTitle,
		summary: session.summary ?? undefined,
		sessionCharacter: session.sessionCharacter ?? undefined,
		sourceTool: session.sourceTool,
		usageSource: session.usage?.usageSource,
		};
		}
		// ──────────────────────────────────────────────────────
		// StatsCache class
		// ──────────────────────────────────────────────────────
		export class StatsCache {
		data;
		dirty;
		constructor() {
		this.dirty = false;
		this.data = this.load();
		}
		/**
		* Refresh the cache by discovering and parsing sessions from all providers.
		* Returns counts of new and total sessions.
		*/
		async refresh() {
		const providers = getAllProviders();
		let newSessions = 0;
		// Collect all discovered file paths (keyed by provider name for metadata)
		const allDiscoveredPaths = new Set();
		for (const provider of providers) {
		const providerName = provider.getProviderName();
		let filePaths;
		try {
		filePaths = await provider.discover();
		}
		catch {
		// If discovery fails for a provider, skip it
		continue;
		}
		for (const filePath of filePaths) {
		allDiscoveredPaths.add(filePath);
		// Check mtime for cache invalidation
		const { realPath } = splitVirtualPath(filePath);
		let currentMtime;
		try {
		currentMtime = fs.statSync(realPath).mtime.toISOString();
		}
		catch {
		// File no longer accessible, skip
		continue;
		}
		const cached = this.data.entries[filePath];
		if (cached && cached.lastModified === currentMtime) {
		// Cache hit — mtime unchanged
		continue;
		}
		// Cache miss — parse the file
		let session;
		try {
		session = await provider.parse(filePath);
		}
		catch {
		// Parse error — skip this file
		continue;
		}
		if (!session)
		continue;
		const row = parsedSessionToRow(session);
		this.data.entries[filePath] = {
		lastModified: currentMtime,
		provider: providerName,
		rows: [row],
		};
		this.dirty = true;
		newSessions++;
		}
		}
		// Prune entries for file paths that no longer exist in any provider's discovery
		for (const cachedPath of Object.keys(this.data.entries)) {
		if (!allDiscoveredPaths.has(cachedPath)) {
		delete this.data.entries[cachedPath];
		this.dirty = true;
		}
		}
		// Persist if anything changed
		if (this.dirty) {
		this.data.lastRefresh = new Date().toISOString();
		this.save();
		}
		return { newSessions, totalSessions: this.getAllRows().length };
		}
		/**
		* Return all cached session rows with dates properly deserialized.
		* JSON serialization turns Date objects into ISO strings — reconstruct them.
		*/
		getAllRows() {
		const rows = [];
		for (const entry of Object.values(this.data.entries)) {
		for (const row of entry.rows) {
		rows.push({
		...row,
		startedAt: new Date(row.startedAt),
		endedAt: new Date(row.endedAt),
		});
		}
		}
		return rows;
		}
		// ──────────────────────────────────────────────────────
		// Private methods
		// ──────────────────────────────────────────────────────
		load() {
		try {
		if (!fs.existsSync(CACHE_PATH)) {
		return this.empty();
		}
		const content = fs.readFileSync(CACHE_PATH, 'utf-8');
		const parsed = JSON.parse(content);
		if (parsed.version !== 1) {
		return this.empty();
		}
		return parsed;
		}
		catch {
		return this.empty();
		}
		}
		save() {
		ensureConfigDir();
		fs.writeFileSync(CACHE_PATH, JSON.stringify(this.data, null, 2));
		this.dirty = false;
		}
		empty() {
		return { version: 1, lastRefresh: '', entries: {} };
		}
		}
		//# sourceMappingURL=cache.js.map

-1

dist/commands/stats/data/cache.js.map

-13

dist/commands/stats/data/firestore.d.ts

		import type { ClaudeInsightConfig } from '../../../types.js';
		import type { StatsDataSource, SessionRow, SessionQueryOptions, UsageStatsDoc, ProjectResolution, PrepareResult, StatsFlags } from './types.js';
		export declare class FirestoreDataSource implements StatsDataSource {
		private config;
		readonly name = "firestore";
		constructor(config: ClaudeInsightConfig);
		prepare(flags: StatsFlags): Promise<PrepareResult>;
		getSessions(opts: SessionQueryOptions): Promise<SessionRow[]>;
		getUsageStats(): Promise<UsageStatsDoc \| null>;
		resolveProjectId(name: string): Promise<ProjectResolution>;
		getLastSession(opts?: Pick<SessionQueryOptions, 'sourceTool' \| 'projectId'>): Promise<SessionRow \| null>;
		}
		//# sourceMappingURL=firestore.d.ts.map

-1

dist/commands/stats/data/firestore.d.ts.map

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-170

dist/commands/stats/data/firestore.js

		// ──────────────────────────────────────────────────────
		// Firestore data source for stats commands
		// ──────────────────────────────────────────────────────
		import admin from 'firebase-admin';
		import { initializeFirebase, getDb, getProjects } from '../../../firebase/client.js';
		import { ProjectNotFoundError, FirestoreIndexError } from './types.js';
		import { findSimilarNames } from './fuzzy-match.js';
		// ──────────────────────────────────────────────────────
		// Helpers
		// ──────────────────────────────────────────────────────
		/** Checks if error is a Firestore FAILED_PRECONDITION (missing composite index) */
		function isFirestoreIndexError(error) {
		if (typeof error === 'object' && error !== null && 'code' in error) {
		return error.code === 9;
		}
		return false;
		}
		/** Extracts the Firebase console index-creation URL from an error message */
		function extractIndexUrl(error) {
		if (typeof error === 'object' && error !== null && 'message' in error) {
		const message = error.message;
		const match = message.match(/(https:\/\/console\.firebase\.google\.com\/[^\s"]+)/);
		return match ? match[1] : null;
		}
		return null;
		}
		// ──────────────────────────────────────────────────────
		// Document mapper
		// ──────────────────────────────────────────────────────
		/** Maps a Firestore document to the universal SessionRow shape */
		function docToSessionRow(doc) {
		const data = doc.data();
		if (!data)
		throw new Error(`Session document ${doc.id} has no data`);
		return {
		id: doc.id,
		projectId: data.projectId,
		projectName: data.projectName,
		startedAt: data.startedAt?.toDate() ?? new Date(),
		endedAt: data.endedAt?.toDate() ?? new Date(),
		messageCount: data.messageCount ?? 0,
		userMessageCount: data.userMessageCount ?? 0,
		assistantMessageCount: data.assistantMessageCount ?? 0,
		toolCallCount: data.toolCallCount ?? 0,
		estimatedCostUsd: data.estimatedCostUsd,
		totalInputTokens: data.totalInputTokens,
		totalOutputTokens: data.totalOutputTokens,
		cacheCreationTokens: data.cacheCreationTokens,
		cacheReadTokens: data.cacheReadTokens,
		primaryModel: data.primaryModel,
		modelsUsed: data.modelsUsed,
		generatedTitle: data.generatedTitle,
		customTitle: data.customTitle,
		summary: data.summary,
		sessionCharacter: data.sessionCharacter,
		sourceTool: data.sourceTool,
		usageSource: data.usageSource,
		};
		}
		// ──────────────────────────────────────────────────────
		// FirestoreDataSource
		// ──────────────────────────────────────────────────────
		export class FirestoreDataSource {
		config;
		name = 'firestore';
		constructor(config) {
		this.config = config;
		}
		async prepare(flags) {
		initializeFirebase(this.config);
		if (!flags.noSync) {
		try {
		const { runSync } = await import('../../sync.js');
		const result = await runSync({ quiet: true });
		if (result.syncedCount > 0) {
		return { message: `Synced ${result.syncedCount} new sessions`, dataChanged: true };
		}
		return { message: 'Up to date', dataChanged: false };
		}
		catch {
		return { message: 'Sync failed (showing cached data)', dataChanged: false };
		}
		}
		return { message: 'Sync skipped', dataChanged: false };
		}
		async getSessions(opts) {
		const firestore = getDb();
		let query = firestore.collection('sessions');
		if (opts.projectId) {
		query = query.where('projectId', '==', opts.projectId);
		}
		if (opts.sourceTool) {
		query = query.where('sourceTool', '==', opts.sourceTool);
		}
		if (opts.periodStart) {
		query = query.where('startedAt', '>=', admin.firestore.Timestamp.fromDate(opts.periodStart));
		}
		query = query.orderBy('startedAt', 'desc');
		try {
		const snapshot = await query.get();
		return snapshot.docs.map(docToSessionRow);
		}
		catch (error) {
		if (isFirestoreIndexError(error)) {
		const url = extractIndexUrl(error);
		throw new FirestoreIndexError(url
		? `Missing Firestore index. Create it here: ${url}`
		: 'Missing Firestore composite index. Check the error details in Firebase console.', url ?? '');
		}
		throw error;
		}
		}
		async getUsageStats() {
		const firestore = getDb();
		const doc = await firestore.collection('stats').doc('usage').get();
		if (!doc.exists)
		return null;
		const data = doc.data();
		return {
		totalInputTokens: data.totalInputTokens ?? 0,
		totalOutputTokens: data.totalOutputTokens ?? 0,
		cacheCreationTokens: data.cacheCreationTokens ?? 0,
		cacheReadTokens: data.cacheReadTokens ?? 0,
		estimatedCostUsd: data.estimatedCostUsd ?? 0,
		sessionsWithUsage: data.sessionsWithUsage ?? 0,
		lastUpdatedAt: data.lastUpdatedAt?.toDate() ?? new Date(),
		};
		}
		async resolveProjectId(name) {
		const projects = await getProjects();
		// Exact match (case-insensitive)
		const exact = projects.find((p) => p.name.toLowerCase() === name.toLowerCase());
		if (exact)
		return { projectId: exact.id, projectName: exact.name };
		// Substring match
		const substring = projects.filter((p) => p.name.toLowerCase().includes(name.toLowerCase()));
		if (substring.length === 1)
		return { projectId: substring[0].id, projectName: substring[0].name };
		// No match — throw with suggestions
		const suggestions = findSimilarNames(name, projects.map((p) => p.name));
		throw new ProjectNotFoundError(`Project "${name}" not found.`, name, projects.map((p) => ({ name: p.name })), suggestions);
		}
		async getLastSession(opts) {
		const firestore = getDb();
		let query = firestore.collection('sessions');
		if (opts?.sourceTool) {
		query = query.where('sourceTool', '==', opts.sourceTool);
		}
		if (opts?.projectId) {
		query = query.where('projectId', '==', opts.projectId);
		}
		query = query.orderBy('startedAt', 'desc').limit(1);
		try {
		const snapshot = await query.get();
		if (snapshot.empty)
		return null;
		return docToSessionRow(snapshot.docs[0]);
		}
		catch (error) {
		if (isFirestoreIndexError(error)) {
		const url = extractIndexUrl(error);
		throw new FirestoreIndexError(url
		? `Missing Firestore index. Create it here: ${url}`
		: 'Missing Firestore composite index. Check the error details in Firebase console.', url ?? '');
		}
		throw error;
		}
		}
		}
		//# sourceMappingURL=firestore.js.map

-1

dist/commands/stats/data/firestore.js.map

-45

dist/firebase/client.d.ts

		import admin from 'firebase-admin';
		import type { ClaudeInsightConfig, ParsedSession, Project } from '../types.js';
		/**
		* Initialize Firebase Admin SDK
		*/
		export declare function initializeFirebase(config: ClaudeInsightConfig): void;
		/**
		* Get Firestore instance
		*/
		export declare function getDb(): admin.firestore.Firestore;
		/**
		* Upload a session to Firestore
		*/
		export declare function uploadSession(session: ParsedSession, isForceSync?: boolean): Promise<void>;
		/**
		* Upload messages to Firestore for LLM analysis
		*/
		export declare function uploadMessages(session: ParsedSession): Promise<void>;
		/**
		* Check if a session already exists
		*/
		export declare function sessionExists(sessionId: string): Promise<boolean>;
		/**
		* Get all projects
		*/
		export declare function getProjects(): Promise<Project[]>;
		/**
		* Get recent sessions
		*/
		export declare function getRecentSessions(limit?: number): Promise<ParsedSession[]>;
		/**
		* Recalculate usage stats from all sessions in Firestore.
		* Used after --force sync to reconcile totals.
		*/
		export declare function recalculateUsageStats(): Promise<{
		sessionsWithUsage: number;
		totalTokens: number;
		estimatedCostUsd: number;
		}>;
		/**
		* Get per-tool session counts grouped by project.
		* Uses select() to only fetch projectId and sourceTool fields (efficient).
		*/
		export declare function getProjectToolCounts(): Promise<Map<string, Map<string, number>>>;
		//# sourceMappingURL=client.d.ts.map

-1

dist/firebase/client.d.ts.map

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-344

dist/firebase/client.js

		import admin from 'firebase-admin';
		import { generateStableProjectId, getDeviceInfo } from '../utils/device.js';
		let db = null;
		/**
		* Initialize Firebase Admin SDK
		*/
		export function initializeFirebase(config) {
		if (!config.firebase) {
		throw new Error('Firebase credentials not configured. Run `code-insights init` to set up.');
		}
		if (admin.apps.length > 0) {
		db = admin.firestore();
		return;
		}
		admin.initializeApp({
		credential: admin.credential.cert({
		projectId: config.firebase.projectId,
		clientEmail: config.firebase.clientEmail,
		privateKey: config.firebase.privateKey.replace(/\\n/g, '\n'),
		}),
		});
		db = admin.firestore();
		}
		/**
		* Get Firestore instance
		*/
		export function getDb() {
		if (!db) {
		throw new Error('Firebase not initialized. Call initializeFirebase first.');
		}
		return db;
		}
		/**
		* Upload a session to Firestore
		*/
		export async function uploadSession(session, isForceSync = false) {
		const firestore = getDb();
		// Generate stable project ID (prefers git remote URL)
		const { projectId, source: projectIdSource, gitRemoteUrl } = generateStableProjectId(session.projectPath);
		// Get device info for multi-device support
		const deviceInfo = getDeviceInfo();
		// Check if session already exists (for idempotent session count)
		const sessionRef = firestore.collection('sessions').doc(session.id);
		const existingSession = await sessionRef.get();
		const isNewSession = !existingSession.exists;
		const batch = firestore.batch();
		// Upsert project
		const projectRef = firestore.collection('projects').doc(projectId);
		batch.set(projectRef, {
		name: session.projectName,
		path: session.projectPath,
		gitRemoteUrl: gitRemoteUrl,
		projectIdSource: projectIdSource,
		lastActivity: admin.firestore.Timestamp.fromDate(session.endedAt),
		updatedAt: admin.firestore.FieldValue.serverTimestamp(),
		}, { merge: true });
		// Only increment session count for NEW sessions (idempotent)
		if (isNewSession) {
		const incrementFields = {
		sessionCount: admin.firestore.FieldValue.increment(1),
		};
		if (!isForceSync && session.usage) {
		incrementFields.totalInputTokens = admin.firestore.FieldValue.increment(session.usage.totalInputTokens);
		incrementFields.totalOutputTokens = admin.firestore.FieldValue.increment(session.usage.totalOutputTokens);
		incrementFields.cacheCreationTokens = admin.firestore.FieldValue.increment(session.usage.cacheCreationTokens);
		incrementFields.cacheReadTokens = admin.firestore.FieldValue.increment(session.usage.cacheReadTokens);
		incrementFields.estimatedCostUsd = admin.firestore.FieldValue.increment(session.usage.estimatedCostUsd);
		}
		batch.update(projectRef, incrementFields);
		}
		// Upload session with device info
		batch.set(sessionRef, {
		projectId: projectId,
		projectName: session.projectName,
		projectPath: session.projectPath,
		gitRemoteUrl: gitRemoteUrl,
		summary: session.summary,
		generatedTitle: session.generatedTitle,
		titleSource: session.titleSource,
		sessionCharacter: session.sessionCharacter,
		startedAt: admin.firestore.Timestamp.fromDate(session.startedAt),
		endedAt: admin.firestore.Timestamp.fromDate(session.endedAt),
		messageCount: session.messageCount,
		userMessageCount: session.userMessageCount,
		assistantMessageCount: session.assistantMessageCount,
		toolCallCount: session.toolCallCount,
		gitBranch: session.gitBranch,
		claudeVersion: session.claudeVersion,
		sourceTool: session.sourceTool ?? 'claude-code',
		// Device info for multi-device tracking
		deviceId: deviceInfo.deviceId,
		deviceHostname: deviceInfo.hostname,
		devicePlatform: deviceInfo.platform,
		syncedAt: admin.firestore.FieldValue.serverTimestamp(),
		// Usage stats (conditional — absent for older sessions without token data)
		...(session.usage ? {
		totalInputTokens: session.usage.totalInputTokens,
		totalOutputTokens: session.usage.totalOutputTokens,
		cacheCreationTokens: session.usage.cacheCreationTokens,
		cacheReadTokens: session.usage.cacheReadTokens,
		estimatedCostUsd: session.usage.estimatedCostUsd,
		modelsUsed: session.usage.modelsUsed,
		primaryModel: session.usage.primaryModel,
		usageSource: session.usage.usageSource,
		} : {}),
		});
		// Atomically increment usage stats for new sessions (non-force only)
		if (isNewSession && !isForceSync && session.usage) {
		const statsRef = firestore.collection('stats').doc('usage');
		batch.set(statsRef, {
		totalInputTokens: admin.firestore.FieldValue.increment(session.usage.totalInputTokens),
		totalOutputTokens: admin.firestore.FieldValue.increment(session.usage.totalOutputTokens),
		cacheCreationTokens: admin.firestore.FieldValue.increment(session.usage.cacheCreationTokens),
		cacheReadTokens: admin.firestore.FieldValue.increment(session.usage.cacheReadTokens),
		estimatedCostUsd: admin.firestore.FieldValue.increment(session.usage.estimatedCostUsd),
		sessionsWithUsage: admin.firestore.FieldValue.increment(1),
		lastUpdatedAt: admin.firestore.FieldValue.serverTimestamp(),
		}, { merge: true });
		}
		await batch.commit();
		}
		/**
		* Upload messages to Firestore for LLM analysis
		*/
		export async function uploadMessages(session) {
		if (session.messages.length === 0)
		return;
		const firestore = getDb();
		const batches = [];
		let currentBatch = firestore.batch();
		let operationCount = 0;
		for (const message of session.messages) {
		const messageRef = firestore.collection('messages').doc(message.id);
		currentBatch.set(messageRef, {
		sessionId: message.sessionId,
		type: message.type,
		content: truncateContent(message.content, 10000),
		thinking: message.thinking
		? truncateContent(message.thinking, 5000)
		: null,
		toolCalls: message.toolCalls.map((tc) => ({
		id: tc.id,
		name: tc.name,
		input: JSON.stringify(tc.input).slice(0, 1000),
		})),
		toolResults: message.toolResults.map((tr) => ({
		toolUseId: tr.toolUseId,
		output: truncateContent(tr.output, 2000),
		})),
		timestamp: admin.firestore.Timestamp.fromDate(message.timestamp),
		parentId: message.parentId,
		// Per-message usage (assistant messages only)
		...(message.usage ? {
		usage: {
		inputTokens: message.usage.inputTokens,
		outputTokens: message.usage.outputTokens,
		cacheCreationTokens: message.usage.cacheCreationTokens,
		cacheReadTokens: message.usage.cacheReadTokens,
		model: message.usage.model,
		estimatedCostUsd: message.usage.estimatedCostUsd,
		},
		} : {}),
		});
		operationCount++;
		if (operationCount >= 500) {
		batches.push(currentBatch);
		currentBatch = firestore.batch();
		operationCount = 0;
		}
		}
		if (operationCount > 0) {
		batches.push(currentBatch);
		}
		await Promise.all(batches.map((batch) => batch.commit()));
		}
		/**
		* Check if a session already exists
		*/
		export async function sessionExists(sessionId) {
		const firestore = getDb();
		const doc = await firestore.collection('sessions').doc(sessionId).get();
		return doc.exists;
		}
		/**
		* Get all projects
		*/
		export async function getProjects() {
		const firestore = getDb();
		const snapshot = await firestore.collection('projects').orderBy('lastActivity', 'desc').get();
		return snapshot.docs.map((doc) => {
		const data = doc.data();
		return {
		id: doc.id,
		name: data.name,
		path: data.path,
		sessionCount: data.sessionCount \|\| 0,
		lastActivity: data.lastActivity?.toDate() \|\| new Date(),
		createdAt: data.createdAt?.toDate() \|\| new Date(),
		};
		});
		}
		/**
		* Get recent sessions
		*/
		export async function getRecentSessions(limit = 10) {
		const firestore = getDb();
		const snapshot = await firestore
		.collection('sessions')
		.orderBy('endedAt', 'desc')
		.limit(limit)
		.get();
		return snapshot.docs.map((doc) => {
		const data = doc.data();
		return {
		id: doc.id,
		projectPath: data.projectPath,
		projectName: data.projectName,
		summary: data.summary,
		startedAt: data.startedAt?.toDate() \|\| new Date(),
		endedAt: data.endedAt?.toDate() \|\| new Date(),
		messageCount: data.messageCount,
		userMessageCount: data.userMessageCount,
		assistantMessageCount: data.assistantMessageCount,
		toolCallCount: data.toolCallCount,
		messages: [],
		insights: [],
		gitBranch: data.gitBranch,
		claudeVersion: data.claudeVersion,
		generatedTitle: data.generatedTitle \|\| null,
		titleSource: data.titleSource \|\| null,
		sessionCharacter: data.sessionCharacter \|\| null,
		};
		});
		}
		/**
		* Recalculate usage stats from all sessions in Firestore.
		* Used after --force sync to reconcile totals.
		*/
		export async function recalculateUsageStats() {
		const firestore = getDb();
		// Query all sessions that have usage data
		const snapshot = await firestore
		.collection('sessions')
		.where('usageSource', '==', 'jsonl')
		.get();
		// Aggregate global + per-project totals
		const global = {
		totalInputTokens: 0,
		totalOutputTokens: 0,
		cacheCreationTokens: 0,
		cacheReadTokens: 0,
		estimatedCostUsd: 0,
		sessionsWithUsage: 0,
		};
		const perProject = {};
		for (const doc of snapshot.docs) {
		const data = doc.data();
		global.totalInputTokens += data.totalInputTokens ?? 0;
		global.totalOutputTokens += data.totalOutputTokens ?? 0;
		global.cacheCreationTokens += data.cacheCreationTokens ?? 0;
		global.cacheReadTokens += data.cacheReadTokens ?? 0;
		global.estimatedCostUsd += data.estimatedCostUsd ?? 0;
		global.sessionsWithUsage++;
		const pid = data.projectId;
		if (pid) {
		if (!perProject[pid]) {
		perProject[pid] = {
		totalInputTokens: 0,
		totalOutputTokens: 0,
		cacheCreationTokens: 0,
		cacheReadTokens: 0,
		estimatedCostUsd: 0,
		};
		}
		perProject[pid].totalInputTokens += data.totalInputTokens ?? 0;
		perProject[pid].totalOutputTokens += data.totalOutputTokens ?? 0;
		perProject[pid].cacheCreationTokens += data.cacheCreationTokens ?? 0;
		perProject[pid].cacheReadTokens += data.cacheReadTokens ?? 0;
		perProject[pid].estimatedCostUsd += data.estimatedCostUsd ?? 0;
		}
		}
		// Write global stats (overwrite, not merge)
		const statsRef = firestore.collection('stats').doc('usage');
		await statsRef.set({
		...global,
		lastUpdatedAt: admin.firestore.FieldValue.serverTimestamp(),
		});
		// Update each project's usage fields
		const batches = [];
		let currentBatch = firestore.batch();
		let opCount = 0;
		for (const [projectId, usage] of Object.entries(perProject)) {
		const projectRef = firestore.collection('projects').doc(projectId);
		currentBatch.set(projectRef, usage, { merge: true });
		opCount++;
		if (opCount >= 500) {
		batches.push(currentBatch);
		currentBatch = firestore.batch();
		opCount = 0;
		}
		}
		if (opCount > 0)
		batches.push(currentBatch);
		await Promise.all(batches.map(b => b.commit()));
		const totalTokens = global.totalInputTokens + global.totalOutputTokens
		+ global.cacheCreationTokens + global.cacheReadTokens;
		return {
		sessionsWithUsage: global.sessionsWithUsage,
		totalTokens,
		estimatedCostUsd: global.estimatedCostUsd,
		};
		}
		/**
		* Get per-tool session counts grouped by project.
		* Uses select() to only fetch projectId and sourceTool fields (efficient).
		*/
		export async function getProjectToolCounts() {
		const firestore = getDb();
		const snapshot = await firestore
		.collection('sessions')
		.select('projectId', 'sourceTool')
		.get();
		const counts = new Map();
		for (const doc of snapshot.docs) {
		const data = doc.data();
		const projectId = data.projectId;
		const sourceTool = data.sourceTool \|\| 'claude-code';
		if (!counts.has(projectId)) {
		counts.set(projectId, new Map());
		}
		const toolMap = counts.get(projectId);
		toolMap.set(sourceTool, (toolMap.get(sourceTool) \|\| 0) + 1);
		}
		return counts;
		}
		/**
		* Truncate content to max length
		*/
		function truncateContent(content, maxLength) {
		if (content.length <= maxLength)
		return content;
		return content.slice(0, maxLength - 20) + '\n... [truncated]';
		}
		//# sourceMappingURL=client.js.map

-1

dist/firebase/client.js.map

-7

dist/parser/insights.d.ts

		import type { ParsedSession, Insight, ParsedInsightContent } from '../types.js';
		export declare function parseInsightContent(raw: string): ParsedInsightContent;
		/**
		* Extract insights from a parsed session using pattern matching
		*/
		export declare function extractInsights(session: ParsedSession): Insight[];
		//# sourceMappingURL=insights.d.ts.map

-1

dist/parser/insights.d.ts.map

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-271

dist/parser/insights.js

		import { v4 as uuidv4 } from 'uuid';
		export function parseInsightContent(raw) {
		const isClaudeInsight = raw.includes('★ Insight') \|\| raw.includes('★Insight');
		if (isClaudeInsight) {
		return parseClaudeFormattedInsight(raw);
		}
		return parseGenericContent(raw);
		}
		function parseClaudeFormattedInsight(raw) {
		let cleaned = raw.replace(/★\sInsight\s─/g, '').replace(/─+/g, '').replace(/\\*/g, '').trim();
		const lines = cleaned.split('\n').map(l => l.trim()).filter(l => l);
		const title = (lines[0] \|\| '').replace(/:$/, '').trim();
		const bullets = lines.slice(1).filter(l => l.startsWith('-')).map(l => l.replace(/^-\s*/, '').trim());
		const summary = bullets.length > 0 ? `${title}: ${bullets[0]}` : title;
		return { title, summary, bullets, rawContent: raw };
		}
		function parseGenericContent(raw) {
		let cleaned = raw.replace(/\\/g, '').replace(/\\"/g, '"').replace(/\\n/g, '\n').trim();
		const lines = cleaned.split('\n').map(l => l.trim()).filter(l => l);
		const title = truncate(lines[0] \|\| cleaned, 100);
		const bullets = lines.slice(1).filter(l => l.startsWith('-') \|\| l.startsWith('•')).map(l => l.replace(/^[-•]\s*/, '').trim());
		return { title, summary: title, bullets, rawContent: raw };
		}
		// Pattern matching rules for different insight types
		const DECISION_PATTERNS = [
		/decided to (.+)/i,
		/chose (.+) over (.+)/i,
		/went with (.+) because (.+)/i,
		/trade-off:?\s*(.+)/i,
		/approach:?\s*(.+)/i,
		/\\decision\\:?\s*(.+)/i,
		/we('ll\| will) use (.+) (for\|to\|because)/i,
		/let's go with (.+)/i,
		/the (best\|right\|better) (approach\|solution\|choice) is (.+)/i,
		];
		const LEARNING_PATTERNS = [
		/learned that (.+)/i,
		/TIL:?\s*(.+)/i,
		/insight:?\s*(.+)/i,
		/realized (.+)/i,
		/mistake:?\s*(.+)/i,
		/note to self:?\s*(.+)/i,
		/important:?\s*(.+)/i,
		/remember:?\s*(.+)/i,
		/turns out (.+)/i,
		/didn't know (.+)/i,
		];
		const WORKITEM_SIGNALS = {
		feature: ['added', 'implemented', 'created', 'built', 'new feature', 'introducing'],
		bugfix: ['fixed', 'resolved', 'patched', 'corrected', 'bug fix', 'fixing'],
		refactor: ['refactored', 'restructured', 'reorganized', 'cleaned', 'improved', 'simplified'],
		docs: ['documented', 'documentation', 'readme', 'comments', 'jsdoc'],
		test: ['tested', 'test', 'spec', 'coverage', 'unit test', 'integration test'],
		};
		const WORK_TOOLS = ['Edit', 'Write', 'Bash'];
		/**
		* Extract insights from a parsed session using pattern matching
		*/
		export function extractInsights(session) {
		const insights = [];
		const projectId = generateProjectId(session.projectPath);
		// Extract from assistant messages
		for (const message of session.messages) {
		if (message.type === 'assistant') {
		// Check for decisions
		const decisions = extractDecisions(message, session, projectId);
		insights.push(...decisions);
		// Check for learnings
		const learnings = extractLearnings(message, session, projectId);
		insights.push(...learnings);
		// Check for work items from tool calls
		const workItems = extractWorkItems(message, session, projectId);
		insights.push(...workItems);
		}
		}
		// Add effort insight for the session
		const effortInsight = createEffortInsight(session, projectId);
		if (effortInsight) {
		insights.push(effortInsight);
		}
		return insights;
		}
		/**
		* Extract decision insights from a message
		*/
		function extractDecisions(message, session, projectId) {
		const insights = [];
		const content = message.content;
		for (const pattern of DECISION_PATTERNS) {
		const match = content.match(pattern);
		if (match) {
		const extractedText = match[1] \|\| match[0];
		// Get surrounding context (up to 200 chars)
		const matchIndex = content.indexOf(match[0]);
		const contextStart = Math.max(0, matchIndex - 100);
		const contextEnd = Math.min(content.length, matchIndex + match[0].length + 100);
		const context = content.slice(contextStart, contextEnd);
		insights.push({
		id: uuidv4(),
		sessionId: session.id,
		projectId,
		projectName: session.projectName,
		type: 'decision',
		title: truncate(extractedText, 100),
		content: context,
		summary: '',
		bullets: [],
		confidence: 0.7,
		source: 'pattern',
		metadata: {
		reasoning: extractedText,
		},
		timestamp: message.timestamp,
		});
		// Only extract first match per pattern to avoid duplicates
		break;
		}
		}
		return insights;
		}
		/**
		* Extract learning insights from a message
		*/
		function extractLearnings(message, session, projectId) {
		const insights = [];
		const content = message.content;
		for (const pattern of LEARNING_PATTERNS) {
		const match = content.match(pattern);
		if (match) {
		const extractedText = match[1] \|\| match[0];
		// Get surrounding context
		const matchIndex = content.indexOf(match[0]);
		const contextStart = Math.max(0, matchIndex - 100);
		const contextEnd = Math.min(content.length, matchIndex + match[0].length + 100);
		const context = content.slice(contextStart, contextEnd);
		insights.push({
		id: uuidv4(),
		sessionId: session.id,
		projectId,
		projectName: session.projectName,
		type: 'learning',
		title: truncate(extractedText, 100),
		content: context,
		summary: '',
		bullets: [],
		confidence: 0.6,
		source: 'pattern',
		metadata: {},
		timestamp: message.timestamp,
		});
		break;
		}
		}
		return insights;
		}
		/**
		* Extract work item insights from tool calls
		*/
		function extractWorkItems(message, session, projectId) {
		const insights = [];
		// Check for file-modifying tool calls
		const fileEdits = message.toolCalls.filter((tc) => WORK_TOOLS.includes(tc.name));
		if (fileEdits.length === 0) {
		return insights;
		}
		// Extract files modified
		const files = [];
		for (const tc of fileEdits) {
		if (tc.name === 'Edit' \|\| tc.name === 'Write') {
		const filePath = tc.input.file_path;
		if (filePath) {
		files.push(filePath);
		}
		}
		}
		if (files.length === 0) {
		return insights;
		}
		// Determine work type from message content
		const workType = determineWorkType(message.content);
		// Create a consolidated work item for this message
		insights.push({
		id: uuidv4(),
		sessionId: session.id,
		projectId,
		projectName: session.projectName,
		type: 'workitem',
		title: `${capitalizeFirst(workType)}: ${files.length} file(s) modified`,
		content: `Files: ${files.join(', ')}`,
		summary: '',
		bullets: [],
		confidence: 0.9,
		source: 'pattern',
		metadata: {
		files,
		workType,
		},
		timestamp: message.timestamp,
		});
		return insights;
		}
		/**
		* Create an effort insight for the session
		*/
		function createEffortInsight(session, projectId) {
		// Calculate session duration in minutes
		const durationMs = session.endedAt.getTime() - session.startedAt.getTime();
		const durationMinutes = Math.round(durationMs / 60000);
		if (durationMinutes < 1) {
		return null;
		}
		return {
		id: uuidv4(),
		sessionId: session.id,
		projectId,
		projectName: session.projectName,
		type: 'effort',
		title: `Session: ${durationMinutes} min, ${session.messageCount} messages`,
		content: `User: ${session.userMessageCount} messages, Assistant: ${session.assistantMessageCount} messages, Tool calls: ${session.toolCallCount}`,
		summary: '',
		bullets: [],
		confidence: 1.0,
		source: 'pattern',
		metadata: {
		duration: durationMinutes,
		},
		timestamp: session.startedAt,
		};
		}
		/**
		* Determine work type from message content
		*/
		function determineWorkType(content) {
		const lowerContent = content.toLowerCase();
		for (const [workType, signals] of Object.entries(WORKITEM_SIGNALS)) {
		for (const signal of signals) {
		if (lowerContent.includes(signal)) {
		return workType;
		}
		}
		}
		return 'feature'; // Default
		}
		/**
		* Generate a stable project ID from path
		*/
		function generateProjectId(projectPath) {
		// Create a simple hash from the path
		let hash = 0;
		for (let i = 0; i < projectPath.length; i++) {
		const char = projectPath.charCodeAt(i);
		hash = (hash << 5) - hash + char;
		hash = hash & hash;
		}
		return `proj_${Math.abs(hash).toString(16)}`;
		}
		/**
		* Truncate string to max length
		*/
		function truncate(str, maxLength) {
		if (str.length <= maxLength)
		return str;
		return str.slice(0, maxLength - 3) + '...';
		}
		/**
		* Capitalize first letter
		*/
		function capitalizeFirst(str) {
		return str.charAt(0).toUpperCase() + str.slice(1);
		}
		//# sourceMappingURL=insights.js.map

-1

dist/parser/insights.js.map

-87

dist/utils/firebase-json.d.ts

		import type { FirebaseServiceAccountJson, FirebaseWebConfig } from '../types.js';
		export type FileReadResult<T> = {
		success: true;
		data: T;
		} \| {
		success: false;
		error: 'not_found' \| 'invalid_json' \| 'permission_denied' \| 'unknown';
		message: string;
		};
		/**
		* Validate Firebase Service Account JSON structure
		*/
		export declare function validateServiceAccountJson(data: unknown): data is FirebaseServiceAccountJson;
		/**
		* Check if data looks like a service account (for cross-type detection)
		*/
		export declare function looksLikeServiceAccount(data: unknown): boolean;
		/**
		* Check if data looks like a web config (for cross-type detection)
		*/
		export declare function looksLikeWebConfig(data: unknown): boolean;
		/**
		* Validate Firebase Web SDK config structure
		*/
		export declare function validateWebConfig(data: unknown): data is FirebaseWebConfig;
		/**
		* Parse Firebase's JavaScript config snippet into a JSON object.
		*
		* Firebase Console gives you JavaScript like:
		* const firebaseConfig = {
		* apiKey: "AIza...",
		* authDomain: "my-project.firebaseapp.com",
		* ...
		* };
		*
		* This function extracts the object and converts it to a parsed object.
		*/
		export declare function parseFirebaseJsConfig(content: string): Record<string, unknown> \| null;
		/**
		* Read a Firebase config file — accepts JSON or JavaScript format.
		*
		* Tries JSON.parse first. If that fails, tries to extract a JS object
		* literal (handles the raw Firebase Console snippet).
		*/
		export declare function readFirebaseConfigFile<T>(filePath: string): FileReadResult<T>;
		/**
		* Resolve file path (expand ~ to home directory)
		*/
		export declare function resolveFilePath(filePath: string): string;
		/**
		* Check if file exists
		*/
		export declare function fileExists(filePath: string): boolean;
		/**
		* Read and parse a JSON file with detailed error reporting
		*/
		export declare function readJsonFileWithError<T>(filePath: string): FileReadResult<T>;
		/**
		* Read and parse a JSON file (simple version, returns null on error)
		*/
		export declare function readJsonFile<T>(filePath: string): T \| null;
		/**
		* Extract service account config from JSON file
		*/
		export declare function extractServiceAccountConfig(json: FirebaseServiceAccountJson): {
		projectId: string;
		clientEmail: string;
		privateKey: string;
		};
		/**
		* Encode web config for URL parameter (base64url encoding per RFC 4648)
		*
		* The web app decodes this with:
		* const base64 = encoded.replace(/-/g, '+').replace(/_/g, '/');
		* const json = atob(base64);
		* const config = JSON.parse(json);
		*/
		export declare function encodeWebConfigForUrl(config: FirebaseWebConfig): string;
		/**
		* Generate the web dashboard URL with embedded config
		*
		* Note: Firebase web API keys are designed for client-side use and are
		* restricted by Firestore security rules, not by key secrecy. However,
		* users should still avoid sharing this URL publicly.
		*/
		export declare function generateDashboardUrl(config: FirebaseWebConfig): string;
		//# sourceMappingURL=firebase-json.d.ts.map

-1

dist/utils/firebase-json.d.ts.map

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-207

dist/utils/firebase-json.js

		import * as fs from 'fs';
		import * as os from 'os';
		/**
		* Validate Firebase Service Account JSON structure
		*/
		export function validateServiceAccountJson(data) {
		if (!data \|\| typeof data !== 'object')
		return false;
		const obj = data;
		return (obj.type === 'service_account' &&
		typeof obj.project_id === 'string' &&
		typeof obj.private_key === 'string' &&
		typeof obj.client_email === 'string' &&
		obj.private_key.includes('-----BEGIN PRIVATE KEY-----'));
		}
		/**
		* Check if data looks like a service account (for cross-type detection)
		*/
		export function looksLikeServiceAccount(data) {
		if (!data \|\| typeof data !== 'object')
		return false;
		const obj = data;
		return obj.type === 'service_account' \|\| typeof obj.private_key === 'string';
		}
		/**
		* Check if data looks like a web config (for cross-type detection)
		*/
		export function looksLikeWebConfig(data) {
		if (!data \|\| typeof data !== 'object')
		return false;
		const obj = data;
		return typeof obj.apiKey === 'string' \|\| typeof obj.authDomain === 'string';
		}
		/**
		* Validate Firebase Web SDK config structure
		*/
		export function validateWebConfig(data) {
		if (!data \|\| typeof data !== 'object')
		return false;
		const obj = data;
		return (typeof obj.apiKey === 'string' &&
		typeof obj.authDomain === 'string' &&
		typeof obj.projectId === 'string' &&
		typeof obj.storageBucket === 'string' &&
		typeof obj.messagingSenderId === 'string' &&
		typeof obj.appId === 'string');
		}
		/**
		* Parse Firebase's JavaScript config snippet into a JSON object.
		*
		* Firebase Console gives you JavaScript like:
		* const firebaseConfig = {
		* apiKey: "AIza...",
		* authDomain: "my-project.firebaseapp.com",
		* ...
		* };
		*
		* This function extracts the object and converts it to a parsed object.
		*/
		export function parseFirebaseJsConfig(content) {
		try {
		// Strip single-line comments
		let cleaned = content.replace(/\/\/.*$/gm, '');
		// Strip multi-line comments
		cleaned = cleaned.replace(/\/\[\s\S]?\*\//g, '');
		// Strip import statements
		cleaned = cleaned.replace(/^import\s+.*$/gm, '');
		// Strip lines like: const app = initializeApp(firebaseConfig);
		cleaned = cleaned.replace(/^.initializeApp.$/gm, '');
		// Extract the object literal between first { and last }
		const firstBrace = cleaned.indexOf('{');
		const lastBrace = cleaned.lastIndexOf('}');
		if (firstBrace === -1 \|\| lastBrace === -1 \|\| lastBrace <= firstBrace) {
		return null;
		}
		let objectStr = cleaned.substring(firstBrace, lastBrace + 1);
		// Quote unquoted keys at start of lines: apiKey: → "apiKey":
		// Uses ^ with multiline to avoid matching colons inside string values
		objectStr = objectStr.replace(/^(\s)(\w+)\s:/gm, '$1"$2":');
		// Remove trailing commas before }
		objectStr = objectStr.replace(/,\s*}/g, '}');
		return JSON.parse(objectStr);
		}
		catch {
		return null;
		}
		}
		/**
		* Read a Firebase config file — accepts JSON or JavaScript format.
		*
		* Tries JSON.parse first. If that fails, tries to extract a JS object
		* literal (handles the raw Firebase Console snippet).
		*/
		export function readFirebaseConfigFile(filePath) {
		const resolvedPath = resolveFilePath(filePath);
		try {
		if (!fs.existsSync(resolvedPath)) {
		return { success: false, error: 'not_found', message: `File not found: ${filePath}` };
		}
		const content = fs.readFileSync(resolvedPath, 'utf-8');
		// Try JSON first
		try {
		const data = JSON.parse(content);
		return { success: true, data };
		}
		catch {
		// Not valid JSON — try parsing as JavaScript
		}
		// Try Firebase JS config format
		const parsed = parseFirebaseJsConfig(content);
		if (parsed) {
		return { success: true, data: parsed };
		}
		return {
		success: false,
		error: 'invalid_json',
		message: 'Could not parse file as JSON or Firebase JavaScript config',
		};
		}
		catch (err) {
		if (err instanceof Error && 'code' in err && err.code === 'EACCES') {
		return { success: false, error: 'permission_denied', message: 'Permission denied reading file' };
		}
		return { success: false, error: 'unknown', message: `Error reading file: ${err instanceof Error ? err.message : 'Unknown error'}` };
		}
		}
		/**
		* Resolve file path (expand ~ to home directory)
		*/
		export function resolveFilePath(filePath) {
		return filePath.replace(/^~/, os.homedir());
		}
		/**
		* Check if file exists
		*/
		export function fileExists(filePath) {
		const resolvedPath = resolveFilePath(filePath);
		return fs.existsSync(resolvedPath);
		}
		/**
		* Read and parse a JSON file with detailed error reporting
		*/
		export function readJsonFileWithError(filePath) {
		const resolvedPath = resolveFilePath(filePath);
		try {
		if (!fs.existsSync(resolvedPath)) {
		return { success: false, error: 'not_found', message: `File not found: ${filePath}` };
		}
		const content = fs.readFileSync(resolvedPath, 'utf-8');
		const data = JSON.parse(content);
		return { success: true, data };
		}
		catch (err) {
		if (err instanceof SyntaxError) {
		return { success: false, error: 'invalid_json', message: 'File contains invalid JSON' };
		}
		if (err instanceof Error && 'code' in err && err.code === 'EACCES') {
		return { success: false, error: 'permission_denied', message: 'Permission denied reading file' };
		}
		return { success: false, error: 'unknown', message: `Error reading file: ${err instanceof Error ? err.message : 'Unknown error'}` };
		}
		}
		/**
		* Read and parse a JSON file (simple version, returns null on error)
		*/
		export function readJsonFile(filePath) {
		const result = readJsonFileWithError(filePath);
		return result.success ? result.data : null;
		}
		/**
		* Extract service account config from JSON file
		*/
		export function extractServiceAccountConfig(json) {
		return {
		projectId: json.project_id,
		clientEmail: json.client_email,
		privateKey: json.private_key,
		};
		}
		/**
		* Encode web config for URL parameter (base64url encoding per RFC 4648)
		*
		* The web app decodes this with:
		* const base64 = encoded.replace(/-/g, '+').replace(/_/g, '/');
		* const json = atob(base64);
		* const config = JSON.parse(json);
		*/
		export function encodeWebConfigForUrl(config) {
		const json = JSON.stringify(config);
		return Buffer.from(json, 'utf-8')
		.toString('base64')
		.replace(/\+/g, '-')
		.replace(/\//g, '_')
		.replace(/=+$/, '');
		}
		/**
		* Generate the web dashboard URL with embedded config
		*
		* Note: Firebase web API keys are designed for client-side use and are
		* restricted by Firestore security rules, not by key secrecy. However,
		* users should still avoid sharing this URL publicly.
		*/
		export function generateDashboardUrl(config) {
		const encodedConfig = encodeWebConfigForUrl(config);
		return `https://code-insights.app/?config=${encodedConfig}`;
		}
		//# sourceMappingURL=firebase-json.js.map

-1

dist/utils/firebase-json.js.map

-12

server-dist/dist/index.d.ts

		export interface ServerOptions {
		port: number;
		staticDir: string;
		openBrowser: boolean;
		}
		/**
		* Start the Code Insights local dashboard server.
		* Serves the Hono API and the pre-built Vite SPA from staticDir.
		* Called by the CLI `dashboard` command.
		*/
		export declare function startServer(options: ServerOptions): Promise<void>;
		//# sourceMappingURL=index.d.ts.map

-1

server-dist/dist/index.d.ts.map

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-92

server-dist/dist/index.js

		import { serve } from '@hono/node-server';
		import { serveStatic } from '@hono/node-server/serve-static';
		import { Hono } from 'hono';
		import { existsSync, readFileSync } from 'fs';
		import { relative, join } from 'path';
		import { openUrl } from '@code-insights/cli/utils/browser';
		import projectsRouter from './routes/projects.js';
		import sessionsRouter from './routes/sessions.js';
		import messagesRouter from './routes/messages.js';
		import insightsRouter from './routes/insights.js';
		import analysisRouter from './routes/analysis.js';
		import analyticsRouter from './routes/analytics.js';
		import configRouter from './routes/config.js';
		import exportRouter from './routes/export.js';
		/**
		* Start the Code Insights local dashboard server.
		* Serves the Hono API and the pre-built Vite SPA from staticDir.
		* Called by the CLI `dashboard` command.
		*/
		export async function startServer(options) {
		const { port, staticDir, openBrowser } = options;
		const app = new Hono();
		// Global error handler — prevents stack trace leakage to clients.
		// Detects malformed JSON bodies (SyntaxError) and returns 400 instead of 500.
		app.onError((err, c) => {
		if (err instanceof SyntaxError && err.message.includes('JSON')) {
		return c.json({ error: 'Invalid JSON in request body' }, 400);
		}
		console.error(err);
		return c.json({ error: 'Internal server error' }, 500);
		});
		// API routes — all under /api
		app.route('/api/projects', projectsRouter);
		app.route('/api/sessions', sessionsRouter);
		app.route('/api/messages', messagesRouter);
		app.route('/api/insights', insightsRouter);
		app.route('/api/analysis', analysisRouter);
		app.route('/api/analytics', analyticsRouter);
		app.route('/api/config', configRouter);
		app.route('/api/export', exportRouter);
		// Health check
		app.get('/api/health', (c) => c.json({ ok: true, version: '0.1.0' }));
		// API 404 catch-all — must come AFTER all /api sub-routers and BEFORE static serving.
		// Without this, unmatched /api/* routes fall through to the SPA fallback and return
		// index.html as 200, which breaks API clients expecting JSON errors.
		app.all('/api/*', (c) => c.json({ error: 'Not found' }, 404));
		// Static file serving — only if the dashboard has been built.
		// serveStatic requires a path relative to process.cwd(), not an absolute path.
		if (existsSync(staticDir)) {
		const relativeStaticDir = relative(process.cwd(), staticDir);
		app.use('/*', serveStatic({ root: relativeStaticDir }));
		// Cache index.html at startup — avoids a readFileSync on every SPA navigation
		// request, which would be a pointless disk read for a file that never changes
		// while the server is running.
		const indexPath = join(staticDir, 'index.html');
		const indexHtml = existsSync(indexPath) ? readFileSync(indexPath, 'utf-8') : null;
		// SPA fallback: any non-API route not matched by serveStatic serves index.html
		// so react-router can handle client-side routing.
		app.get('*', (c) => {
		if (indexHtml)
		return c.html(indexHtml);
		return c.text('Dashboard not found. Run pnpm build first.', 404);
		});
		}
		else {
		// Dashboard not built — serve a helpful message
		app.get('*', (c) => c.html(`
		<html><body style="font-family:monospace;padding:2rem">
		<h2>Code Insights Dashboard</h2>
		<p>The dashboard has not been built yet.</p>
		<pre>pnpm install && pnpm build</pre>
		<p>Then restart the server.</p>
		</body></html>
		`));
		}
		// Graceful shutdown: just call process.exit(0).
		// The process 'exit' handler in cli/src/db/client.ts already calls closeDb()
		// which runs WAL checkpoint. Calling closeDb() here would double-close.
		const shutdown = () => {
		process.exit(0);
		};
		process.on('SIGINT', shutdown);
		process.on('SIGTERM', shutdown);
		serve({ fetch: app.fetch, port }, (info) => {
		const url = `http://localhost:${info.port}`;
		console.log(` Code Insights dashboard running at ${url}`);
		if (openBrowser) {
		openUrl(url);
		}
		});
		}
		//# sourceMappingURL=index.js.map

-1

server-dist/dist/index.js.map

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-80

server-dist/dist/llm/analysis.d.ts

		import { type SQLiteMessageRow } from './prompts.js';
		export type { SQLiteMessageRow };
		export interface AnalysisProgress {
		phase: 'loading_messages' \| 'analyzing' \| 'saving';
		currentChunk?: number;
		totalChunks?: number;
		}
		export interface AnalysisOptions {
		onProgress?: (progress: AnalysisProgress) => void;
		signal?: AbortSignal;
		}
		export interface AnalysisResult {
		success: boolean;
		insights: InsightRow[];
		error?: string;
		usage?: {
		inputTokens: number;
		outputTokens: number;
		};
		}
		export interface InsightRow {
		id: string;
		session_id: string;
		project_id: string;
		project_name: string;
		type: string;
		title: string;
		content: string;
		summary: string;
		bullets: string;
		confidence: number;
		source: 'llm';
		metadata: string \| null;
		timestamp: string;
		created_at: string;
		scope: string;
		analysis_version: string;
		}
		export interface SessionData {
		id: string;
		project_id: string;
		project_name: string;
		project_path: string;
		summary: string \| null;
		ended_at: string;
		}
		/**
		* Analyze a session and generate insights, saving them to SQLite.
		*/
		export declare function analyzeSession(session: SessionData, messages: SQLiteMessageRow[], options?: AnalysisOptions): Promise<AnalysisResult>;
		/**
		* Analyze prompt quality for a session.
		*/
		export declare function analyzePromptQuality(session: SessionData, messages: SQLiteMessageRow[], options?: AnalysisOptions): Promise<AnalysisResult>;
		export interface RecurringInsightGroup {
		insightIds: string[];
		theme: string;
		}
		export interface RecurringInsightResult {
		success: boolean;
		groups: RecurringInsightGroup[];
		updatedCount: number;
		error?: string;
		usage?: {
		inputTokens: number;
		outputTokens: number;
		};
		}
		/**
		* Find recurring patterns across multiple insights and write bidirectional links to SQLite.
		*/
		export declare function findRecurringInsights(insights: Array<{
		id: string;
		type: string;
		title: string;
		summary: string;
		project_name: string;
		session_id: string;
		}>): Promise<RecurringInsightResult>;
		//# sourceMappingURL=analysis.d.ts.map

-1

server-dist/dist/llm/analysis.d.ts.map

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-509

server-dist/dist/llm/analysis.js

		// Core analysis engine — server-side.
		// Ported from web repo (src/lib/llm/analysis.ts) with SQLite persistence replacing Firestore.
		// Key differences from web repo:
		// - Uses SQLiteMessageRow instead of web Message type
		// - Writes insights directly to SQLite via getDb() (not Firestore)
		// - Abort handling uses error.name === 'AbortError' (not DOMException)
		// - Uses session's existing project_id from SQLite (not re-derived hash)
		import { randomUUID } from 'crypto';
		import { getDb } from '@code-insights/cli/db/client';
		import { createLLMClient, isLLMConfigured } from './client.js';
		import { SESSION_ANALYSIS_SYSTEM_PROMPT, generateSessionAnalysisPrompt, formatMessagesForAnalysis, parseAnalysisResponse, PROMPT_QUALITY_SYSTEM_PROMPT, generatePromptQualityPrompt, parsePromptQualityResponse, } from './prompts.js';
		// Maximum tokens to send to LLM (leaving room for response)
		const MAX_INPUT_TOKENS = 80000;
		const ANALYSIS_VERSION = '2.0.0';
		/**
		* Analyze a session and generate insights, saving them to SQLite.
		*/
		export async function analyzeSession(session, messages, options) {
		if (!isLLMConfigured()) {
		return {
		success: false,
		insights: [],
		error: 'LLM not configured. Run `code-insights config llm` to configure a provider.',
		};
		}
		if (messages.length === 0) {
		return {
		success: false,
		insights: [],
		error: 'No messages found for this session.',
		};
		}
		try {
		const client = createLLMClient();
		const formattedMessages = formatMessagesForAnalysis(messages);
		const estimatedTokens = client.estimateTokens(formattedMessages);
		let analysisResponse;
		let totalInputTokens = 0;
		let totalOutputTokens = 0;
		if (estimatedTokens > MAX_INPUT_TOKENS) {
		// Chunk the messages and analyze separately
		const chunks = chunkMessages(messages, client.estimateTokens.bind(client));
		const chunkResponses = [];
		const totalChunks = chunks.length;
		for (let i = 0; i < chunks.length; i++) {
		const chunk = chunks[i];
		options?.onProgress?.({ phase: 'analyzing', currentChunk: i + 1, totalChunks });
		const chunkFormatted = formatMessagesForAnalysis(chunk);
		const prompt = generateSessionAnalysisPrompt(session.project_name, session.summary, chunkFormatted);
		const response = await client.chat([
		{ role: 'system', content: SESSION_ANALYSIS_SYSTEM_PROMPT },
		{ role: 'user', content: prompt },
		], { signal: options?.signal });
		if (response.usage) {
		totalInputTokens += response.usage.inputTokens;
		totalOutputTokens += response.usage.outputTokens;
		}
		const parsed = parseAnalysisResponse(response.content);
		if (parsed)
		chunkResponses.push(parsed);
		}
		analysisResponse = mergeAnalysisResponses(chunkResponses);
		}
		else {
		options?.onProgress?.({ phase: 'analyzing', currentChunk: 1, totalChunks: 1 });
		const prompt = generateSessionAnalysisPrompt(session.project_name, session.summary, formattedMessages);
		const response = await client.chat([
		{ role: 'system', content: SESSION_ANALYSIS_SYSTEM_PROMPT },
		{ role: 'user', content: prompt },
		], { signal: options?.signal });
		if (response.usage) {
		totalInputTokens = response.usage.inputTokens;
		totalOutputTokens = response.usage.outputTokens;
		}
		const parsed = parseAnalysisResponse(response.content);
		if (!parsed) {
		return {
		success: false,
		insights: [],
		error: 'Failed to parse LLM response. Please try again.',
		};
		}
		analysisResponse = parsed;
		}
		options?.onProgress?.({ phase: 'saving' });
		const insights = convertToInsightRows(analysisResponse, session);
		// Save new insights first, then delete old non-prompt-quality insights
		// (safe order: if save fails, old data is preserved)
		saveInsightsToDb(insights);
		deleteSessionInsights(session.id, {
		excludeTypes: ['prompt_quality'],
		excludeIds: insights.map(i => i.id),
		});
		return {
		success: true,
		insights,
		usage: { inputTokens: totalInputTokens, outputTokens: totalOutputTokens },
		};
		}
		catch (error) {
		if (error instanceof Error && error.name === 'AbortError') {
		return { success: false, insights: [], error: 'Analysis cancelled' };
		}
		return {
		success: false,
		insights: [],
		error: error instanceof Error ? error.message : 'Analysis failed',
		};
		}
		}
		/**
		* Analyze prompt quality for a session.
		*/
		export async function analyzePromptQuality(session, messages, options) {
		if (!isLLMConfigured()) {
		return {
		success: false,
		insights: [],
		error: 'LLM not configured. Run `code-insights config llm` to configure a provider.',
		};
		}
		if (messages.length === 0) {
		return {
		success: false,
		insights: [],
		error: 'No messages found for this session.',
		};
		}
		const userMessages = messages.filter(m => m.type === 'user');
		if (userMessages.length < 2) {
		return {
		success: false,
		insights: [],
		error: 'Not enough user messages to analyze prompt quality (need at least 2).',
		};
		}
		try {
		const client = createLLMClient();
		const formattedMessages = formatMessagesForAnalysis(messages);
		let analysisInput = formattedMessages;
		const estimatedTokens = client.estimateTokens(formattedMessages);
		if (estimatedTokens > MAX_INPUT_TOKENS) {
		const targetLength = Math.floor((MAX_INPUT_TOKENS / estimatedTokens) * formattedMessages.length * 0.8);
		analysisInput = formattedMessages.slice(0, targetLength) + '\n\n[... conversation truncated for analysis ...]';
		}
		const prompt = generatePromptQualityPrompt(session.project_name, analysisInput, messages.length);
		options?.onProgress?.({ phase: 'analyzing' });
		const response = await client.chat([
		{ role: 'system', content: PROMPT_QUALITY_SYSTEM_PROMPT },
		{ role: 'user', content: prompt },
		], { signal: options?.signal });
		const parsed = parsePromptQualityResponse(response.content);
		if (!parsed) {
		return {
		success: false,
		insights: [],
		error: 'Failed to parse prompt quality analysis. Please try again.',
		};
		}
		options?.onProgress?.({ phase: 'saving' });
		const insight = convertPromptQualityToInsightRow(parsed, session);
		// Save new insight, then delete old prompt_quality insights
		saveInsightsToDb([insight]);
		deleteSessionInsights(session.id, {
		includeOnlyTypes: ['prompt_quality'],
		excludeIds: [insight.id],
		});
		return {
		success: true,
		insights: [insight],
		usage: response.usage ? {
		inputTokens: response.usage.inputTokens,
		outputTokens: response.usage.outputTokens,
		} : undefined,
		};
		}
		catch (error) {
		if (error instanceof Error && error.name === 'AbortError') {
		return { success: false, insights: [], error: 'Analysis cancelled' };
		}
		return {
		success: false,
		insights: [],
		error: error instanceof Error ? error.message : 'Prompt quality analysis failed',
		};
		}
		}
		/**
		* Find recurring patterns across multiple insights and write bidirectional links to SQLite.
		*/
		export async function findRecurringInsights(insights) {
		if (!isLLMConfigured()) {
		return { success: false, groups: [], updatedCount: 0, error: 'LLM not configured.' };
		}
		const candidates = insights
		.filter(i => i.type !== 'summary' && i.type !== 'prompt_quality')
		.slice(0, 200);
		if (candidates.length < 2) {
		return {
		success: false,
		groups: [],
		updatedCount: 0,
		error: 'Need at least 2 non-summary insights to find patterns.',
		};
		}
		try {
		const client = createLLMClient();
		const insightData = candidates.map(i => ({
		id: i.id,
		type: i.type === 'technique' ? 'learning' : i.type,
		title: i.title,
		summary: i.summary.slice(0, 150),
		projectName: i.project_name,
		sessionId: i.session_id,
		}));
		const prompt = `Analyze these insights from coding sessions and find groups of semantically similar or duplicate insights — ones that express the same learning or decision even if worded differently.

		RULES:
		- Only group insights that are genuinely about the same concept/topic
		- Insights in a group should be from DIFFERENT sessions (same sessionId = not recurring)
		- A group must have at least 2 insights
		- An insight can only belong to one group
		- Provide a brief "theme" describing what the group shares
		- If no recurring patterns exist, return an empty groups array

		INSIGHTS:
		${JSON.stringify(insightData, null, 2)}

		Respond with valid JSON only:
		{
		"groups": [
		{
		"insightIds": ["insight_abc", "insight_def"],
		"theme": "Brief description of the shared concept"
		}
		]
		}`;
		const response = await client.chat([
		{
		role: 'system',
		content: 'You are an expert at identifying recurring patterns and themes across software development insights. You find semantically similar insights even when they are worded differently. Respond with valid JSON only.',
		},
		{ role: 'user', content: prompt },
		]);
		const jsonMatch = response.content.match(/\{[\s\S]*\}/);
		if (!jsonMatch) {
		return { success: false, groups: [], updatedCount: 0, error: 'Failed to parse recurring insights response.' };
		}
		const parsed = JSON.parse(jsonMatch[0]);
		const groups = parsed.groups \|\| [];
		const validIds = new Set(candidates.map(i => i.id));
		const validGroups = groups
		.map(g => ({
		...g,
		insightIds: g.insightIds.filter(id => validIds.has(id)),
		}))
		.filter(g => g.insightIds.length >= 2);
		if (validGroups.length === 0) {
		return {
		success: true,
		groups: [],
		updatedCount: 0,
		usage: response.usage
		? { inputTokens: response.usage.inputTokens, outputTokens: response.usage.outputTokens }
		: undefined,
		};
		}
		// Build bidirectional links
		const linkMap = new Map();
		for (const group of validGroups) {
		for (const id of group.insightIds) {
		const others = group.insightIds.filter(otherId => otherId !== id);
		const existing = linkMap.get(id) \|\| [];
		linkMap.set(id, [...new Set([...existing, ...others])]);
		}
		}
		// Write links to SQLite
		const db = getDb();
		const updateLinks = db.prepare(`UPDATE insights SET linked_insight_ids = ? WHERE id = ?`);
		for (const [insightId, linkedIds] of linkMap.entries()) {
		updateLinks.run(JSON.stringify(linkedIds), insightId);
		}
		return {
		success: true,
		groups: validGroups,
		updatedCount: linkMap.size,
		usage: response.usage
		? { inputTokens: response.usage.inputTokens, outputTokens: response.usage.outputTokens }
		: undefined,
		};
		}
		catch (error) {
		return {
		success: false,
		groups: [],
		updatedCount: 0,
		error: error instanceof Error ? error.message : 'Failed to find recurring insights',
		};
		}
		}
		// --- Internal helpers ---
		function chunkMessages(messages, estimateTokens) {
		const chunks = [];
		let currentChunk = [];
		let currentTokens = 0;
		const chunkLimit = MAX_INPUT_TOKENS * 0.8;
		for (const message of messages) {
		let toolResults = [];
		try {
		toolResults = message.tool_results ? JSON.parse(message.tool_results) : [];
		}
		catch {
		toolResults = [];
		}
		const messageText = [
		message.content,
		message.thinking?.slice(0, 1000) ?? '',
		...toolResults.map(r => (r.output \|\| '').slice(0, 200)),
		].join(' ');
		const messageTokens = estimateTokens(messageText);
		if (currentTokens + messageTokens > chunkLimit && currentChunk.length > 0) {
		chunks.push(currentChunk);
		currentChunk = [];
		currentTokens = 0;
		}
		currentChunk.push(message);
		currentTokens += messageTokens;
		}
		if (currentChunk.length > 0) {
		chunks.push(currentChunk);
		}
		return chunks;
		}
		function mergeAnalysisResponses(responses) {
		if (responses.length === 0) {
		return {
		summary: { title: 'Analysis failed', content: '', bullets: [] },
		decisions: [],
		learnings: [],
		};
		}
		if (responses.length === 1)
		return responses[0];
		const merged = {
		summary: responses[0].summary,
		decisions: [],
		learnings: [],
		};
		for (const response of responses) {
		merged.decisions.push(...response.decisions);
		merged.learnings.push(...response.learnings);
		}
		merged.decisions = deduplicateByTitle(merged.decisions).slice(0, 3);
		merged.learnings = deduplicateByTitle(merged.learnings).slice(0, 5);
		return merged;
		}
		function deduplicateByTitle(items) {
		const seen = new Set();
		return items.filter((item) => {
		const normalized = item.title.toLowerCase().trim();
		if (seen.has(normalized))
		return false;
		seen.add(normalized);
		return true;
		});
		}
		function convertToInsightRows(response, session) {
		const insights = [];
		const now = new Date().toISOString();
		insights.push({
		id: randomUUID(),
		session_id: session.id,
		project_id: session.project_id,
		project_name: session.project_name,
		type: 'summary',
		title: response.summary.title,
		content: response.summary.content,
		summary: response.summary.content,
		bullets: JSON.stringify(response.summary.bullets),
		confidence: 0.9,
		source: 'llm',
		metadata: null,
		timestamp: session.ended_at,
		created_at: now,
		scope: 'session',
		analysis_version: ANALYSIS_VERSION,
		});
		for (const decision of response.decisions) {
		const confidence = decision.confidence ?? 85;
		if (confidence < 70)
		continue;
		insights.push({
		id: randomUUID(),
		session_id: session.id,
		project_id: session.project_id,
		project_name: session.project_name,
		type: 'decision',
		title: decision.title,
		content: decision.content,
		summary: decision.content.slice(0, 200),
		bullets: JSON.stringify(decision.alternatives \|\| []),
		confidence: confidence / 100,
		source: 'llm',
		metadata: JSON.stringify({
		reasoning: decision.reasoning,
		alternatives: decision.alternatives,
		evidence: decision.evidence,
		}),
		timestamp: session.ended_at,
		created_at: now,
		scope: 'session',
		analysis_version: ANALYSIS_VERSION,
		});
		}
		for (const learning of response.learnings) {
		const confidence = learning.confidence ?? 80;
		if (confidence < 70)
		continue;
		insights.push({
		id: randomUUID(),
		session_id: session.id,
		project_id: session.project_id,
		project_name: session.project_name,
		type: 'learning',
		title: learning.title,
		content: learning.content,
		summary: learning.content.slice(0, 200),
		bullets: JSON.stringify([]),
		confidence: confidence / 100,
		source: 'llm',
		metadata: JSON.stringify({
		context: learning.context,
		evidence: learning.evidence,
		}),
		timestamp: session.ended_at,
		created_at: now,
		scope: 'session',
		analysis_version: ANALYSIS_VERSION,
		});
		}
		return insights;
		}
		function convertPromptQualityToInsightRow(response, session) {
		const now = new Date().toISOString();
		return {
		id: randomUUID(),
		session_id: session.id,
		project_id: session.project_id,
		project_name: session.project_name,
		type: 'prompt_quality',
		title: `Prompt Efficiency: ${response.efficiencyScore}/100`,
		content: response.overallAssessment,
		summary: response.overallAssessment,
		bullets: JSON.stringify(response.tips),
		confidence: 0.85,
		source: 'llm',
		metadata: JSON.stringify({
		efficiencyScore: response.efficiencyScore,
		wastedTurns: response.wastedTurns,
		antiPatterns: response.antiPatterns,
		potentialMessageReduction: response.potentialMessageReduction,
		}),
		timestamp: session.ended_at,
		created_at: now,
		scope: 'session',
		analysis_version: ANALYSIS_VERSION,
		};
		}
		/**
		* Write insight rows to SQLite using prepared statements.
		*/
		function saveInsightsToDb(insights) {
		const db = getDb();
		const insert = db.prepare(`
		INSERT OR REPLACE INTO insights (
		id, session_id, project_id, project_name, type, title, content,
		summary, bullets, confidence, source, metadata, timestamp,
		created_at, scope, analysis_version
		) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)
		`);
		const insertMany = db.transaction((rows) => {
		for (const row of rows) {
		insert.run(row.id, row.session_id, row.project_id, row.project_name, row.type, row.title, row.content, row.summary, row.bullets, row.confidence, row.source, row.metadata, row.timestamp, row.created_at, row.scope, row.analysis_version);
		}
		});
		insertMany(insights);
		}
		/**
		* Delete insights for a session, with optional type and ID exclusions.
		*/
		function deleteSessionInsights(sessionId, opts) {
		const db = getDb();
		const conditions = ['session_id = ?'];
		const params = [sessionId];
		if (opts.excludeTypes && opts.excludeTypes.length > 0) {
		conditions.push(`type NOT IN (${opts.excludeTypes.map(() => '?').join(', ')})`);
		params.push(...opts.excludeTypes);
		}
		if (opts.includeOnlyTypes && opts.includeOnlyTypes.length > 0) {
		conditions.push(`type IN (${opts.includeOnlyTypes.map(() => '?').join(', ')})`);
		params.push(...opts.includeOnlyTypes);
		}
		if (opts.excludeIds && opts.excludeIds.length > 0) {
		conditions.push(`id NOT IN (${opts.excludeIds.map(() => '?').join(', ')})`);
		params.push(...opts.excludeIds);
		}
		db.prepare(`DELETE FROM insights WHERE ${conditions.join(' AND ')}`).run(...params);
		}
		//# sourceMappingURL=analysis.js.map

-1

server-dist/dist/llm/analysis.js.map

-27

server-dist/dist/llm/client.d.ts

		import type { LLMClient } from './types.js';
		import type { LLMProviderConfig } from './types.js';
		/**
		* Load LLM config from the CLI config file.
		*/
		export declare function loadLLMConfig(): LLMProviderConfig \| null;
		/**
		* Check if LLM is configured.
		*/
		export declare function isLLMConfigured(): boolean;
		/**
		* Create an LLM client from the current config.
		* Throws if LLM is not configured.
		*/
		export declare function createLLMClient(): LLMClient;
		/**
		* Create an LLM client from a specific config object (used for testing).
		*/
		export declare function createClientFromConfig(config: LLMProviderConfig): LLMClient;
		/**
		* Test LLM connectivity with the given config.
		*/
		export declare function testLLMConfig(config: LLMProviderConfig): Promise<{
		success: boolean;
		error?: string;
		}>;
		//# sourceMappingURL=client.d.ts.map

-1

server-dist/dist/llm/client.d.ts.map

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-71

server-dist/dist/llm/client.js

		// LLM client factory — server-side.
		// Config is loaded from ~/.code-insights/config.json via the CLI config system.
		// No localStorage or browser APIs used here.
		import { loadConfig } from '@code-insights/cli/utils/config';
		import { createOpenAIClient } from './providers/openai.js';
		import { createAnthropicClient } from './providers/anthropic.js';
		import { createGeminiClient } from './providers/gemini.js';
		import { createOllamaClient } from './providers/ollama.js';
		/**
		* Load LLM config from the CLI config file.
		*/
		export function loadLLMConfig() {
		const config = loadConfig();
		return config?.dashboard?.llm ?? null;
		}
		/**
		* Check if LLM is configured.
		*/
		export function isLLMConfigured() {
		const llm = loadLLMConfig();
		if (!llm)
		return false;
		if (llm.provider === 'ollama')
		return !!llm.model;
		return !!llm.apiKey && !!llm.model;
		}
		/**
		* Create an LLM client from the current config.
		* Throws if LLM is not configured.
		*/
		export function createLLMClient() {
		const config = loadLLMConfig();
		if (!config) {
		throw new Error('LLM not configured. Run `code-insights config llm` to configure a provider.');
		}
		return createClientFromConfig(config);
		}
		/**
		* Create an LLM client from a specific config object (used for testing).
		*/
		export function createClientFromConfig(config) {
		switch (config.provider) {
		case 'openai':
		return createOpenAIClient(config.apiKey ?? '', config.model);
		case 'anthropic':
		return createAnthropicClient(config.apiKey ?? '', config.model);
		case 'gemini':
		return createGeminiClient(config.apiKey ?? '', config.model);
		case 'ollama':
		return createOllamaClient(config.model, config.baseUrl);
		default:
		throw new Error(`Unknown LLM provider: ${config.provider}`);
		}
		}
		/**
		* Test LLM connectivity with the given config.
		*/
		export async function testLLMConfig(config) {
		try {
		const client = createClientFromConfig(config);
		await client.chat([{ role: 'user', content: 'Say "ok" and nothing else.' }]);
		return { success: true };
		}
		catch (error) {
		return {
		success: false,
		error: error instanceof Error ? error.message : 'Unknown error',
		};
		}
		}
		//# sourceMappingURL=client.js.map

-1

server-dist/dist/llm/client.js.map

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-7

server-dist/dist/llm/index.d.ts

		export type { LLMClient, LLMMessage, LLMResponse, ChatOptions } from './types.js';
		export type { LLMProvider, LLMProviderConfig } from './types.js';
		export { createLLMClient, createClientFromConfig, loadLLMConfig, isLLMConfigured, testLLMConfig } from './client.js';
		export { analyzeSession, analyzePromptQuality, findRecurringInsights } from './analysis.js';
		export type { AnalysisResult, InsightRow, SessionData, RecurringInsightResult } from './analysis.js';
		export { discoverOllamaModels } from './providers/ollama.js';
		//# sourceMappingURL=index.d.ts.map

-1

server-dist/dist/llm/index.d.ts.map

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-5

server-dist/dist/llm/index.js

		// Public API for the server-side LLM engine.
		export { createLLMClient, createClientFromConfig, loadLLMConfig, isLLMConfigured, testLLMConfig } from './client.js';
		export { analyzeSession, analyzePromptQuality, findRecurringInsights } from './analysis.js';
		export { discoverOllamaModels } from './providers/ollama.js';
		//# sourceMappingURL=index.js.map

-1

server-dist/dist/llm/index.js.map

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-73

server-dist/dist/llm/prompts.d.ts

		export interface SQLiteMessageRow {
		id: string;
		session_id: string;
		type: 'user' \| 'assistant' \| 'system';
		content: string;
		thinking: string \| null;
		tool_calls: string;
		tool_results: string;
		usage: string \| null;
		timestamp: string;
		parent_id: string \| null;
		}
		/**
		* Format SQLite message rows for LLM consumption.
		* Handles snake_case fields and JSON-encoded tool_calls/tool_results.
		*/
		export declare function formatMessagesForAnalysis(messages: SQLiteMessageRow[]): string;
		/**
		* System prompt for session analysis.
		*/
		export declare const SESSION_ANALYSIS_SYSTEM_PROMPT = "You are an expert at analyzing software development conversations and extracting valuable insights. Your task is to analyze an AI coding session (a conversation between a user and an AI coding assistant) and extract structured insights.\n\nYou will identify:\n1. Summary: A high-level narrative of what was accomplished\n2. Decisions: Technical choices made, including reasoning and alternatives considered (max 3)\n3. Learnings: Technical discoveries, gotchas, problem-solving approaches, debugging strategies, or transferable knowledge (max 5)\n\nQuality Standards:\n- Only include insights you would write in a team knowledge base for future reference\n- Each insight MUST reference concrete details: specific file names, library names, error messages, API endpoints, or code patterns\n- Do not invent file names, APIs, errors, or details not present in the conversation\n- Rate your confidence in each insight's value (0-100). Only include insights you rate 70+.\n- It is better to return 0 insights in a category than to include generic or trivial ones\n- If a session is straightforward with no notable decisions or learnings, say so in the summary and leave other categories empty\n- The summary must mention the most important concrete artifact changed (file, endpoint, or test) if any\n\nDO NOT include insights like these (too generic/trivial):\n- \"Used debugging techniques to fix an issue\"\n- \"Made architectural decisions about the codebase\"\n- \"Implemented a new feature\" (the summary already covers this)\n- \"Used React hooks for state management\" (too generic without specifics)\n- \"Fixed a bug in the code\" (what bug? what was the root cause?)\n- Anything that restates the task without adding transferable knowledge\n\nRespond with valid JSON only, wrapped in <json>...</json> tags. Do not include any other text.";
		/**
		* Generate the user prompt for session analysis.
		*/
		export declare function generateSessionAnalysisPrompt(projectName: string, sessionSummary: string \| null, formattedMessages: string): string;
		export interface AnalysisResponse {
		summary: {
		title: string;
		content: string;
		bullets: string[];
		};
		decisions: Array<{
		title: string;
		content: string;
		reasoning: string;
		alternatives?: string[];
		confidence?: number;
		evidence?: string[];
		}>;
		learnings: Array<{
		title: string;
		content: string;
		context: string;
		confidence?: number;
		evidence?: string[];
		}>;
		}
		/**
		* Parse the LLM response into structured insights.
		*/
		export declare function parseAnalysisResponse(response: string): AnalysisResponse \| null;
		export declare const PROMPT_QUALITY_SYSTEM_PROMPT = "You are an expert at analyzing how effectively humans communicate with AI coding assistants. Your task is to review a conversation between a user and Claude Code, and evaluate the user's prompting efficiency.\n\nYou will identify:\n1. Wasted turns: User messages that led to clarifications, corrections, or repeated instructions because the original prompt was unclear, missing context, or too vague.\n2. Anti-patterns: Recurring bad habits in the user's prompting style.\n3. Efficiency score: A 0-100 rating of how optimally the user communicated.\n4. Actionable tips: Specific improvements the user can make.\n\nGuidelines:\n- Focus on USER messages only \u2014 don't critique the assistant's responses\n- A \"wasted turn\" is when the user had to send a follow-up message to clarify, correct, or repeat something that could have been included in the original prompt\n- Only mark a wasted turn if the assistant explicitly asked for clarification or corrected a misunderstanding\n- Common anti-patterns: vague instructions, missing file paths, not providing error messages, incomplete requirements, repeated instructions, not specifying what \"it\" refers to\n- Be constructive, not judgmental \u2014 the goal is to help users improve\n- Consider the context: some clarification exchanges are normal and expected\n- A score of 100 means every user message was perfectly clear and complete\n- A score of 50 means about half the messages could have been more efficient\n\nRespond with valid JSON only, wrapped in <json>...</json> tags. Do not include any other text.";
		export declare function generatePromptQualityPrompt(projectName: string, formattedMessages: string, messageCount: number): string;
		export interface WastedTurn {
		messageIndex: number;
		reason: string;
		suggestedRewrite: string;
		}
		export interface AntiPattern {
		name: string;
		count: number;
		examples: string[];
		}
		export interface PromptQualityResponse {
		efficiencyScore: number;
		potentialMessageReduction: number;
		overallAssessment: string;
		wastedTurns: WastedTurn[];
		antiPatterns: AntiPattern[];
		tips: string[];
		}
		export declare function parsePromptQualityResponse(response: string): PromptQualityResponse \| null;
		//# sourceMappingURL=prompts.d.ts.map

-1

server-dist/dist/llm/prompts.d.ts.map

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-242

server-dist/dist/llm/prompts.js

		// Analysis prompts and response parsers for LLM session analysis.
		// Ported from web repo (src/lib/llm/prompts.ts) with SQLite-aware message formatting.
		/**
		* Format SQLite message rows for LLM consumption.
		* Handles snake_case fields and JSON-encoded tool_calls/tool_results.
		*/
		export function formatMessagesForAnalysis(messages) {
		let userIndex = 0;
		let assistantIndex = 0;
		return messages
		.map((m) => {
		const role = m.type === 'user' ? 'User' : m.type === 'assistant' ? 'Assistant' : 'System';
		const roleLabel = role === 'User'
		? `User#${userIndex++}`
		: role === 'Assistant'
		? `Assistant#${assistantIndex++}`
		: 'System';
		// Parse JSON-encoded tool_calls
		let toolCalls = [];
		try {
		toolCalls = m.tool_calls ? JSON.parse(m.tool_calls) : [];
		}
		catch {
		toolCalls = [];
		}
		// Parse JSON-encoded tool_results
		let toolResults = [];
		try {
		toolResults = m.tool_results ? JSON.parse(m.tool_results) : [];
		}
		catch {
		toolResults = [];
		}
		const toolInfo = toolCalls.length > 0
		? `\n[Tools used: ${toolCalls.map(t => t.name \|\| 'unknown').join(', ')}]`
		: '';
		// Include thinking content — capped at 1000 chars to stay within token budget
		const thinkingInfo = m.thinking
		? `\n[Thinking: ${m.thinking.slice(0, 1000)}]`
		: '';
		// Include tool results for context — 200 chars per result
		const resultInfo = toolResults.length > 0
		? `\n[Tool results: ${toolResults.map(r => (r.output \|\| '').slice(0, 200)).join(' \| ')}]`
		: '';
		return `### ${roleLabel}:\n${m.content}${thinkingInfo}${toolInfo}${resultInfo}`;
		})
		.join('\n\n');
		}
		/**
		* System prompt for session analysis.
		*/
		export const SESSION_ANALYSIS_SYSTEM_PROMPT = `You are an expert at analyzing software development conversations and extracting valuable insights. Your task is to analyze an AI coding session (a conversation between a user and an AI coding assistant) and extract structured insights.

		You will identify:
		1. Summary: A high-level narrative of what was accomplished
		2. Decisions: Technical choices made, including reasoning and alternatives considered (max 3)
		3. Learnings: Technical discoveries, gotchas, problem-solving approaches, debugging strategies, or transferable knowledge (max 5)

		Quality Standards:
		- Only include insights you would write in a team knowledge base for future reference
		- Each insight MUST reference concrete details: specific file names, library names, error messages, API endpoints, or code patterns
		- Do not invent file names, APIs, errors, or details not present in the conversation
		- Rate your confidence in each insight's value (0-100). Only include insights you rate 70+.
		- It is better to return 0 insights in a category than to include generic or trivial ones
		- If a session is straightforward with no notable decisions or learnings, say so in the summary and leave other categories empty
		- The summary must mention the most important concrete artifact changed (file, endpoint, or test) if any

		DO NOT include insights like these (too generic/trivial):
		- "Used debugging techniques to fix an issue"
		- "Made architectural decisions about the codebase"
		- "Implemented a new feature" (the summary already covers this)
		- "Used React hooks for state management" (too generic without specifics)
		- "Fixed a bug in the code" (what bug? what was the root cause?)
		- Anything that restates the task without adding transferable knowledge

		Respond with valid JSON only, wrapped in <json>...</json> tags. Do not include any other text.`;
		/**
		* Generate the user prompt for session analysis.
		*/
		export function generateSessionAnalysisPrompt(projectName, sessionSummary, formattedMessages) {
		return `Analyze this AI coding session and extract insights.

		Project: ${projectName}
		${sessionSummary ? `Session Summary: ${sessionSummary}\n` : ''}
		--- CONVERSATION ---
		${formattedMessages}
		--- END CONVERSATION ---

		Extract insights in this JSON format:
		{
		"summary": {
		"title": "Brief title describing main accomplishment (max 60 chars)",
		"content": "2-3 sentence narrative of what was accomplished",
		"bullets": ["Key point 1", "Key point 2", "Key point 3"]
		},
		"decisions": [
		{
		"title": "The specific decision made (max 60 chars)",
		"content": "Detailed explanation with concrete details",
		"reasoning": "Why this choice was made over alternatives",
		"alternatives": ["Alternative 1 considered", "Alternative 2 considered"],
		"confidence": 85,
		"evidence": ["User#4: ...", "Assistant#5: ..."]
		}
		],
		"learnings": [
		{
		"title": "Specific thing learned (max 60 chars)",
		"content": "Detailed explanation with concrete details",
		"context": "When/where this applies and why it matters",
		"confidence": 80,
		"evidence": ["User#7: ...", "Assistant#8: ..."]
		}
		]
		}

		Only include insights rated 70+ confidence. If you cannot cite evidence, drop the insight. Return empty arrays for categories with no strong insights. Max 3 decisions, 5 learnings.
		Evidence should reference the labeled turns in the conversation (e.g., "User#2", "Assistant#5").

		Respond with valid JSON only, wrapped in <json>...</json> tags. Do not include any other text.`;
		}
		function extractJsonPayload(response) {
		const tagged = response.match(/<json>\s([\s\S]?)\s*<\/json>/i);
		if (tagged?.[1])
		return tagged[1].trim();
		const jsonMatch = response.match(/\{[\s\S]*\}/);
		return jsonMatch ? jsonMatch[0] : null;
		}
		/**
		* Parse the LLM response into structured insights.
		*/
		export function parseAnalysisResponse(response) {
		try {
		const jsonPayload = extractJsonPayload(response);
		if (!jsonPayload) {
		console.error('No JSON found in analysis response');
		return null;
		}
		const parsed = JSON.parse(jsonPayload);
		if (!parsed.summary \|\| typeof parsed.summary.title !== 'string') {
		console.error('Invalid analysis response structure');
		return null;
		}
		parsed.decisions = parsed.decisions \|\| [];
		parsed.learnings = parsed.learnings \|\| [];
		return parsed;
		}
		catch (error) {
		console.error('Failed to parse analysis response:', error);
		return null;
		}
		}
		// --- Prompt Quality Analysis ---
		export const PROMPT_QUALITY_SYSTEM_PROMPT = `You are an expert at analyzing how effectively humans communicate with AI coding assistants. Your task is to review a conversation between a user and Claude Code, and evaluate the user's prompting efficiency.

		You will identify:
		1. Wasted turns: User messages that led to clarifications, corrections, or repeated instructions because the original prompt was unclear, missing context, or too vague.
		2. Anti-patterns: Recurring bad habits in the user's prompting style.
		3. Efficiency score: A 0-100 rating of how optimally the user communicated.
		4. Actionable tips: Specific improvements the user can make.

		Guidelines:
		- Focus on USER messages only — don't critique the assistant's responses
		- A "wasted turn" is when the user had to send a follow-up message to clarify, correct, or repeat something that could have been included in the original prompt
		- Only mark a wasted turn if the assistant explicitly asked for clarification or corrected a misunderstanding
		- Common anti-patterns: vague instructions, missing file paths, not providing error messages, incomplete requirements, repeated instructions, not specifying what "it" refers to
		- Be constructive, not judgmental — the goal is to help users improve
		- Consider the context: some clarification exchanges are normal and expected
		- A score of 100 means every user message was perfectly clear and complete
		- A score of 50 means about half the messages could have been more efficient

		Respond with valid JSON only, wrapped in <json>...</json> tags. Do not include any other text.`;
		export function generatePromptQualityPrompt(projectName, formattedMessages, messageCount) {
		return `Analyze the user's prompting efficiency in this AI coding session.

		Project: ${projectName}
		Total messages: ${messageCount}

		--- CONVERSATION ---
		${formattedMessages}
		--- END CONVERSATION ---

		Evaluate the user's prompting quality and respond with this JSON format:
		{
		"efficiencyScore": 75,
		"potentialMessageReduction": 3,
		"overallAssessment": "2-3 sentence summary of the user's prompting style and efficiency",
		"wastedTurns": [
		{
		"messageIndex": 5,
		"reason": "Missing context — didn't specify which file to modify",
		"suggestedRewrite": "A better version of the user's original message that would have avoided the follow-up"
		}
		],
		"antiPatterns": [
		{
		"name": "Vague Instructions",
		"count": 3,
		"examples": ["fix it", "make it work", "do the thing"]
		}
		],
		"tips": [
		"Always include file paths when asking to modify code",
		"Provide error messages verbatim when reporting bugs"
		]
		}

		Rules:
		- messageIndex refers to the 0-based index of the USER message, as labeled in the conversation (e.g., User#0)
		- Only include genuinely wasted turns, not normal back-and-forth
		- Tips should be specific and actionable, not generic; include the relevant user message index in parentheses
		- If the user prompted well, say so — don't manufacture issues
		- potentialMessageReduction is how many fewer messages the session could have taken with better prompts

		Respond with valid JSON only, wrapped in <json>...</json> tags. Do not include any other text.`;
		}
		export function parsePromptQualityResponse(response) {
		try {
		const jsonPayload = extractJsonPayload(response);
		if (!jsonPayload) {
		console.error('No JSON found in prompt quality response');
		return null;
		}
		const parsed = JSON.parse(jsonPayload);
		if (typeof parsed.efficiencyScore !== 'number') {
		console.error('Invalid prompt quality response: missing efficiencyScore');
		return null;
		}
		parsed.efficiencyScore = Math.max(0, Math.min(100, Math.round(parsed.efficiencyScore)));
		parsed.potentialMessageReduction = parsed.potentialMessageReduction \|\| 0;
		parsed.overallAssessment = parsed.overallAssessment \|\| '';
		parsed.wastedTurns = parsed.wastedTurns \|\| [];
		parsed.antiPatterns = parsed.antiPatterns \|\| [];
		parsed.tips = parsed.tips \|\| [];
		return parsed;
		}
		catch (error) {
		console.error('Failed to parse prompt quality response:', error);
		return null;
		}
		}
		//# sourceMappingURL=prompts.js.map

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server-dist/dist/llm/prompts.js.map

-3

server-dist/dist/llm/providers/anthropic.d.ts

		import type { LLMClient } from '../types.js';
		export declare function createAnthropicClient(apiKey: string, model: string): LLMClient;
		//# sourceMappingURL=anthropic.d.ts.map

-1

server-dist/dist/llm/providers/anthropic.d.ts.map

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-45

server-dist/dist/llm/providers/anthropic.js

		// Anthropic provider implementation (server-side, no browser dependencies)
		// Note: 'anthropic-dangerous-direct-browser-access' header is intentionally omitted here —
		// this runs server-side where direct API access is safe and expected.
		export function createAnthropicClient(apiKey, model) {
		return {
		provider: 'anthropic',
		model,
		async chat(messages, options) {
		// Extract system message if present
		const systemMessage = messages.find(m => m.role === 'system');
		const chatMessages = messages.filter(m => m.role !== 'system');
		const response = await fetch('https://api.anthropic.com/v1/messages', {
		method: 'POST',
		headers: {
		'Content-Type': 'application/json',
		'x-api-key': apiKey,
		'anthropic-version': '2023-06-01',
		},
		signal: options?.signal,
		body: JSON.stringify({
		model,
		max_tokens: 4096,
		system: systemMessage?.content,
		messages: chatMessages.map(m => ({ role: m.role, content: m.content })),
		}),
		});
		if (!response.ok) {
		const error = await response.json().catch(() => ({}));
		throw new Error(error.error?.message \|\| `Anthropic API error: ${response.status}`);
		}
		const data = await response.json();
		return {
		content: data.content[0]?.text \|\| '',
		usage: data.usage ? {
		inputTokens: data.usage.input_tokens,
		outputTokens: data.usage.output_tokens,
		} : undefined,
		};
		},
		estimateTokens(text) {
		return Math.ceil(text.length / 4);
		},
		};
		}
		//# sourceMappingURL=anthropic.js.map

-1

server-dist/dist/llm/providers/anthropic.js.map

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-3

server-dist/dist/llm/providers/gemini.d.ts

		import type { LLMClient } from '../types.js';
		export declare function createGeminiClient(apiKey: string, model: string): LLMClient;
		//# sourceMappingURL=gemini.d.ts.map

-1

server-dist/dist/llm/providers/gemini.d.ts.map

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-51

server-dist/dist/llm/providers/gemini.js

		// Gemini provider implementation (server-side, no browser dependencies)
		export function createGeminiClient(apiKey, model) {
		return {
		provider: 'gemini',
		model,
		async chat(messages, options) {
		const systemMessage = messages.find(m => m.role === 'system');
		const chatMessages = messages.filter(m => m.role !== 'system');
		const contents = chatMessages.map(m => ({
		role: m.role === 'assistant' ? 'model' : 'user',
		parts: [{ text: m.content }],
		}));
		const body = {
		contents,
		generationConfig: {
		temperature: 0.7,
		maxOutputTokens: 4096,
		},
		};
		if (systemMessage) {
		body.systemInstruction = {
		parts: [{ text: systemMessage.content }],
		};
		}
		// Gemini REST API requires the API key as a query parameter (not a header).
		// This is Google's documented authentication pattern for the Generative Language API.
		const response = await fetch(`https://generativelanguage.googleapis.com/v1beta/models/${model}:generateContent?key=${apiKey}`, {
		method: 'POST',
		headers: { 'Content-Type': 'application/json' },
		signal: options?.signal,
		body: JSON.stringify(body),
		});
		if (!response.ok) {
		const error = await response.json().catch(() => ({}));
		throw new Error(error.error?.message \|\| `Gemini API error: ${response.status}`);
		}
		const data = await response.json();
		return {
		content: data.candidates?.[0]?.content?.parts?.[0]?.text \|\| '',
		usage: data.usageMetadata ? {
		inputTokens: data.usageMetadata.promptTokenCount,
		outputTokens: data.usageMetadata.candidatesTokenCount,
		} : undefined,
		};
		},
		estimateTokens(text) {
		return Math.ceil(text.length / 4);
		},
		};
		}
		//# sourceMappingURL=gemini.js.map

-1

server-dist/dist/llm/providers/gemini.js.map

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-12

server-dist/dist/llm/providers/ollama.d.ts

		import type { LLMClient } from '../types.js';
		export declare function createOllamaClient(model: string, baseUrl?: string): LLMClient;
		/**
		* Discover installed Ollama models by querying the local API.
		* Returns empty array if Ollama is not running or unreachable.
		*/
		export declare function discoverOllamaModels(baseUrl?: string): Promise<Array<{
		name: string;
		size: number;
		modifiedAt: string;
		}>>;
		//# sourceMappingURL=ollama.d.ts.map

-1

server-dist/dist/llm/providers/ollama.d.ts.map

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-61

server-dist/dist/llm/providers/ollama.js

		// Ollama provider implementation (local models, no API key required)
		const DEFAULT_OLLAMA_URL = 'http://localhost:11434';
		export function createOllamaClient(model, baseUrl) {
		const url = baseUrl \|\| DEFAULT_OLLAMA_URL;
		return {
		provider: 'ollama',
		model,
		async chat(messages, options) {
		const response = await fetch(`${url}/api/chat`, {
		method: 'POST',
		headers: { 'Content-Type': 'application/json' },
		signal: options?.signal,
		body: JSON.stringify({
		model,
		messages: messages.map(m => ({ role: m.role, content: m.content })),
		stream: false,
		options: { temperature: 0.7 },
		}),
		});
		if (!response.ok) {
		const error = await response.text().catch(() => '');
		throw new Error(`Ollama API error: ${response.status}${error ? ` - ${error}` : ''}`);
		}
		const data = await response.json();
		return {
		content: data.message?.content \|\| '',
		usage: {
		inputTokens: data.prompt_eval_count \|\| 0,
		outputTokens: data.eval_count \|\| 0,
		},
		};
		},
		estimateTokens(text) {
		return Math.ceil(text.length / 4);
		},
		};
		}
		/**
		* Discover installed Ollama models by querying the local API.
		* Returns empty array if Ollama is not running or unreachable.
		*/
		export async function discoverOllamaModels(baseUrl) {
		const url = baseUrl \|\| DEFAULT_OLLAMA_URL;
		try {
		const response = await fetch(`${url}/api/tags`, {
		signal: AbortSignal.timeout(3000),
		});
		if (!response.ok)
		return [];
		const data = await response.json();
		return (data.models \|\| []).map(m => ({
		name: m.name,
		size: m.size,
		modifiedAt: m.modified_at,
		}));
		}
		catch {
		return [];
		}
		}
		//# sourceMappingURL=ollama.js.map

-1

server-dist/dist/llm/providers/ollama.js.map

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-3

server-dist/dist/llm/providers/openai.d.ts

		import type { LLMClient } from '../types.js';
		export declare function createOpenAIClient(apiKey: string, model: string): LLMClient;
		//# sourceMappingURL=openai.d.ts.map

-1

server-dist/dist/llm/providers/openai.d.ts.map

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-39

server-dist/dist/llm/providers/openai.js

		// OpenAI provider implementation (server-side, no browser dependencies)
		export function createOpenAIClient(apiKey, model) {
		return {
		provider: 'openai',
		model,
		async chat(messages, options) {
		const response = await fetch('https://api.openai.com/v1/chat/completions', {
		method: 'POST',
		headers: {
		'Content-Type': 'application/json',
		'Authorization': `Bearer ${apiKey}`,
		},
		signal: options?.signal,
		body: JSON.stringify({
		model,
		messages: messages.map(m => ({ role: m.role, content: m.content })),
		temperature: 0.7,
		}),
		});
		if (!response.ok) {
		const error = await response.json().catch(() => ({}));
		throw new Error(error.error?.message \|\| `OpenAI API error: ${response.status}`);
		}
		const data = await response.json();
		return {
		content: data.choices[0]?.message?.content \|\| '',
		usage: data.usage ? {
		inputTokens: data.usage.prompt_tokens,
		outputTokens: data.usage.completion_tokens,
		} : undefined,
		};
		},
		estimateTokens(text) {
		// Rough estimate: ~4 characters per token for English
		return Math.ceil(text.length / 4);
		},
		};
		}
		//# sourceMappingURL=openai.js.map

-1

server-dist/dist/llm/providers/openai.js.map

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-22

server-dist/dist/llm/types.d.ts

		export type { LLMProvider, LLMProviderConfig, ProviderInfo, ProviderModelOption } from '@code-insights/cli/types';
		export interface LLMMessage {
		role: 'system' \| 'user' \| 'assistant';
		content: string;
		}
		export interface LLMResponse {
		content: string;
		usage?: {
		inputTokens: number;
		outputTokens: number;
		};
		}
		export interface ChatOptions {
		signal?: AbortSignal;
		}
		export interface LLMClient {
		chat(messages: LLMMessage[], options?: ChatOptions): Promise<LLMResponse>;
		estimateTokens(text: string): number;
		readonly provider: string;
		readonly model: string;
		}
		//# sourceMappingURL=types.d.ts.map

-1

server-dist/dist/llm/types.d.ts.map

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-5

server-dist/dist/llm/types.js

		// LLM abstraction types for the server-side LLM engine.
		// Provider metadata (PROVIDERS constant) lives in cli/src/constants/llm-providers.ts.
		// LLMProvider, LLMProviderConfig, ProviderInfo are imported from CLI types (single source of truth).
		export {};
		//# sourceMappingURL=types.js.map

-1

server-dist/dist/llm/types.js.map

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-4

server-dist/dist/routes/analysis.d.ts

		import { Hono } from 'hono';
		declare const app: Hono<import("hono/types").BlankEnv, import("hono/types").BlankSchema, "/">;
		export default app;
		//# sourceMappingURL=analysis.d.ts.map

-1

server-dist/dist/routes/analysis.d.ts.map

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-103

server-dist/dist/routes/analysis.js

		import { Hono } from 'hono';
		import { getDb } from '@code-insights/cli/db/client';
		import { trackEvent } from '@code-insights/cli/utils/telemetry';
		import { parseIntParam } from '../utils.js';
		import { analyzeSession, analyzePromptQuality, findRecurringInsights } from '../llm/analysis.js';
		import { isLLMConfigured } from '../llm/client.js';
		const app = new Hono();
		// POST /api/analysis/session
		// Body: { sessionId: string }
		// Fetches session + messages from SQLite, runs LLM analysis, saves insights, returns results.
		app.post('/session', async (c) => {
		if (!isLLMConfigured()) {
		return c.json({
		success: false,
		error: 'LLM not configured. Run `code-insights config llm` to configure a provider.',
		}, 400);
		}
		const body = await c.req.json();
		if (!body.sessionId \|\| typeof body.sessionId !== 'string') {
		return c.json({ error: 'Missing required field: sessionId' }, 400);
		}
		const db = getDb();
		const session = db.prepare(`
		SELECT id, project_id, project_name, project_path, summary, ended_at
		FROM sessions WHERE id = ?
		`).get(body.sessionId);
		if (!session) {
		return c.json({ error: 'Session not found' }, 404);
		}
		const messages = db.prepare(`
		SELECT id, session_id, type, content, thinking, tool_calls, tool_results, usage, timestamp, parent_id
		FROM messages WHERE session_id = ? ORDER BY timestamp ASC
		`).all(body.sessionId);
		const result = await analyzeSession(session, messages);
		if (result.success)
		trackEvent('analysis', true, 'session');
		return c.json(result, result.success ? 200 : 422);
		});
		// POST /api/analysis/prompt-quality
		// Body: { sessionId: string }
		// Runs prompt quality analysis on user messages in the session.
		app.post('/prompt-quality', async (c) => {
		if (!isLLMConfigured()) {
		return c.json({
		success: false,
		error: 'LLM not configured. Run `code-insights config llm` to configure a provider.',
		}, 400);
		}
		const body = await c.req.json();
		if (!body.sessionId \|\| typeof body.sessionId !== 'string') {
		return c.json({ error: 'Missing required field: sessionId' }, 400);
		}
		const db = getDb();
		const session = db.prepare(`
		SELECT id, project_id, project_name, project_path, summary, ended_at
		FROM sessions WHERE id = ?
		`).get(body.sessionId);
		if (!session) {
		return c.json({ error: 'Session not found' }, 404);
		}
		const messages = db.prepare(`
		SELECT id, session_id, type, content, thinking, tool_calls, tool_results, usage, timestamp, parent_id
		FROM messages WHERE session_id = ? ORDER BY timestamp ASC
		`).all(body.sessionId);
		const result = await analyzePromptQuality(session, messages);
		if (result.success)
		trackEvent('analysis', true, 'prompt-quality');
		return c.json(result, result.success ? 200 : 422);
		});
		// POST /api/analysis/recurring
		// Body: { projectId?: string; limit?: number }
		// Finds recurring insight patterns across sessions.
		app.post('/recurring', async (c) => {
		if (!isLLMConfigured()) {
		return c.json({
		success: false,
		error: 'LLM not configured. Run `code-insights config llm` to configure a provider.',
		}, 400);
		}
		const body = await c.req.json();
		const db = getDb();
		const conditions = [];
		const params = [];
		if (body.projectId) {
		conditions.push('project_id = ?');
		params.push(body.projectId);
		}
		const where = conditions.length > 0 ? `WHERE ${conditions.join(' AND ')}` : '';
		const limit = Math.min(parseIntParam(String(body.limit ?? ''), 200), 200);
		const insights = db.prepare(`
		SELECT id, type, title, summary, project_name, session_id
		FROM insights
		${where}
		ORDER BY timestamp DESC
		LIMIT ?
		`).all(...params, limit);
		const result = await findRecurringInsights(insights);
		if (result.success)
		trackEvent('analysis', true, 'recurring');
		return c.json(result, result.success ? 200 : 422);
		});
		export default app;
		//# sourceMappingURL=analysis.js.map

-1

server-dist/dist/routes/analysis.js.map

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-4

server-dist/dist/routes/analytics.d.ts

		import { Hono } from 'hono';
		declare const app: Hono<import("hono/types").BlankEnv, import("hono/types").BlankSchema, "/">;
		export default app;
		//# sourceMappingURL=analytics.d.ts.map

-1

server-dist/dist/routes/analytics.d.ts.map

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-47

server-dist/dist/routes/analytics.js

		import { Hono } from 'hono';
		import { getDb } from '@code-insights/cli/db/client';
		const app = new Hono();
		const VALID_RANGES = ['7d', '30d', '90d', 'all'];
		// Dashboard overview stats for a given time range (e.g. ?range=7d\|30d\|90d\|all)
		app.get('/dashboard', (c) => {
		const db = getDb();
		const { range = '7d' } = c.req.query();
		if (!VALID_RANGES.includes(range)) {
		return c.json({ error: `Invalid range. Must be one of: ${VALID_RANGES.join(', ')}` }, 400);
		}
		let periodStart = null;
		const now = new Date();
		if (range === '7d') {
		periodStart = new Date(now.getTime() - 7 * 24 * 60 * 60 * 1000).toISOString();
		}
		else if (range === '30d') {
		periodStart = new Date(now.getTime() - 30 * 24 * 60 * 60 * 1000).toISOString();
		}
		else if (range === '90d') {
		periodStart = new Date(now.getTime() - 90 * 24 * 60 * 60 * 1000).toISOString();
		}
		const where = periodStart ? 'WHERE started_at >= ?' : '';
		const params = periodStart ? [periodStart] : [];
		const stats = db.prepare(`
		SELECT
		COUNT(*) AS session_count,
		SUM(message_count) AS total_messages,
		SUM(total_input_tokens) AS total_input_tokens,
		SUM(total_output_tokens) AS total_output_tokens,
		SUM(estimated_cost_usd) AS estimated_cost_usd
		FROM sessions ${where}
		`).get(...params);
		return c.json({ range, stats });
		});
		// Global cumulative usage stats
		app.get('/usage', (c) => {
		const db = getDb();
		const stats = db.prepare(`
		SELECT total_input_tokens, total_output_tokens, cache_creation_tokens,
		cache_read_tokens, estimated_cost_usd, sessions_with_usage, last_updated_at
		FROM usage_stats WHERE id = 1
		`).get();
		return c.json({ stats: stats ?? null });
		});
		export default app;
		//# sourceMappingURL=analytics.js.map

-1

server-dist/dist/routes/analytics.js.map

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-4

server-dist/dist/routes/config.d.ts

		import { Hono } from 'hono';
		declare const app: Hono<import("hono/types").BlankEnv, import("hono/types").BlankSchema, "/">;
		export default app;
		//# sourceMappingURL=config.d.ts.map

-1

server-dist/dist/routes/config.d.ts.map

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-108

server-dist/dist/routes/config.js

		import { Hono } from 'hono';
		import { loadConfig, saveConfig } from '@code-insights/cli/utils/config';
		import { loadLLMConfig, testLLMConfig } from '../llm/client.js';
		import { discoverOllamaModels } from '../llm/providers/ollama.js';
		const app = new Hono();
		const VALID_PROVIDERS = ['openai', 'anthropic', 'gemini', 'ollama'];
		function maskApiKey(key) {
		if (!key \|\| key.length < 8)
		return key ? '***' : undefined;
		return key.slice(0, 4) + '...' + key.slice(-4);
		}
		// GET /api/config/llm — return full config (API key masked)
		app.get('/llm', (c) => {
		const config = loadConfig();
		const llm = config?.dashboard?.llm;
		return c.json({
		dashboardPort: config?.dashboard?.port ?? 7890,
		provider: llm?.provider,
		model: llm?.model,
		apiKey: maskApiKey(llm?.apiKey),
		baseUrl: llm?.baseUrl,
		});
		});
		// PUT /api/config/llm — update dashboard port and/or LLM config
		app.put('/llm', async (c) => {
		const body = await c.req.json();
		const config = loadConfig() ?? {
		sync: { claudeDir: '', excludeProjects: [] },
		};
		let changed = false;
		// Update dashboard port if provided
		if (body.dashboardPort !== undefined) {
		const port = body.dashboardPort;
		if (typeof port !== 'number' \|\| !Number.isInteger(port) \|\| port < 1 \|\| port > 65535) {
		return c.json({ error: 'dashboardPort must be an integer between 1 and 65535' }, 400);
		}
		config.dashboard = { ...config.dashboard, port };
		changed = true;
		}
		// Update LLM config if any LLM field is provided
		const hasLLMField = body.provider !== undefined \|\| body.model !== undefined \|\|
		body.apiKey !== undefined \|\| body.baseUrl !== undefined;
		if (hasLLMField) {
		if (body.provider !== undefined && !VALID_PROVIDERS.includes(body.provider)) {
		return c.json({ error: `provider must be one of: ${VALID_PROVIDERS.join(', ')}` }, 400);
		}
		const existingLlm = config.dashboard?.llm ?? {};
		const updatedLlm = {
		provider: body.provider ?? existingLlm.provider ?? 'ollama',
		model: body.model ?? existingLlm.model ?? '',
		// Preserve existing API key if not provided in update
		...(body.apiKey !== undefined
		? { apiKey: body.apiKey \|\| undefined }
		: existingLlm.apiKey !== undefined ? { apiKey: existingLlm.apiKey } : {}),
		...(body.baseUrl !== undefined
		? { baseUrl: body.baseUrl \|\| undefined }
		: existingLlm.baseUrl !== undefined ? { baseUrl: existingLlm.baseUrl } : {}),
		};
		if (!updatedLlm.model) {
		return c.json({ error: 'model is required when setting LLM config' }, 400);
		}
		config.dashboard = { ...config.dashboard, llm: updatedLlm };
		changed = true;
		}
		if (!changed) {
		return c.json({ ok: true });
		}
		saveConfig(config);
		return c.json({ ok: true });
		});
		// POST /api/config/llm/test — validate LLM credentials with a test call
		app.post('/llm/test', async (c) => {
		// Allow testing with body config or existing saved config
		let testConfig = null;
		try {
		const body = await c.req.json();
		if (body.provider && body.model) {
		testConfig = {
		provider: body.provider,
		model: body.model,
		...(body.apiKey ? { apiKey: body.apiKey } : {}),
		...(body.baseUrl ? { baseUrl: body.baseUrl } : {}),
		};
		}
		}
		catch {
		// No body or invalid JSON — use existing config
		}
		if (!testConfig) {
		testConfig = loadLLMConfig();
		}
		if (!testConfig) {
		return c.json({
		success: false,
		error: 'No LLM config found. Run `code-insights config llm` or provide config in request body.',
		}, 400);
		}
		const result = await testLLMConfig(testConfig);
		return c.json(result, result.success ? 200 : 422);
		});
		// GET /api/config/llm/ollama-models — return locally available Ollama models
		app.get('/llm/ollama-models', async (c) => {
		const baseUrl = c.req.query('baseUrl');
		const models = await discoverOllamaModels(baseUrl);
		return c.json({ models });
		});
		export default app;
		//# sourceMappingURL=config.js.map

-1

server-dist/dist/routes/config.js.map

-4

server-dist/dist/routes/export.d.ts

		import { Hono } from 'hono';
		declare const app: Hono<import("hono/types").BlankEnv, import("hono/types").BlankSchema, "/">;
		export default app;
		//# sourceMappingURL=export.d.ts.map

-1

server-dist/dist/routes/export.d.ts.map

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-52

server-dist/dist/routes/export.js

		import { Hono } from 'hono';
		import { getDb } from '@code-insights/cli/db/client';
		import { trackEvent } from '@code-insights/cli/utils/telemetry';
		const app = new Hono();
		// POST /api/export/markdown — export sessions/insights as markdown
		app.post('/markdown', async (c) => {
		const db = getDb();
		const body = await c.req.json();
		const { sessionIds, projectId } = body;
		if (sessionIds !== undefined && !Array.isArray(sessionIds)) {
		return c.json({ error: 'sessionIds must be an array' }, 400);
		}
		if (sessionIds && sessionIds.some((id) => typeof id !== 'string')) {
		return c.json({ error: 'sessionIds must contain only strings' }, 400);
		}
		if (sessionIds && sessionIds.length > 100) {
		return c.json({ error: 'Maximum 100 session IDs per export request' }, 400);
		}
		let sessions;
		if (sessionIds && sessionIds.length > 0) {
		const placeholders = sessionIds.map(() => '?').join(', ');
		sessions = db.prepare(`SELECT id, project_name, generated_title, custom_title, started_at, ended_at,
		message_count, estimated_cost_usd, session_character, source_tool
		FROM sessions WHERE id IN (${placeholders}) ORDER BY started_at DESC`).all(...sessionIds);
		}
		else if (projectId) {
		sessions = db.prepare(`SELECT id, project_name, generated_title, custom_title, started_at, ended_at,
		message_count, estimated_cost_usd, session_character, source_tool
		FROM sessions WHERE project_id = ? ORDER BY started_at DESC`).all(projectId);
		}
		else {
		return c.json({ error: 'sessionIds or projectId required' }, 400);
		}
		const lines = ['# Code Insights Export', ''];
		for (const s of sessions) {
		const title = (s.custom_title ?? s.generated_title ?? s.id);
		lines.push(`## ${title}`);
		lines.push(`- Started: ${s.started_at}`);
		lines.push(`- Ended: ${s.ended_at}`);
		lines.push(`- Messages: ${s.message_count}`);
		if (s.estimated_cost_usd != null) {
		lines.push(`- Cost: $${Number(s.estimated_cost_usd).toFixed(4)}`);
		}
		lines.push('');
		}
		const markdown = lines.join('\n');
		trackEvent('export', true, 'markdown');
		c.header('Content-Type', 'text/markdown');
		return c.body(markdown);
		});
		export default app;
		//# sourceMappingURL=export.js.map

-1

server-dist/dist/routes/export.js.map

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-4

server-dist/dist/routes/insights.d.ts

		import { Hono } from 'hono';
		declare const app: Hono<import("hono/types").BlankEnv, import("hono/types").BlankSchema, "/">;
		export default app;
		//# sourceMappingURL=insights.d.ts.map

-1

server-dist/dist/routes/insights.d.ts.map

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-80

server-dist/dist/routes/insights.js

		import { Hono } from 'hono';
		import { getDb } from '@code-insights/cli/db/client';
		import { randomUUID } from 'crypto';
		import { parseIntParam } from '../utils.js';
		const app = new Hono();
		const VALID_TYPES = ['summary', 'decision', 'learning', 'technique', 'prompt_quality'];
		app.get('/', (c) => {
		const db = getDb();
		const { projectId, sessionId, type, limit, offset } = c.req.query();
		const conditions = [];
		const params = [];
		if (projectId) {
		conditions.push('project_id = ?');
		params.push(projectId);
		}
		if (sessionId) {
		conditions.push('session_id = ?');
		params.push(sessionId);
		}
		if (type) {
		conditions.push('type = ?');
		params.push(type);
		}
		const where = conditions.length > 0 ? `WHERE ${conditions.join(' AND ')}` : '';
		const insights = db.prepare(`
		SELECT id, session_id, project_id, project_name, type, title, content,
		summary, bullets, confidence, source, metadata, timestamp,
		created_at, scope, analysis_version, linked_insight_ids
		FROM insights
		${where}
		ORDER BY timestamp DESC
		LIMIT ? OFFSET ?
		`).all(...params, parseIntParam(limit, 100), parseIntParam(offset, 0));
		return c.json({ insights });
		});
		app.post('/', async (c) => {
		const db = getDb();
		const body = await c.req.json();
		// Validate required string fields
		const required = ['sessionId', 'projectId', 'type', 'title', 'content'];
		for (const field of required) {
		if (!body[field] \|\| typeof body[field] !== 'string') {
		return c.json({ error: `Missing or invalid field: ${field}` }, 400);
		}
		}
		// Validate type is one of the known insight types
		if (!VALID_TYPES.includes(body.type)) {
		return c.json({ error: `type must be one of: ${VALID_TYPES.join(', ')}` }, 400);
		}
		// Validate confidence is a finite number if provided
		if (body.confidence !== undefined && (typeof body.confidence !== 'number' \|\| !Number.isFinite(body.confidence))) {
		return c.json({ error: 'confidence must be a finite number' }, 400);
		}
		const id = randomUUID();
		const now = new Date().toISOString();
		try {
		db.prepare(`
		INSERT INTO insights (
		id, session_id, project_id, project_name, type, title, content,
		summary, bullets, confidence, source, metadata, timestamp, created_at
		) VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, 'llm', ?, ?, ?)
		`).run(id, body.sessionId, body.projectId, body.projectName ?? '', body.type, body.title, body.content, body.summary ?? '', body.bullets ? JSON.stringify(body.bullets) : null, body.confidence ?? 0, body.metadata ? JSON.stringify(body.metadata) : null, now, now);
		}
		catch (err) {
		if (err instanceof Error && err.message.includes('FOREIGN KEY constraint failed')) {
		return c.json({ error: 'Invalid sessionId or projectId' }, 400);
		}
		throw err;
		}
		return c.json({ id }, 201);
		});
		app.delete('/:id', (c) => {
		const db = getDb();
		const result = db.prepare('DELETE FROM insights WHERE id = ?').run(c.req.param('id'));
		if (result.changes === 0)
		return c.json({ error: 'Not found' }, 404);
		return c.json({ ok: true });
		});
		export default app;
		//# sourceMappingURL=insights.js.map

-1

server-dist/dist/routes/insights.js.map

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-4

server-dist/dist/routes/messages.d.ts

		import { Hono } from 'hono';
		declare const app: Hono<import("hono/types").BlankEnv, import("hono/types").BlankSchema, "/">;
		export default app;
		//# sourceMappingURL=messages.d.ts.map

-1

server-dist/dist/routes/messages.d.ts.map

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-19

server-dist/dist/routes/messages.js

		import { Hono } from 'hono';
		import { getDb } from '@code-insights/cli/db/client';
		import { parseIntParam } from '../utils.js';
		const app = new Hono();
		app.get('/:sessionId', (c) => {
		const db = getDb();
		const { limit, offset } = c.req.query();
		const messages = db.prepare(`
		SELECT id, session_id, type, content, thinking,
		tool_calls, tool_results, usage, timestamp, parent_id
		FROM messages
		WHERE session_id = ?
		ORDER BY timestamp ASC
		LIMIT ? OFFSET ?
		`).all(c.req.param('sessionId'), parseIntParam(limit, 100), parseIntParam(offset, 0));
		return c.json({ messages });
		});
		export default app;
		//# sourceMappingURL=messages.js.map

-1

server-dist/dist/routes/messages.js.map

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-4

server-dist/dist/routes/projects.d.ts

		import { Hono } from 'hono';
		declare const app: Hono<import("hono/types").BlankEnv, import("hono/types").BlankSchema, "/">;
		export default app;
		//# sourceMappingURL=projects.d.ts.map

-1

server-dist/dist/routes/projects.d.ts.map

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-32

server-dist/dist/routes/projects.js

		import { Hono } from 'hono';
		import { getDb } from '@code-insights/cli/db/client';
		import { parseIntParam } from '../utils.js';
		const app = new Hono();
		app.get('/', (c) => {
		const db = getDb();
		const { limit, offset } = c.req.query();
		const projects = db.prepare(`
		SELECT id, name, path, git_remote_url, session_count, last_activity,
		total_input_tokens, total_output_tokens, cache_creation_tokens,
		cache_read_tokens, estimated_cost_usd, created_at, updated_at
		FROM projects
		ORDER BY last_activity DESC
		LIMIT ? OFFSET ?
		`).all(parseIntParam(limit, 100), parseIntParam(offset, 0));
		return c.json({ projects });
		});
		app.get('/:id', (c) => {
		const db = getDb();
		const project = db.prepare(`
		SELECT id, name, path, git_remote_url, session_count, last_activity,
		total_input_tokens, total_output_tokens, cache_creation_tokens,
		cache_read_tokens, estimated_cost_usd, created_at, updated_at
		FROM projects
		WHERE id = ?
		`).get(c.req.param('id'));
		if (!project)
		return c.json({ error: 'Not found' }, 404);
		return c.json({ project });
		});
		export default app;
		//# sourceMappingURL=projects.js.map

-1

server-dist/dist/routes/projects.js.map

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-4

server-dist/dist/routes/sessions.d.ts

		import { Hono } from 'hono';
		declare const app: Hono<import("hono/types").BlankEnv, import("hono/types").BlankSchema, "/">;
		export default app;
		//# sourceMappingURL=sessions.d.ts.map

-1

server-dist/dist/routes/sessions.d.ts.map

{"version":3,"file":"sessions.d.ts","sourceRoot":"","sources":["../../src/routes/sessions.ts"],"names":[],"mappings":"AAAA,OAAO,EAAE,IAAI,EAAE,MAAM,MAAM,CAAC;AAI5B,QAAA,MAAM,GAAG,4EAAa,CAAC;AAqEvB,eAAe,GAAG,CAAC"}

-65

server-dist/dist/routes/sessions.js

		import { Hono } from 'hono';
		import { getDb } from '@code-insights/cli/db/client';
		import { parseIntParam } from '../utils.js';
		const app = new Hono();
		app.get('/', (c) => {
		const db = getDb();
		const { projectId, sourceTool, limit, offset } = c.req.query();
		const conditions = [];
		const params = [];
		if (projectId) {
		conditions.push('project_id = ?');
		params.push(projectId);
		}
		if (sourceTool) {
		conditions.push('source_tool = ?');
		params.push(sourceTool);
		}
		const where = conditions.length > 0 ? `WHERE ${conditions.join(' AND ')}` : '';
		const sessions = db.prepare(`
		SELECT id, project_id, project_name, project_path, git_remote_url,
		summary, custom_title, generated_title, title_source, session_character,
		started_at, ended_at, message_count, user_message_count,
		assistant_message_count, tool_call_count, git_branch,
		claude_version, source_tool, device_id, device_hostname,
		device_platform, synced_at, total_input_tokens, total_output_tokens,
		cache_creation_tokens, cache_read_tokens, estimated_cost_usd,
		models_used, primary_model, usage_source
		FROM sessions
		${where}
		ORDER BY started_at DESC
		LIMIT ? OFFSET ?
		`).all(...params, parseIntParam(limit, 50), parseIntParam(offset, 0));
		return c.json({ sessions });
		});
		app.get('/:id', (c) => {
		const db = getDb();
		const session = db.prepare(`
		SELECT id, project_id, project_name, project_path, git_remote_url,
		summary, custom_title, generated_title, title_source, session_character,
		started_at, ended_at, message_count, user_message_count,
		assistant_message_count, tool_call_count, git_branch,
		claude_version, source_tool, device_id, device_hostname,
		device_platform, synced_at, total_input_tokens, total_output_tokens,
		cache_creation_tokens, cache_read_tokens, estimated_cost_usd,
		models_used, primary_model, usage_source
		FROM sessions WHERE id = ?
		`).get(c.req.param('id'));
		if (!session)
		return c.json({ error: 'Not found' }, 404);
		return c.json({ session });
		});
		app.patch('/:id', async (c) => {
		const db = getDb();
		const body = await c.req.json();
		const { customTitle } = body;
		if (customTitle === undefined) {
		return c.json({ error: 'customTitle is required' }, 400);
		}
		const result = db.prepare('UPDATE sessions SET custom_title = ? WHERE id = ?').run(customTitle \|\| null, c.req.param('id'));
		if (result.changes === 0)
		return c.json({ error: 'Not found' }, 404);
		return c.json({ ok: true });
		});
		export default app;
		//# sourceMappingURL=sessions.js.map

-1

server-dist/dist/routes/sessions.js.map

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-6

server-dist/dist/utils.d.ts

		/**
		* Parse an integer query parameter with a safe default.
		* Returns the default if the value is missing, NaN, negative, or non-finite.
		*/
		export declare function parseIntParam(value: string \| undefined, defaultVal: number): number;
		//# sourceMappingURL=utils.d.ts.map

-1

server-dist/dist/utils.d.ts.map

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-9

server-dist/dist/utils.js

		/**
		* Parse an integer query parameter with a safe default.
		* Returns the default if the value is missing, NaN, negative, or non-finite.
		*/
		export function parseIntParam(value, defaultVal) {
		const n = value !== undefined ? parseInt(value, 10) : defaultVal;
		return Number.isFinite(n) && n >= 0 ? n : defaultVal;
		}
		//# sourceMappingURL=utils.js.map

-1

server-dist/dist/utils.js.map

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