ai-memory-cli - npm Package Compare versions

Comparing version 1.1.0 to 1.1.2

dist/public.js

@@ -264,3 +264,4 @@ // src/sources/cursor.ts
       }
-      const { DatabaseSync } = await import("sqlite");
+      const sqliteMod = "node:sqlite";
+      const { DatabaseSync } = await import(sqliteMod);
       const db = new DatabaseSync(tmpDb, { readonly: true });
@@ -278,3 +279,5 @@ const row = db.prepare("SELECT value FROM ItemTable WHERE key = ?").get("composer.composerHeaders");
       return map;
-    } catch {
+    } catch (err) {
+      process.stderr.write(`[ai-memory] title map load failed: ${err}
+`);
       return /* @__PURE__ */ new Map();
@@ -281,0 +284,0 @@ }

dist/public.js.map

@@ -1,1 +0,1 @@
-{"version":3,"sources":["../src/sources/cursor.ts","../src/sources/claude-code.ts","../src/sources/detector.ts"],"sourcesContent":["import { readdir, readFile, stat, copyFile, mkdir } from \"node:fs/promises\";\nimport { join, basename } from \"node:path\";\nimport { homedir, tmpdir } from \"node:os\";\nimport type {\n  Source,\n  ConversationMeta,\n  Conversation,\n  ConversationTurn,\n} from \"../types.js\";\n\nconst UUID_RE = /^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$/i;\n\nexport class CursorSource implements Source {\n  readonly type = \"cursor\" as const;\n  private basePath: string;\n  private projectName: string | undefined;\n\n  constructor(projectName?: string) {\n    this.projectName = projectName;\n    this.basePath = join(homedir(), \".cursor\", \"projects\");\n  }\n\n  async detect(): Promise<boolean> {\n    try {\n      const projectDir = await this.resolveProjectDir();\n      if (!projectDir) return false;\n      const transcriptsDir = join(projectDir, \"agent-transcripts\");\n      const s = await stat(transcriptsDir);\n      return s.isDirectory();\n    } catch {\n      return false;\n    }\n  }\n\n  async listConversations(): Promise<ConversationMeta[]> {\n    const transcriptsDir = await this.getTranscriptsDir();\n    if (!transcriptsDir) return [];\n\n    // Load real titles from Cursor's workspace DB (best-effort)\n    const titleMap = await this.loadTitleMap();\n\n    const entries = await readdir(transcriptsDir, { withFileTypes: true });\n    const conversations: ConversationMeta[] = [];\n\n    for (const entry of entries) {\n      if (entry.isDirectory() && UUID_RE.test(entry.name)) {\n        const meta = await this.readConversationMeta(\n          transcriptsDir,\n          entry.name,\n          titleMap\n        );\n        if (meta) conversations.push(meta);\n      } else if (entry.isFile() && entry.name.endsWith(\".txt\")) {\n        const meta = await this.readLegacyMeta(transcriptsDir, entry.name);\n        if (meta) conversations.push(meta);\n      }\n    }\n\n    return conversations.sort((a, b) => b.modifiedAt - a.modifiedAt);\n  }\n\n  async loadConversation(meta: ConversationMeta): Promise<Conversation> {\n    if (meta.filePath.endsWith(\".txt\")) {\n      return this.loadLegacyConversation(meta);\n    }\n    return this.loadJsonlConversation(meta);\n  }\n\n  // --- JSONL format (current) ---\n\n  private async loadJsonlConversation(\n    meta: ConversationMeta\n  ): Promise<Conversation> {\n    const raw = await readFile(meta.filePath, \"utf-8\");\n    const turns = this.parseJsonlContent(raw);\n    return { meta: { ...meta, turnCount: turns.length }, turns };\n  }\n\n  parseJsonlContent(raw: string): ConversationTurn[] {\n    const turns: ConversationTurn[] = [];\n\n    for (const line of raw.split(\"\\n\")) {\n      const trimmed = line.trim();\n      if (!trimmed) continue;\n\n      try {\n        const obj = JSON.parse(trimmed);\n        const role = obj.role as \"user\" | \"assistant\";\n        if (role !== \"user\" && role !== \"assistant\") continue;\n\n        const textParts = this.extractTextParts(obj.message?.content);\n        if (!textParts) continue;\n\n        turns.push({ role, text: textParts });\n      } catch {\n        // Skip malformed lines\n      }\n    }\n\n    return turns;\n  }\n\n  private extractTextParts(content: unknown): string | null {\n    if (!Array.isArray(content)) return null;\n\n    const texts: string[] = [];\n    for (const part of content) {\n      if (\n        part &&\n        typeof part === \"object\" &&\n        \"type\" in part &&\n        part.type === \"text\" &&\n        \"text\" in part &&\n        typeof part.text === \"string\"\n      ) {\n        texts.push(this.cleanUserQuery(part.text));\n      }\n    }\n\n    const joined = texts.join(\"\\n\").trim();\n    return joined || null;\n  }\n\n  private cleanUserQuery(text: string): string {\n    const match = text.match(/<user_query>\\s*([\\s\\S]*?)\\s*<\\/user_query>/);\n    if (match) return match[1].trim();\n    return text;\n  }\n\n  // --- Legacy .txt format ---\n\n  private async loadLegacyConversation(\n    meta: ConversationMeta\n  ): Promise<Conversation> {\n    const raw = await readFile(meta.filePath, \"utf-8\");\n    const turns = this.parseLegacyContent(raw);\n    return { meta: { ...meta, turnCount: turns.length }, turns };\n  }\n\n  parseLegacyContent(raw: string): ConversationTurn[] {\n    const turns: ConversationTurn[] = [];\n    const blocks = raw.split(/^(user|assistant):\\s*$/m);\n\n    let currentRole: \"user\" | \"assistant\" | null = null;\n    for (const block of blocks) {\n      const trimmed = block.trim();\n      if (trimmed === \"user\") {\n        currentRole = \"user\";\n      } else if (trimmed === \"assistant\") {\n        currentRole = \"assistant\";\n      } else if (currentRole && trimmed) {\n        turns.push({\n          role: currentRole,\n          text: this.cleanUserQuery(trimmed),\n        });\n        currentRole = null;\n      }\n    }\n\n    return turns;\n  }\n\n  // --- Metadata helpers ---\n\n  private async readConversationMeta(\n    transcriptsDir: string,\n    uuid: string,\n    titleMap: Map<string, string> = new Map()\n  ): Promise<ConversationMeta | null> {\n    const jsonlPath = join(transcriptsDir, uuid, `${uuid}.jsonl`);\n    try {\n      const fileStat = await stat(jsonlPath);\n      const raw = await readFile(jsonlPath, \"utf-8\");\n      // Prefer real title from DB; fall back to first user message\n      const title = titleMap.get(uuid) ?? this.extractTitle(raw, uuid);\n      const turnCount = this.countTurns(raw);\n\n      return {\n        id: uuid,\n        source: \"cursor\",\n        filePath: jsonlPath,\n        title,\n        modifiedAt: fileStat.mtimeMs,\n        turnCount,\n      };\n    } catch {\n      return null;\n    }\n  }\n\n  private async readLegacyMeta(\n    transcriptsDir: string,\n    filename: string\n  ): Promise<ConversationMeta | null> {\n    const filePath = join(transcriptsDir, filename);\n    try {\n      const fileStat = await stat(filePath);\n      const id = basename(filename, \".txt\");\n      const raw = await readFile(filePath, \"utf-8\");\n      const title = this.extractLegacyTitle(raw, id);\n\n      return {\n        id,\n        source: \"cursor\",\n        filePath,\n        title,\n        modifiedAt: fileStat.mtimeMs,\n        turnCount: (raw.match(/^(user|assistant):\\s*$/m) || []).length,\n      };\n    } catch {\n      return null;\n    }\n  }\n\n  private extractTitle(jsonlRaw: string, fallbackId: string): string {\n    for (const line of jsonlRaw.split(\"\\n\").slice(0, 5)) {\n      try {\n        const obj = JSON.parse(line.trim());\n        if (obj.role === \"user\") {\n          const text = this.extractTextParts(obj.message?.content);\n          if (text) {\n            const cleaned = text.replace(/\\s+/g, \" \").trim();\n            return cleaned.length > 60\n              ? cleaned.slice(0, 57) + \"...\"\n              : cleaned;\n          }\n        }\n      } catch {\n        // skip\n      }\n    }\n    return fallbackId.slice(0, 8);\n  }\n\n  private extractLegacyTitle(raw: string, fallbackId: string): string {\n    const match = raw.match(\n      /<user_query>\\s*([\\s\\S]*?)\\s*<\\/user_query>/\n    );\n    if (match) {\n      const text = match[1].replace(/\\s+/g, \" \").trim();\n      return text.length > 60 ? text.slice(0, 57) + \"...\" : text;\n    }\n    return fallbackId.slice(0, 8);\n  }\n\n  private countTurns(jsonlRaw: string): number {\n    let count = 0;\n    for (const line of jsonlRaw.split(\"\\n\")) {\n      if (line.includes('\"role\"')) count++;\n    }\n    return count;\n  }\n\n  // --- Project directory resolution ---\n\n  private async resolveProjectDir(): Promise<string | null> {\n    if (this.projectName) {\n      const dir = join(this.basePath, this.projectName);\n      try {\n        const s = await stat(dir);\n        if (s.isDirectory()) return dir;\n      } catch {\n        // fall through\n      }\n    }\n\n    try {\n      const projects = await readdir(this.basePath, { withFileTypes: true });\n\n      // Collect candidates with transcript dirs\n      type Candidate = { dir: string; count: number; mtime: number };\n      const candidates: Candidate[] = [];\n\n      for (const p of projects) {\n        if (!p.isDirectory()) continue;\n        // Skip temp/AppData/numeric-only project directories\n        if (this.isTempProject(p.name)) continue;\n\n        const transcriptsDir = join(this.basePath, p.name, \"agent-transcripts\");\n        try {\n          const s = await stat(transcriptsDir);\n          if (!s.isDirectory()) continue;\n\n          const entries = await readdir(transcriptsDir);\n          const count = entries.length;\n          if (count === 0) continue;\n\n          candidates.push({\n            dir: join(this.basePath, p.name),\n            count,\n            mtime: s.mtimeMs,\n          });\n        } catch {\n          // no transcripts\n        }\n      }\n\n      if (candidates.length === 0) return null;\n\n      // Prefer the project matching the current working directory\n      const cwd = process.cwd().replace(/\\\\/g, \"-\").replace(/:/g, \"\").toLowerCase();\n      const cwdMatch = candidates.find((c) =>\n        cwd.endsWith(basename(c.dir).toLowerCase())\n      );\n      if (cwdMatch) return cwdMatch.dir;\n\n      // Otherwise pick the project with the most conversations\n      candidates.sort((a, b) => b.count - a.count || b.mtime - a.mtime);\n      return candidates[0].dir;\n    } catch {\n      // .cursor/projects doesn't exist\n    }\n\n    return null;\n  }\n\n  private isTempProject(name: string): boolean {\n    // Skip numeric-only names (e.g. \"1775614169037\")\n    if (/^\\d+$/.test(name)) return true;\n    // Skip AppData/Temp paths encoded as project names\n    if (name.toLowerCase().includes(\"appdata\")) return true;\n    if (name.toLowerCase().includes(\"temp\")) return true;\n    if (name.toLowerCase().includes(\"local-temp\")) return true;\n    return false;\n  }\n\n  private async getTranscriptsDir(): Promise<string | null> {\n    const projectDir = await this.resolveProjectDir();\n    if (!projectDir) return null;\n    return join(projectDir, \"agent-transcripts\");\n  }\n\n  // --- Title map from Cursor's workspace SQLite DB ---\n\n  /**\n   * Returns a map of { [composerId/UUID]: title } by reading\n   * Cursor's GLOBAL state.vscdb (key \"composer.composerHeaders\").\n   * This file contains titles for ALL workspaces.\n   * Uses node:sqlite (Node.js 22+). Silently returns empty map on any error.\n   */\n  private async loadTitleMap(): Promise<Map<string, string>> {\n    try {\n      const dbPath = this.getGlobalDbPath();\n      if (!dbPath) return new Map();\n\n      // Copy db + WAL + SHM to temp to avoid lock conflicts when Cursor is running\n      const ts = Date.now();\n      const tmpDb = join(tmpdir(), `ai-memory-global-${ts}.vscdb`);\n      await copyFile(dbPath, tmpDb);\n      for (const ext of [\"-wal\", \"-shm\"]) {\n        try { await copyFile(dbPath + ext, tmpDb + ext); } catch { /* optional */ }\n      }\n\n      const { DatabaseSync } = await import(\"node:sqlite\" as string);\n      const db = new (DatabaseSync as new (p: string, opts?: Record<string, unknown>) => {\n        prepare(sql: string): { get(...args: unknown[]): unknown };\n        close(): void;\n      })(tmpDb, { readonly: true });\n\n      const row = db\n        .prepare(\"SELECT value FROM ItemTable WHERE key = ?\")\n        .get(\"composer.composerHeaders\") as { value?: string } | undefined;\n      db.close();\n\n      if (!row?.value) return new Map();\n\n      const data = JSON.parse(row.value) as {\n        allComposers?: Array<{ composerId?: string; name?: string }>;\n      };\n\n      const map = new Map<string, string>();\n      for (const c of data.allComposers ?? []) {\n        if (c.composerId && c.name && c.name.trim()) {\n          map.set(c.composerId, c.name.trim());\n        }\n      }\n      return map;\n    } catch {\n      return new Map();\n    }\n  }\n\n  private getGlobalDbPath(): string | null {\n    if (process.platform === \"win32\") {\n      const appData = process.env.APPDATA;\n      return appData\n        ? join(appData, \"Cursor\", \"User\", \"globalStorage\", \"state.vscdb\")\n        : null;\n    }\n    if (process.platform === \"darwin\") {\n      return join(\n        homedir(),\n        \"Library\",\n        \"Application Support\",\n        \"Cursor\",\n        \"User\",\n        \"globalStorage\",\n        \"state.vscdb\"\n      );\n    }\n    return join(\n      homedir(),\n      \".config\",\n      \"Cursor\",\n      \"User\",\n      \"globalStorage\",\n      \"state.vscdb\"\n    );\n  }\n}\n","import { readdir, readFile, stat } from \"node:fs/promises\";\nimport { join } from \"node:path\";\nimport { homedir } from \"node:os\";\nimport type {\n  Source,\n  ConversationMeta,\n  Conversation,\n  ConversationTurn,\n} from \"../types.js\";\n\nconst UUID_RE = /^[0-9a-f]{8}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{4}-[0-9a-f]{12}$/i;\n\n/**\n * Claude Code stores sessions at:\n *   ~/.claude/projects/{path-with-dashes}/{uuid}.jsonl\n *\n * Each line is a JSONL event with role \"user\" | \"assistant\".\n * Assistant messages may contain tool_use / tool_result blocks — we extract\n * only text blocks for knowledge extraction.\n */\nexport class ClaudeCodeSource implements Source {\n  readonly type = \"claude-code\" as const;\n  private basePath: string;\n\n  constructor() {\n    this.basePath = join(homedir(), \".claude\", \"projects\");\n  }\n\n  async detect(): Promise<boolean> {\n    try {\n      const s = await stat(this.basePath);\n      return s.isDirectory();\n    } catch {\n      return false;\n    }\n  }\n\n  async listConversations(): Promise<ConversationMeta[]> {\n    const conversations: ConversationMeta[] = [];\n\n    let projectDirs: string[];\n    try {\n      const entries = await readdir(this.basePath, { withFileTypes: true });\n      // Claude Code encodes the project path as a dir name with path separators\n      // replaced by \"-\" (e.g. /home/user/myproject → -home-user-myproject).\n      // Filter to only dirs that match the current working directory.\n      const cwdEncoded = process.cwd().replace(/[/\\\\:]/g, \"-\").toLowerCase();\n      const cwdBasename = process.cwd().split(/[/\\\\]/).pop()?.toLowerCase() ?? \"\";\n\n      projectDirs = entries\n        .filter((e) => {\n          if (!e.isDirectory()) return false;\n          const name = e.name.toLowerCase();\n          // Match if dir name ends with or contains the cwd path encoding\n          return name.endsWith(cwdEncoded) || name.includes(`-${cwdBasename}`);\n        })\n        .map((e) => join(this.basePath, e.name));\n\n      // If no cwd-specific dirs found, fall back to all dirs (avoids empty results)\n      if (projectDirs.length === 0) {\n        projectDirs = entries\n          .filter((e) => e.isDirectory())\n          .map((e) => join(this.basePath, e.name));\n      }\n    } catch {\n      return [];\n    }\n\n    for (const projectDir of projectDirs) {\n      const files = await readdir(projectDir).catch(() => []);\n      for (const file of files) {\n        if (!file.endsWith(\".jsonl\")) continue;\n        const id = file.replace(\".jsonl\", \"\");\n        if (!UUID_RE.test(id)) continue;\n\n        const filePath = join(projectDir, file);\n        const meta = await this.readMeta(filePath, id);\n        if (meta) conversations.push(meta);\n      }\n    }\n\n    return conversations.sort((a, b) => b.modifiedAt - a.modifiedAt);\n  }\n\n  async loadConversation(meta: ConversationMeta): Promise<Conversation> {\n    const raw = await readFile(meta.filePath, \"utf-8\");\n    const turns = this.parseJsonlContent(raw);\n    return { meta: { ...meta, turnCount: turns.length }, turns };\n  }\n\n  parseJsonlContent(raw: string): ConversationTurn[] {\n    const turns: ConversationTurn[] = [];\n\n    for (const line of raw.split(\"\\n\")) {\n      const trimmed = line.trim();\n      if (!trimmed) continue;\n\n      try {\n        const obj = JSON.parse(trimmed);\n        const role = obj.role as \"user\" | \"assistant\";\n        if (role !== \"user\" && role !== \"assistant\") continue;\n\n        const text = this.extractText(obj);\n        if (!text) continue;\n\n        turns.push({ role, text });\n      } catch {\n        // Skip malformed lines\n      }\n    }\n\n    return turns;\n  }\n\n  private extractText(obj: Record<string, unknown>): string | null {\n    // Claude Code format: message may be in obj.message or obj directly\n    const content =\n      (obj.message as Record<string, unknown>)?.content ?? obj.content;\n\n    if (typeof content === \"string\") {\n      return content.trim() || null;\n    }\n\n    if (Array.isArray(content)) {\n      const texts: string[] = [];\n      for (const part of content) {\n        if (\n          part &&\n          typeof part === \"object\" &&\n          \"type\" in part &&\n          part.type === \"text\" &&\n          \"text\" in part &&\n          typeof part.text === \"string\" &&\n          part.text.trim()\n        ) {\n          texts.push((part.text as string).trim());\n        }\n      }\n      const joined = texts.join(\"\\n\").trim();\n      return joined || null;\n    }\n\n    return null;\n  }\n\n  private async readMeta(\n    filePath: string,\n    id: string\n  ): Promise<ConversationMeta | null> {\n    try {\n      const fileStat = await stat(filePath);\n      const raw = await readFile(filePath, \"utf-8\");\n      const turns = this.parseJsonlContent(raw);\n      const title = this.extractTitle(raw, id);\n\n      return {\n        id,\n        source: \"claude-code\",\n        filePath,\n        title,\n        modifiedAt: fileStat.mtimeMs,\n        turnCount: turns.length,\n      };\n    } catch {\n      return null;\n    }\n  }\n\n  private extractTitle(raw: string, fallbackId: string): string {\n    for (const line of raw.split(\"\\n\").slice(0, 5)) {\n      try {\n        const obj = JSON.parse(line.trim());\n        if (obj.role === \"user\") {\n          const text = this.extractText(obj);\n          if (text) {\n            const cleaned = text.replace(/\\s+/g, \" \").trim();\n            return cleaned.length > 60\n              ? cleaned.slice(0, 57) + \"...\"\n              : cleaned;\n          }\n        }\n      } catch {\n        // skip\n      }\n    }\n    return fallbackId.slice(0, 8);\n  }\n}\n","import type { Source, SourceType } from \"../types.js\";\nimport { CursorSource } from \"./cursor.js\";\nimport { ClaudeCodeSource } from \"./claude-code.js\";\n\ninterface DetectionResult {\n  available: Source[];\n  unavailable: SourceType[];\n}\n\nexport async function detectSources(\n  projectName?: string\n): Promise<DetectionResult> {\n  const candidates: Source[] = [\n    new CursorSource(projectName),\n    new ClaudeCodeSource(),\n  ];\n\n  const available: Source[] = [];\n  const unavailable: SourceType[] = [];\n\n  for (const source of candidates) {\n    const ok = await source.detect();\n    if (ok) {\n      available.push(source);\n    } else {\n      unavailable.push(source.type);\n    }\n  }\n\n  return { available, unavailable };\n}\n\nexport function createSource(\n  type: SourceType,\n  projectName?: string\n): Source {\n  switch (type) {\n    case \"cursor\":\n      return new CursorSource(projectName);\n    case \"claude-code\":\n      return new ClaudeCodeSource();\n    default:\n      throw new Error(`Source type \"${type}\" is not yet supported`);\n  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join(projectDir, \"agent-transcripts\");\n      const s = await stat(transcriptsDir);\n      return s.isDirectory();\n    } catch {\n      return false;\n    }\n  }\n\n  async listConversations(): Promise<ConversationMeta[]> {\n    const transcriptsDir = await this.getTranscriptsDir();\n    if (!transcriptsDir) return [];\n\n    // Load real titles from Cursor's workspace DB (best-effort)\n    const titleMap = await this.loadTitleMap();\n\n    const entries = await readdir(transcriptsDir, { withFileTypes: true });\n    const conversations: ConversationMeta[] = [];\n\n    for (const entry of entries) {\n      if (entry.isDirectory() && UUID_RE.test(entry.name)) {\n        const meta = await this.readConversationMeta(\n          transcriptsDir,\n          entry.name,\n          titleMap\n        );\n        if (meta) conversations.push(meta);\n      } else if (entry.isFile() && entry.name.endsWith(\".txt\")) {\n        const meta = await this.readLegacyMeta(transcriptsDir, entry.name);\n        if (meta) conversations.push(meta);\n      }\n    }\n\n    return conversations.sort((a, b) => b.modifiedAt - a.modifiedAt);\n  }\n\n  async loadConversation(meta: ConversationMeta): Promise<Conversation> {\n    if (meta.filePath.endsWith(\".txt\")) {\n      return this.loadLegacyConversation(meta);\n    }\n    return this.loadJsonlConversation(meta);\n  }\n\n  // --- JSONL format (current) ---\n\n  private async loadJsonlConversation(\n    meta: ConversationMeta\n  ): Promise<Conversation> {\n    const raw = await readFile(meta.filePath, \"utf-8\");\n    const turns = this.parseJsonlContent(raw);\n    return { meta: { ...meta, turnCount: turns.length }, turns };\n  }\n\n  parseJsonlContent(raw: string): ConversationTurn[] {\n    const turns: ConversationTurn[] = [];\n\n    for (const line of raw.split(\"\\n\")) {\n      const trimmed = line.trim();\n      if (!trimmed) continue;\n\n      try {\n        const obj = JSON.parse(trimmed);\n        const role = obj.role as \"user\" | \"assistant\";\n        if (role !== \"user\" && role !== \"assistant\") continue;\n\n        const textParts = this.extractTextParts(obj.message?.content);\n        if (!textParts) continue;\n\n        turns.push({ role, text: textParts });\n      } catch {\n        // Skip malformed lines\n      }\n    }\n\n    return turns;\n  }\n\n  private extractTextParts(content: unknown): string | null {\n    if (!Array.isArray(content)) return null;\n\n    const texts: string[] = [];\n    for (const part of content) {\n      if (\n        part &&\n        typeof part === \"object\" &&\n        \"type\" in part &&\n        part.type === \"text\" &&\n        \"text\" in part &&\n        typeof part.text === \"string\"\n      ) {\n        texts.push(this.cleanUserQuery(part.text));\n      }\n    }\n\n    const joined = texts.join(\"\\n\").trim();\n    return joined || null;\n  }\n\n  private cleanUserQuery(text: string): string {\n    const match = text.match(/<user_query>\\s*([\\s\\S]*?)\\s*<\\/user_query>/);\n    if (match) return match[1].trim();\n    return text;\n  }\n\n  // --- Legacy .txt format ---\n\n  private async loadLegacyConversation(\n    meta: ConversationMeta\n  ): Promise<Conversation> {\n    const raw = await readFile(meta.filePath, \"utf-8\");\n    const turns = this.parseLegacyContent(raw);\n    return { meta: { ...meta, turnCount: turns.length }, turns };\n  }\n\n  parseLegacyContent(raw: string): ConversationTurn[] {\n    const turns: ConversationTurn[] = [];\n    const blocks = raw.split(/^(user|assistant):\\s*$/m);\n\n    let currentRole: \"user\" | \"assistant\" | null = null;\n    for (const block of blocks) {\n      const trimmed = block.trim();\n      if (trimmed === \"user\") {\n        currentRole = \"user\";\n      } else if (trimmed === \"assistant\") {\n        currentRole = \"assistant\";\n      } else if (currentRole && trimmed) {\n        turns.push({\n          role: currentRole,\n          text: this.cleanUserQuery(trimmed),\n        });\n        currentRole = null;\n      }\n    }\n\n    return turns;\n  }\n\n  // --- Metadata helpers ---\n\n  private async readConversationMeta(\n    transcriptsDir: string,\n    uuid: string,\n    titleMap: Map<string, string> = new Map()\n  ): Promise<ConversationMeta | null> {\n    const jsonlPath = join(transcriptsDir, uuid, `${uuid}.jsonl`);\n    try {\n      const fileStat = await stat(jsonlPath);\n      const raw = await readFile(jsonlPath, \"utf-8\");\n      // Prefer real title from DB; fall back to first user message\n      const title = titleMap.get(uuid) ?? this.extractTitle(raw, uuid);\n      const turnCount = this.countTurns(raw);\n\n      return {\n        id: uuid,\n        source: \"cursor\",\n        filePath: jsonlPath,\n        title,\n        modifiedAt: fileStat.mtimeMs,\n        turnCount,\n      };\n    } catch {\n      return null;\n    }\n  }\n\n  private async readLegacyMeta(\n    transcriptsDir: string,\n    filename: string\n  ): Promise<ConversationMeta | null> {\n    const filePath = join(transcriptsDir, filename);\n    try {\n      const fileStat = await stat(filePath);\n      const id = basename(filename, \".txt\");\n      const raw = await readFile(filePath, \"utf-8\");\n      const title = this.extractLegacyTitle(raw, id);\n\n      return {\n        id,\n        source: \"cursor\",\n        filePath,\n        title,\n        modifiedAt: fileStat.mtimeMs,\n        turnCount: (raw.match(/^(user|assistant):\\s*$/m) || []).length,\n      };\n    } catch {\n      return null;\n    }\n  }\n\n  private extractTitle(jsonlRaw: string, fallbackId: string): string {\n    for (const line of jsonlRaw.split(\"\\n\").slice(0, 5)) {\n      try {\n        const obj = JSON.parse(line.trim());\n        if (obj.role === \"user\") {\n          const text = this.extractTextParts(obj.message?.content);\n          if (text) {\n            const cleaned = text.replace(/\\s+/g, \" \").trim();\n            return cleaned.length > 60\n              ? cleaned.slice(0, 57) + \"...\"\n              : cleaned;\n          }\n        }\n      } catch {\n        // skip\n      }\n    }\n    return fallbackId.slice(0, 8);\n  }\n\n  private extractLegacyTitle(raw: string, fallbackId: string): string {\n    const match = raw.match(\n      /<user_query>\\s*([\\s\\S]*?)\\s*<\\/user_query>/\n    );\n    if (match) {\n      const text = match[1].replace(/\\s+/g, \" \").trim();\n      return text.length > 60 ? text.slice(0, 57) + \"...\" : text;\n    }\n    return fallbackId.slice(0, 8);\n  }\n\n  private countTurns(jsonlRaw: string): number {\n    let count = 0;\n    for (const line of jsonlRaw.split(\"\\n\")) {\n      if (line.includes('\"role\"')) count++;\n    }\n    return count;\n  }\n\n  // --- Project directory resolution ---\n\n  private async resolveProjectDir(): Promise<string | null> {\n    if (this.projectName) {\n      const dir = join(this.basePath, this.projectName);\n      try {\n        const s = await stat(dir);\n        if (s.isDirectory()) return dir;\n      } catch {\n        // fall through\n      }\n    }\n\n    try {\n      const projects = await readdir(this.basePath, { withFileTypes: true });\n\n      // Collect candidates with transcript dirs\n      type Candidate = { dir: string; count: number; mtime: number };\n      const candidates: Candidate[] = [];\n\n      for (const p of projects) {\n        if (!p.isDirectory()) continue;\n        // Skip temp/AppData/numeric-only project directories\n        if (this.isTempProject(p.name)) continue;\n\n        const transcriptsDir = join(this.basePath, p.name, \"agent-transcripts\");\n        try {\n          const s = await stat(transcriptsDir);\n          if (!s.isDirectory()) continue;\n\n          const entries = await readdir(transcriptsDir);\n          const count = entries.length;\n          if (count === 0) continue;\n\n          candidates.push({\n            dir: join(this.basePath, p.name),\n            count,\n            mtime: s.mtimeMs,\n          });\n        } catch {\n          // no transcripts\n        }\n      }\n\n      if (candidates.length === 0) return null;\n\n      // Prefer the project matching the current working directory\n      const cwd = process.cwd().replace(/\\\\/g, \"-\").replace(/:/g, \"\").toLowerCase();\n      const cwdMatch = candidates.find((c) =>\n        cwd.endsWith(basename(c.dir).toLowerCase())\n      );\n      if (cwdMatch) return cwdMatch.dir;\n\n      // Otherwise pick the project with the most conversations\n      candidates.sort((a, b) => b.count - a.count || b.mtime - a.mtime);\n      return candidates[0].dir;\n    } catch {\n      // .cursor/projects doesn't exist\n    }\n\n    return null;\n  }\n\n  private isTempProject(name: string): boolean {\n    // Skip numeric-only names (e.g. \"1775614169037\")\n    if (/^\\d+$/.test(name)) return true;\n    // Skip AppData/Temp paths encoded as project names\n    if (name.toLowerCase().includes(\"appdata\")) return true;\n    if (name.toLowerCase().includes(\"temp\")) return true;\n    if (name.toLowerCase().includes(\"local-temp\")) return true;\n    return false;\n  }\n\n  private async getTranscriptsDir(): Promise<string | null> {\n    const projectDir = await this.resolveProjectDir();\n    if (!projectDir) return null;\n    return join(projectDir, \"agent-transcripts\");\n  }\n\n  // --- Title map from Cursor's workspace SQLite DB ---\n\n  /**\n   * Returns a map of { [composerId/UUID]: title } by reading\n   * Cursor's GLOBAL state.vscdb (key \"composer.composerHeaders\").\n   * This file contains titles for ALL workspaces.\n   * Uses node:sqlite (Node.js 22+). 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[]) {\n        if (c.composerId && c.name && c.name.trim()) {\n          map.set(c.composerId, c.name.trim());\n        }\n      }\n      return map;\n    } catch (err) {\n      // Non-fatal — fall back to first-message title extraction\n      process.stderr.write(`[ai-memory] title map load failed: ${err}\\n`);\n      return new Map();\n    }\n  }\n\n  private getGlobalDbPath(): string | null {\n    if (process.platform === \"win32\") {\n      const appData = process.env.APPDATA;\n      return appData\n        ? join(appData, \"Cursor\", \"User\", \"globalStorage\", \"state.vscdb\")\n        : null;\n    }\n    if (process.platform === \"darwin\") {\n      return join(\n        homedir(),\n        \"Library\",\n        \"Application Support\",\n        \"Cursor\",\n        \"User\",\n        \"globalStorage\",\n        \"state.vscdb\"\n      );\n    }\n    return join(\n      homedir(),\n      \".config\",\n      \"Cursor\",\n      \"User\",\n      \"globalStorage\",\n      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s.isDirectory();\n    } catch {\n      return false;\n    }\n  }\n\n  async listConversations(): Promise<ConversationMeta[]> {\n    const conversations: ConversationMeta[] = [];\n\n    let projectDirs: string[];\n    try {\n      const entries = await readdir(this.basePath, { withFileTypes: true });\n      // Claude Code encodes the project path as a dir name with path separators\n      // replaced by \"-\" (e.g. /home/user/myproject → -home-user-myproject).\n      // Filter to only dirs that match the current working directory.\n      const cwdEncoded = process.cwd().replace(/[/\\\\:]/g, \"-\").toLowerCase();\n      const cwdBasename = process.cwd().split(/[/\\\\]/).pop()?.toLowerCase() ?? \"\";\n\n      projectDirs = entries\n        .filter((e) => {\n          if (!e.isDirectory()) return false;\n          const name = e.name.toLowerCase();\n          // Match if dir name ends with or contains the cwd path encoding\n          return name.endsWith(cwdEncoded) || name.includes(`-${cwdBasename}`);\n        })\n        .map((e) => join(this.basePath, e.name));\n\n      // If no cwd-specific dirs found, fall back to all dirs (avoids empty results)\n      if (projectDirs.length === 0) {\n        projectDirs = entries\n          .filter((e) => e.isDirectory())\n          .map((e) => join(this.basePath, e.name));\n      }\n    } catch {\n      return [];\n    }\n\n    for (const projectDir of projectDirs) {\n      const files = await readdir(projectDir).catch(() => []);\n      for (const file of files) {\n        if (!file.endsWith(\".jsonl\")) continue;\n        const id = file.replace(\".jsonl\", \"\");\n        if (!UUID_RE.test(id)) continue;\n\n        const filePath = join(projectDir, file);\n        const meta = await this.readMeta(filePath, id);\n        if (meta) conversations.push(meta);\n      }\n    }\n\n    return conversations.sort((a, b) => b.modifiedAt - a.modifiedAt);\n  }\n\n  async loadConversation(meta: ConversationMeta): Promise<Conversation> {\n    const raw = await readFile(meta.filePath, \"utf-8\");\n    const turns = this.parseJsonlContent(raw);\n    return { meta: { ...meta, turnCount: turns.length }, turns };\n  }\n\n  parseJsonlContent(raw: string): ConversationTurn[] {\n    const turns: ConversationTurn[] = [];\n\n    for (const line of raw.split(\"\\n\")) {\n      const trimmed = line.trim();\n      if (!trimmed) continue;\n\n      try {\n        const obj = JSON.parse(trimmed);\n        const role = obj.role as \"user\" | \"assistant\";\n        if (role !== \"user\" && role !== \"assistant\") continue;\n\n        const text = this.extractText(obj);\n        if (!text) continue;\n\n        turns.push({ role, text });\n      } catch {\n        // Skip malformed lines\n      }\n    }\n\n    return turns;\n  }\n\n  private extractText(obj: Record<string, unknown>): string | null {\n    // Claude Code format: message may be in obj.message or obj directly\n    const content =\n      (obj.message as Record<string, unknown>)?.content ?? obj.content;\n\n    if (typeof content === \"string\") {\n      return content.trim() || null;\n    }\n\n    if (Array.isArray(content)) {\n      const texts: string[] = [];\n      for (const part of content) {\n        if (\n          part &&\n          typeof part === \"object\" &&\n          \"type\" in part &&\n          part.type === \"text\" &&\n          \"text\" in part &&\n          typeof part.text === \"string\" &&\n          part.text.trim()\n        ) {\n          texts.push((part.text as string).trim());\n        }\n      }\n      const joined = texts.join(\"\\n\").trim();\n      return joined || null;\n    }\n\n    return null;\n  }\n\n  private async readMeta(\n    filePath: string,\n    id: string\n  ): Promise<ConversationMeta | null> {\n    try {\n      const fileStat = await stat(filePath);\n      const raw = await readFile(filePath, \"utf-8\");\n      const turns = this.parseJsonlContent(raw);\n      const title = this.extractTitle(raw, id);\n\n      return {\n        id,\n        source: \"claude-code\",\n        filePath,\n        title,\n        modifiedAt: fileStat.mtimeMs,\n        turnCount: turns.length,\n      };\n    } catch {\n      return null;\n    }\n  }\n\n  private extractTitle(raw: string, fallbackId: string): string {\n    for (const line of raw.split(\"\\n\").slice(0, 5)) {\n      try {\n        const obj = JSON.parse(line.trim());\n        if (obj.role === \"user\") {\n          const text = this.extractText(obj);\n          if (text) {\n            const cleaned = text.replace(/\\s+/g, \" \").trim();\n            return cleaned.length > 60\n              ? cleaned.slice(0, 57) + \"...\"\n              : cleaned;\n          }\n        }\n      } catch {\n        // skip\n      }\n    }\n    return fallbackId.slice(0, 8);\n  }\n}\n","import type { Source, SourceType } from \"../types.js\";\nimport { CursorSource } from \"./cursor.js\";\nimport { ClaudeCodeSource } from 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package.json

 {
   "name": "ai-memory-cli",
-  "version": "1.1.0",
+  "version": "1.1.2",
   "description": "Extract structured knowledge from AI editor conversations (Cursor, Claude Code) into git-trackable files",
@@ -5,0 +5,0 @@ "type": "module",

README.md

@@ -8,3 +8,3 @@ # ai-memory
 ```bash
-npx ai-memory extract --incremental
+npx ai-memory-cli extract --incremental
 ```
@@ -30,3 +30,3 @@
 
-Cursor transcripts  →  AI extracts          →  .ai-memory/
+Cursor transcripts  �? AI extracts          �? .ai-memory/
 Claude Code sessions    decisions/todos/        ├── decisions/
@@ -52,3 +52,3 @@ architecture/           ├── architecture/
 ```bash
-npx ai-memory extract
+npx ai-memory-cli extract
 ```
@@ -67,8 +67,8 @@
 
-### `list` — Browse available conversations
+### `list` �?Browse available conversations
 
 ```bash
-npx ai-memory list                             # list all conversations with status
-npx ai-memory list --source cursor             # filter by source
-npx ai-memory list --json                      # JSON output
+npx ai-memory-cli list                             # list all conversations with status
+npx ai-memory-cli list --source cursor             # filter by source
+npx ai-memory-cli list --json                      # JSON output
 ```
@@ -78,29 +78,29 @@
 
-### `extract` — Extract memories from conversation history
+### `extract` �?Extract memories from conversation history
 
 ```bash
-npx ai-memory extract                          # auto-detect all sources
-npx ai-memory extract --incremental            # only new/modified conversations
-npx ai-memory extract --pick 4                 # process specific conversation by list index
-npx ai-memory extract --pick 1,4,7             # process multiple by index
-npx ai-memory extract --id b5677be8            # process by conversation ID prefix
-npx ai-memory extract --since "3 days ago"     # conversations modified in last 3 days
-npx ai-memory extract --since "2 weeks ago"    # also supports weeks
-npx ai-memory extract --source cursor          # specify source
-npx ai-memory extract --type decision,todo     # only extract specific types
-npx ai-memory extract --dry-run                # preview conversations to process (no LLM, no writes)
-npx ai-memory extract --verbose                # show LLM request details
-npx ai-memory extract --json                   # JSON output for CI
+npx ai-memory-cli extract                          # auto-detect all sources
+npx ai-memory-cli extract --incremental            # only new/modified conversations
+npx ai-memory-cli extract --pick 4                 # process specific conversation by list index
+npx ai-memory-cli extract --pick 1,4,7             # process multiple by index
+npx ai-memory-cli extract --id b5677be8            # process by conversation ID prefix
+npx ai-memory-cli extract --since "3 days ago"     # conversations modified in last 3 days
+npx ai-memory-cli extract --since "2 weeks ago"    # also supports weeks
+npx ai-memory-cli extract --source cursor          # specify source
+npx ai-memory-cli extract --type decision,todo     # only extract specific types
+npx ai-memory-cli extract --dry-run                # preview conversations to process (no LLM, no writes)
+npx ai-memory-cli extract --verbose                # show LLM request details
+npx ai-memory-cli extract --json                   # JSON output for CI
 ```
 
-### `summary` — Generate a project-level summary
+### `summary` �?Generate a project-level summary
 
 ```bash
-npx ai-memory summary                          # write/update SUMMARY.md
-npx ai-memory summary --output MEMORY.md       # custom output path
-npx ai-memory summary --focus "payment module" # focus on a topic
-npx ai-memory summary --verbose                # show LLM debug info
+npx ai-memory-cli summary                          # write/update SUMMARY.md
+npx ai-memory-cli summary --output MEMORY.md       # custom output path
+npx ai-memory-cli summary --focus "payment module" # focus on a topic
+npx ai-memory-cli summary --verbose                # show LLM debug info
 ```
 
-### `context` — Generate a continuation prompt
+### `context` �?Generate a continuation prompt
 
@@ -110,16 +110,16 @@ For seamlessly resuming work in a new conversation or on another machine:
 ```bash
-npx ai-memory context                          # generate context block (instant, no LLM)
-npx ai-memory context --copy                   # generate and copy to clipboard
-npx ai-memory context --topic "coupon system"  # focus on a specific topic
-npx ai-memory context --recent 7               # only last 7 days of memories
-npx ai-memory context --output CONTEXT.md      # write to file
-npx ai-memory context --summarize              # use LLM to write a condensed prose summary
+npx ai-memory-cli context                          # generate context block (instant, no LLM)
+npx ai-memory-cli context --copy                   # generate and copy to clipboard
+npx ai-memory-cli context --topic "coupon system"  # focus on a specific topic
+npx ai-memory-cli context --recent 7               # only last 7 days of memories
+npx ai-memory-cli context --output CONTEXT.md      # write to file
+npx ai-memory-cli context --summarize              # use LLM to write a condensed prose summary
 ```
 
-The default (no `--summarize`) assembles a structured block directly from your memories — instant, free, and lossless. Paste the output at the start of your next Cursor/Claude Code conversation.
+The default (no `--summarize`) assembles a structured block directly from your memories �?instant, free, and lossless. Paste the output at the start of your next Cursor/Claude Code conversation.
 
-### `init` — Initialize config
+### `init` �?Initialize config
 
 ```bash
-npx ai-memory init
+npx ai-memory-cli init
 ```
@@ -158,3 +158,3 @@
 
-**Content**: Use OAuth Bridge pattern — static/oauth-bridge.html receives the redirect callback and forwards it to the App via postMessage
+**Content**: Use OAuth Bridge pattern �?static/oauth-bridge.html receives the redirect callback and forwards it to the App via postMessage
 
@@ -186,6 +186,6 @@ **Reasoning**: Embedded WebViews cannot receive OAuth redirects directly; bridge page acts as intermediary
 # 1. See what conversations are available
-npx ai-memory list
+npx ai-memory-cli list
 
 # 2. Extract everything (takes a few minutes on first run)
-npx ai-memory extract
+npx ai-memory-cli extract
 
@@ -201,3 +201,3 @@ # 3. Commit the knowledge base
 # After a productive coding session
-npx ai-memory extract --incremental
+npx ai-memory-cli extract --incremental
 
@@ -212,9 +212,9 @@ # Commit new memories
 # Generate a context block and copy to clipboard
-npx ai-memory context --copy
+npx ai-memory-cli context --copy
 
 # Focus on what you're about to work on
-npx ai-memory context --topic "payment module" --copy
+npx ai-memory-cli context --topic "payment module" --copy
 
 # Or write to a file and attach it
-npx ai-memory context --output CONTEXT.md
+npx ai-memory-cli context --output CONTEXT.md
 ```
@@ -237,3 +237,3 @@
 
-The AI will immediately understand your project's decisions, conventions, and current state — no need to re-explain.
+The AI will immediately understand your project's decisions, conventions, and current state �?no need to re-explain.
 
@@ -244,9 +244,9 @@ ### Processing a specific conversation
 # First, find the index of the conversation you want
-npx ai-memory list
+npx ai-memory-cli list
 
 # Then extract just that one
-npx ai-memory extract --pick 3
+npx ai-memory-cli extract --pick 3
 
 # Or match by ID prefix (shown in list output)
-npx ai-memory extract --id b5677be8
+npx ai-memory-cli extract --id b5677be8
 ```
@@ -262,14 +262,9 @@
 Cursor / Claude Code dev work
-        │
-npx ai-memory extract --incremental
-        │
-git add .ai-memory/
+        �?npx ai-memory-cli extract --incremental
+        �?git add .ai-memory/
 git commit && git push
                                                git pull
-                                                    │
-                                               npx ai-memory context --topic "today's work"
-                                                    │
-                                               Paste context → new conversation
-                                                    │
-                                               Seamlessly resume
+                                                    �?                                               npx ai-memory-cli context --topic "today's work"
+                                                    �?                                               Paste context �?new conversation
+                                                    �?                                               Seamlessly resume
 ```
@@ -281,3 +276,3 @@
 
-`ai-memory` works with zero config. To customize, run `npx ai-memory init` or create `.ai-memory/.config.json` manually:
+`ai-memory` works with zero config. To customize, run `npx ai-memory-cli init` or create `.ai-memory/.config.json` manually:
 
@@ -298,3 +293,3 @@ ```jsonc
     "summaryFile": "SUMMARY.md",
-    "language": "zh"             // "zh" or "en" — output language for summaries
+    "language": "zh"             // "zh" or "en" �?output language for summaries
   },
@@ -325,12 +320,12 @@ "model": ""                    // leave empty for auto-selection
 ├── decisions/
-│   ├── 2026-04-12-oauth-bridge-pattern.md
-│   └── 2026-04-13-async-job-queue-design.md
+�?  ├── 2026-04-12-oauth-bridge-pattern.md
+�?  └── 2026-04-13-async-job-queue-design.md
 ├── architecture/
-│   └── 2026-04-10-payment-module-design.md
+�?  └── 2026-04-10-payment-module-design.md
 ├── conventions/
-│   └── 2026-04-08-coding-conventions.md
+�?  └── 2026-04-08-coding-conventions.md
 ├── todos/
-│   └── 2026-04-12-add-retry-logic.md
+�?  └── 2026-04-12-add-retry-logic.md
 ├── issues/
-│   └── 2026-04-11-sqlite-locking-fix.md
+�?  └── 2026-04-11-sqlite-locking-fix.md
 ├── .index/                                 # Extraction index (auto-managed)
@@ -341,3 +336,3 @@ ├── .config.json                            # Configuration (commit this)
 
-Add `.ai-memory/.state.json` to `.gitignore` — it tracks which conversations have been processed and is machine-specific.
+Add `.ai-memory/.state.json` to `.gitignore` �?it tracks which conversations have been processed and is machine-specific.
 
@@ -351,3 +346,3 @@ ---
 - name: Extract AI memories
-  run: npx ai-memory extract --incremental --json
+  run: npx ai-memory-cli extract --incremental --json
   env:
@@ -366,2 +361,2 @@ AI_REVIEW_API_KEY: ${{ secrets.AI_REVIEW_API_KEY }}
 
-MIT — [Conor Liu](https://github.com/conorliu)
+MIT �?[Conor Liu](https://github.com/conorliu)

README.zh-CN.md

@@ -1,2 +0,2 @@
-# ai-memory
+# ai-memory
 
@@ -8,3 +8,3 @@ 从 AI 编辑器对话历史（Cursor、Claude Code）中提取结构化知识，保存为可 git 跟踪的 Markdown 文件。
 ```bash
-npx ai-memory extract --incremental
+npx ai-memory-cli extract --incremental
 ```
@@ -18,3 +18,3 @@
 
-每天用 Cursor 或 Claude Code 开发时，你会做出无数决策："用 OAuth Bridge 模式"、"异步任务走 SSE bridge"、"这个项目里不用 `getServerSideProps`"。这些决策活在聊天记录里，在这些情况下会彻底丢失：
+每天在 Cursor 或 Claude Code 开发时，你会做出无数决策："用 OAuth Bridge 模式"、"异步任务走 SSE bridge"、"这个项目里不用 `getServerSideProps`"。这些决策活在聊天记录里，在这些情况下会彻底丢失：
 
@@ -25,9 +25,9 @@ - 换了台电脑
 
-`ai-memory` 读取本地对话历史，用 AI 提取有价值的内容，保存为结构化 Markdown 文件提交到 git。
+`ai-memory-cli` 读取本地对话历史，用 AI 提取有价值的内容，保存为结构化 Markdown 文件提交到 git。
 
 ```
-你的聊天记录          ai-memory             你的 git 仓库
-（本地，非结构化）     （提取 + 分类）        （结构化，可搜索）
+你的聊天记录          ai-memory-cli         你的 git 仓库
+（本地，非结构化）    （提取 + 分类）       （结构化，可搜索）
 
-Cursor 对话      →   AI 提取             →  .ai-memory/
+Cursor 对话      -->  AI 提取             --> .ai-memory/
 Claude Code 对话      决策/待办/架构/问题      ├── decisions/
@@ -39,3 +39,2 @@ ├── architecture/
 
-
 ---
@@ -55,3 +54,3 @@
 ```bash
-npx ai-memory extract
+npx ai-memory-cli extract
 ```
@@ -63,3 +62,3 @@
 git add .ai-memory/
-git commit -m "chore: 添加 AI 对话知识库"
+git commit --trailer "Made-with: Cursor" -m "chore: 添加 AI 对话知识库"
 ```
@@ -74,5 +73,5 @@
 ```bash
-npx ai-memory list                             # 显示所有对话及提取状态
-npx ai-memory list --source cursor             # 指定来源
-npx ai-memory list --json                      # JSON 输出
+npx ai-memory-cli list                             # 显示所有对话及提取状态
+npx ai-memory-cli list --source cursor             # 指定来源
+npx ai-memory-cli list --json                      # JSON 输出
 ```
@@ -85,14 +84,14 @@
 ```bash
-npx ai-memory extract                          # 自动检测所有来源
-npx ai-memory extract --incremental            # 只处理上次之后新增或修改的对话
-npx ai-memory extract --pick 4                 # 按列表序号处理特定对话
-npx ai-memory extract --pick 1,4,7             # 按多个序号处理
-npx ai-memory extract --id b5677be8            # 按对话 ID 前缀处理
-npx ai-memory extract --since "3 days ago"     # 只处理最近 3 天的对话
-npx ai-memory extract --since "2 weeks ago"    # 也支持 weeks 单位
-npx ai-memory extract --source cursor          # 指定来源
-npx ai-memory extract --type decision,todo     # 只提取指定类型
-npx ai-memory extract --dry-run                # 预览要处理的对话（不调用 LLM，不写入文件）
-npx ai-memory extract --verbose                # 显示 LLM 请求详情
-npx ai-memory extract --json                   # JSON 输出（CI 友好）
+npx ai-memory-cli extract                          # 自动检测所有来源
+npx ai-memory-cli extract --incremental            # 只处理上次之后新增或修改的对话
+npx ai-memory-cli extract --pick 4                 # 按列表序号处理特定对话
+npx ai-memory-cli extract --pick 1,4,7             # 按多个序号处理
+npx ai-memory-cli extract --id b5677be8            # 按对话 ID 前缀处理
+npx ai-memory-cli extract --since "3 days ago"     # 只处理最近 3 天的对话
+npx ai-memory-cli extract --since "2 weeks ago"    # 也支持 weeks 单位
+npx ai-memory-cli extract --source cursor          # 指定来源
+npx ai-memory-cli extract --type decision,todo     # 只提取指定类型
+npx ai-memory-cli extract --dry-run                # 预览要处理的对话（不调用 LLM，不写入文件）
+npx ai-memory-cli extract --verbose                # 显示 LLM 请求详情
+npx ai-memory-cli extract --json                   # JSON 输出（CI 友好）
 ```
@@ -103,6 +102,6 @@
 ```bash
-npx ai-memory summary                          # 生成/更新 SUMMARY.md
-npx ai-memory summary --output MEMORY.md       # 自定义输出路径
-npx ai-memory summary --focus "支付模块"        # 聚焦特定主题
-npx ai-memory summary --verbose                # 显示 LLM 调试信息
+npx ai-memory-cli summary                          # 生成/更新 SUMMARY.md
+npx ai-memory-cli summary --output MEMORY.md       # 自定义输出路径
+npx ai-memory-cli summary --focus "支付模块"        # 聚焦特定主题
+npx ai-memory-cli summary --verbose                # 显示 LLM 调试信息
 ```
@@ -112,14 +111,14 @@
 
-在新对话或换设备时无缝续接上下文：
+在新对话或换设备时无缝续接上下文。
 
 ```bash
-npx ai-memory context                          # 生成上下文块（即时，无需调用 LLM）
-npx ai-memory context --copy                   # 生成并复制到剪贴板
-npx ai-memory context --topic "优惠券系统"      # 聚焦特定主题
-npx ai-memory context --recent 7               # 只包含最近 7 天的记忆
-npx ai-memory context --output CONTEXT.md      # 写入文件
-npx ai-memory context --summarize              # 用 LLM 生成精简的散文摘要（较慢，消耗 token）
+npx ai-memory-cli context                          # 生成上下文块（即时，无需调用 LLM）
+npx ai-memory-cli context --copy                   # 生成并复制到剪贴板
+npx ai-memory-cli context --topic "优惠券系统"      # 聚焦特定主题
+npx ai-memory-cli context --recent 7               # 只包含最近 7 天的记忆
+npx ai-memory-cli context --output CONTEXT.md      # 写入文件
+npx ai-memory-cli context --summarize              # 用 LLM 生成精简的散文摘要（较慢，消耗 token）
 ```
 
-默认模式（不带 `--summarize`）直接从记忆组装结构化块 — 即时、免费、无信息损失。将输出粘贴到下一次 Cursor/Claude Code 对话的开头。
+默认模式（不加 `--summarize`）直接从记忆组装结构化块——即时、免费、无信息损失。将输出粘贴到下一个 Cursor/Claude Code 对话的开头。
 
@@ -129,6 +128,6 @@ ### `init` — 初始化配置
 ```bash
-npx ai-memory init
+npx ai-memory-cli init
 ```
 
-自动检测你使用的编辑器，创建 `.ai-memory/.config.json`，并把 `.ai-memory/.state.json` 加入 `.gitignore`。
+自动检测你使用的编辑器，创建 `.ai-memory/.config.json`，并将 `.ai-memory/.state.json` 加入 `.gitignore`。
 
@@ -139,4 +138,4 @@ ---
 
-| 类型                   | 捕获内容                               |
-| ---------------------- | -------------------------------------- |
+| 类型             | 捕获内容                               |
+|------------------|----------------------------------------|
 | **decision**     | 技术决策：选了什么、为什么、排除了什么 |
@@ -152,12 +151,22 @@ | **architecture** | 系统设计、模块划分、数据流             |
 
+每条记忆保存为独立的 Markdown 文件（如 `.ai-memory/decisions/2026-03-25-oauth-bridge-webview.md`）：
+
 ```markdown
-## [Decision] WebView OAuth Bridge 模式
+# OAuth Bridge 模式（WebView）
 
-- **日期**: 2026-03-25
-- **来源**: cursor:fa49d306 (HF OAuth 集成)
-- **上下文**: hf-app 需要在 App 内嵌 WebView 中完成 Google/Facebook OAuth
-- **决策**: 采用 OAuth Bridge 模式，通过 static/oauth-bridge.html 中转回调，再用 postMessage 传回 App
-- **理由**: App 内嵌 WebView 无法直接接收 redirect，Bridge 页面接收后中转
-- **排除方案**: Deep Link（Android/iOS 行为不一致）、Custom URL Scheme（部分浏览器不支持）
-- **影响**: hf-app login 页面、oauth-web、后端 OAuth 回调路由
+> **日期**: 2026-03-25
+> **来源**: cursor:fa49d306
+> **对话**: HF OAuth 集成
+
+---
+
+**上下文**: hf-app 需要在 App 内嵌 WebView 中完成 Google/Facebook OAuth
+
+**决策**: 采用 OAuth Bridge 模式，通过 static/oauth-bridge.html 中转回调，再用 postMessage 传回 App
+
+**理由**: App 内嵌 WebView 无法直接接收 redirect，Bridge 页面接收后中转
+
+**排除方案**: Deep Link（Android/iOS 行为不一致）、Custom URL Scheme（部分浏览器不支持）
+
+**影响**: hf-app login 页面、oauth-web、后端 OAuth 回调路由
 ```
@@ -169,7 +178,7 @@
 
-| 来源                  | 数据位置                                         | 状态           |
-| --------------------- | ------------------------------------------------ | -------------- |
-| **Cursor**      | `~/.cursor/projects/{name}/agent-transcripts/` | 已支持         |
-| **Claude Code** | `~/.claude/projects/{path}/*.jsonl`            | Beta（自动检测）|
-| Windsurf        | 本地存储路径未公开                               | 计划中         |
+| 来源            | 数据位置                                           | 状态            |
+|-----------------|----------------------------------------------------|-----------------|
+| **Cursor**      | `~/.cursor/projects/{name}/agent-transcripts/`     | 已支持          |
+| **Claude Code** | `~/.claude/projects/{path}/*.jsonl`                | Beta（自动检测）|
+| Windsurf        | 本地存储路径未公开                                 | 计划中          |
 
@@ -184,10 +193,10 @@ ---
 # 1. 先看有哪些对话
-npx ai-memory list
+npx ai-memory-cli list
 
 # 2. 全量提取（首次运行需几分钟）
-npx ai-memory extract
+npx ai-memory-cli extract
 
 # 3. 提交知识库
 git add .ai-memory/
-git commit -m "chore: 初始化 AI 对话知识库"
+git commit --trailer "Made-with: Cursor" -m "chore: 初始化 AI 对话知识库"
 ```
@@ -199,22 +208,22 @@
 # 每次编码结束后
-npx ai-memory extract --incremental
+npx ai-memory-cli extract --incremental
 
-# 提交新增记忆
-git add .ai-memory/ && git commit -m "chore: 更新对话记忆"
+# 提交新记忆
+git add .ai-memory/ && git commit --trailer "Made-with: Cursor" -m "chore: 更新记忆"
 ```
 
-### 开始新对话前（关键用法）
+### 开始新对话
 
 ```bash
 # 生成上下文块并复制到剪贴板
-npx ai-memory context --copy
+npx ai-memory-cli context --copy
 
-# 聚焦到即将处理的模块
-npx ai-memory context --topic "支付模块" --copy
+# 聚焦即将开始的工作
+npx ai-memory-cli context --topic "支付模块" --copy
 
 # 或写入文件作为附件
-npx ai-memory context --output CONTEXT.md
+npx ai-memory-cli context --output CONTEXT.md
 ```
 
-将复制的内容粘贴到新 Cursor/Claude Code 对话的**开头**，输出格式如下：
+将复制的 prompt 粘贴到新 Cursor/Claude Code 会话的开头。输出示例：
 
@@ -224,25 +233,25 @@ ```markdown
 
-### 技术决策（勿随意更改）
-- **OAuth Bridge 模式**: WebView 无法直接接收 redirect，改用 Bridge 页中转...
+### 关键决策（直接遵循，无需重新讨论）
+- **使用 OAuth Bridge 模式**: WebView 无法直接接收 redirect...
 
-### 代码约定（必须遵守）
-- **不在该项目中调用 getServerSideProps**: ...
+### 约定（始终遵守）
+- **此项目中不使用 getServerSideProps**: ...
 
-### 待办事项
-- [ ] 给支付 webhook handler 加重试逻辑
+### 当前待办
+- [ ] 为支付 webhook handler 添加重试逻辑
 ```
 
-AI 会立即了解你的项目决策、规范和当前状态，无需重新解释，实现无缝续接。
+AI 会立即理解你项目的决策、约定和当前状态——无需重新解释。
 
-### 处理特定对话
+### 只处理指定对话
 
 ```bash
-# 先查看对话列表，找到序号
-npx ai-memory list
+# 先找到目标对话的序号
+npx ai-memory-cli list
 
-# 只处理这一个
-npx ai-memory extract --pick 3
+# 只处理这一条
+npx ai-memory-cli extract --pick 3
 
 # 或按 ID 前缀匹配（list 输出中有显示）
-npx ai-memory extract --id b5677be8
+npx ai-memory-cli extract --id b5677be8
 ```
@@ -255,17 +264,12 @@
 ```
-工作电脑                                         家里电脑
-────────                                         ────────
-Cursor / Claude Code 对话开发
-        │
-npx ai-memory extract --incremental
-        │
-git add .ai-memory/
-git commit && git push
-                                                 git pull
-                                                     │
-                                                 npx ai-memory context --topic "今天的工作"
-                                                     │
-                                                 复制 context → 粘贴到新对话开头
-                                                     │
-                                                 无缝续接上下文
+工作机                                         家用机
+──────                                         ──────
+Cursor / Claude Code 开发
+        --> npx ai-memory-cli extract --incremental
+        --> git add .ai-memory/
+git commit --trailer "Made-with: Cursor" && git push
+                                               git pull
+                                               --> npx ai-memory-cli context --topic "今天的工作"
+                                               --> 粘贴上下文到新对话
+                                               --> 无缝续接
 ```
@@ -277,3 +281,3 @@
 
-`ai-memory` 开箱即用，无需配置。如需自定义，运行 `npx ai-memory init` 或手动创建 `.ai-memory/.config.json`：
+`ai-memory-cli` 开箱即用，无需配置。如需自定义，运行 `npx ai-memory-cli init` 或手动创建 `.ai-memory/.config.json`：
 
@@ -288,4 +292,4 @@ ```jsonc
     "types": ["decision", "architecture", "convention", "todo", "issue"],
-    "ignoreConversations": [],   // 需要跳过的对话 UUID
-    "minConversationLength": 5  // 少于 N 轮的对话跳过
+    "ignoreConversations": [],    // 要跳过的对话 UUID
+    "minConversationLength": 5   // 跳过过短的对话
   },
@@ -295,5 +299,5 @@ "output": {
     "summaryFile": "SUMMARY.md",
-    "language": "zh"            // "zh" 或 "en"，影响 summary/context 输出语言
+    "language": "zh"             // "zh" 或 "en"，摘要输出语言
   },
-  "model": ""                   // 留空自动选择
+  "model": ""                    // 留空则自动选择
 }
@@ -304,61 +308,39 @@ ```
 
-| 变量                   | 说明                                        |
-| ---------------------- | ------------------------------------------- |
-| `AI_REVIEW_API_KEY`  | API key（推荐，与 ai-review-pipeline 共用） |
-| `OPENAI_API_KEY`     | OpenAI API key                              |
-| `ANTHROPIC_API_KEY`  | Anthropic API key                           |
-| `AI_REVIEW_BASE_URL` | 自定义 API 接口地址                         |
-| `AI_REVIEW_MODEL`    | 指定模型（默认：`gpt-4o-mini`）           |
+| 变量                   | 说明                                       |
+|------------------------|--------------------------------------------|
+| `AI_REVIEW_API_KEY`    | API key（推荐，与 ai-review-pipeline 共用）|
+| `OPENAI_API_KEY`       | OpenAI API key                             |
+| `ANTHROPIC_API_KEY`    | Anthropic API key                          |
+| `AI_REVIEW_BASE_URL`   | 自定义 API 地址                             |
+| `AI_REVIEW_MODEL`      | 使用的模型（默认：`gpt-4o-mini`）           |
 
 ---
 
-## 输出目录结构
+## 输出结构
 
-每条记忆是一个独立 Markdown 文件，按类型分目录存放：
+每条记忆是独立的文件，按类型分目录存放：
 
 ```
 .ai-memory/
-├── SUMMARY.md                              # 项目级总结（由 summary 命令生成）
-├── decisions/                              # 技术决策
+├── SUMMARY.md                              # 项目总结（summary 命令生成）
+├── decisions/
 │   ├── 2026-04-12-oauth-bridge-pattern.md
 │   └── 2026-04-13-async-job-queue-design.md
-├── architecture/                           # 架构设计
+├── architecture/
 │   └── 2026-04-10-payment-module-design.md
-├── conventions/                            # 编码规范
-│   └── 2026-04-08-typescript-strict-mode.md
-├── todos/                                  # 待办事项
+├── conventions/
+│   └── 2026-04-08-coding-conventions.md
+├── todos/
 │   └── 2026-04-12-add-retry-logic.md
-├── issues/                                 # Bug/问题记录
+├── issues/
 │   └── 2026-04-11-sqlite-locking-fix.md
-├── .index/                                 # 提取索引（自动维护，无需手动修改）
-├── .config.json                            # 配置文件（提交到 git）
+├── .index/                                 # 提取索引（自动管理）
+├── .config.json                            # 配置文件（建议提交到 git）
 └── .state.json                             # 提取状态（加入 .gitignore）
 ```
 
-每个 Markdown 文件的格式：
+将 `.ai-memory/.state.json` 加入 `.gitignore`——它记录哪些对话已处理，是机器相关的文件。
 
-```markdown
-# OAuth Bridge 模式用于 WebView
-
-> **日期**: 2026-03-25
-> **来源**: cursor:fa49d306
-> **对话**: HF OAuth 集成
-
 ---
 
-**上下文**: hf-app 需要在 App 内嵌 WebView 中完成 OAuth
-
-**内容**: 采用 OAuth Bridge 模式，static/oauth-bridge.html 接收 redirect 后通过 postMessage 传回 App
-
-**理由**: App 内嵌 WebView 无法直接接收 redirect 回调
-
-**排除方案**: Deep Link（Android/iOS 行为不一致）、Custom URL Scheme（兼容性差）
-
-**影响**: hf-app login 页面、oauth-web、后端 OAuth 回调路由
-```
-
-`.ai-memory/.state.json` 记录已处理的对话，是机器级别的状态，加入 `.gitignore` 不用提交。
-
----
-
 ## CI 集成
@@ -368,4 +350,4 @@
 # .github/workflows/memory.yml
-- name: 提取 AI 对话记忆
-  run: npx ai-memory extract --incremental --json
+- name: 提取 AI 记忆
+  run: npx ai-memory-cli extract --incremental --json
   env:
@@ -379,7 +361,7 @@ AI_REVIEW_API_KEY: ${{ secrets.AI_REVIEW_API_KEY }}
 
-- Node.js >= 22（依赖内置 `node:sqlite` 模块）
-- 任意 OpenAI 兼容 provider 的 API key
+- Node.js >= 22（内置 `node:sqlite` 支持所需）
+- 任意 OpenAI 兼容提供商的 API key
 
 ## License
 
-MIT — [Conor Liu](https://github.com/conorliu)
+MIT — [Conor Liu](https://github.com/conorliu)

New alerts

Network access

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This module accesses the network.

Found 1 instance in 1 package

Environment variable access

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Package accesses environment variables, which may be a sign of credential stuffing or data theft.

Found 10 instances in 1 package

Filesystem access

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Accesses the file system, and could potentially read sensitive data.

Found 1 instance in 1 package

AI-detected potential code anomaly

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AI has identified unusual behaviors that may pose a security risk.

Found 1 instance in 1 package

Long strings

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Contains long string literals, which may be a sign of obfuscated or packed code.

Found 1 instance in 1 package

Fixed alerts

Network access

Supply chain risk

This module accesses the network.

Found 1 instance in 1 package

Environment variable access

Supply chain risk

Package accesses environment variables, which may be a sign of credential stuffing or data theft.

Found 10 instances in 1 package

Filesystem access

Supply chain risk

Accesses the file system, and could potentially read sensitive data.

Found 1 instance in 1 package

Long strings

Supply chain risk

Contains long string literals, which may be a sign of obfuscated or packed code.

Found 1 instance in 1 package

Improved metrics

Total package byte prevSize

271011

0.1%

Lines of code

2505

0.24%

Worsened metrics

Number of lines in readme file

344

-1.43%

Number of low supply chain risk alerts

36

2.86%

No dependency changes