@opencode-manager/memory

@opencode-manager/memory

Semantic memory and planning plugin for OpenCode AI agents

Quick Start

pnpm add @opencode-manager/memory

Add to your opencode.json:

{
  "plugin": ["@opencode-manager/memory@latest"]
}

The local embedding model downloads automatically on install. For API-based embeddings (OpenAI or Voyage), see Configuration.

Features

• Semantic Memory Search - Store and retrieve project memories using vector embeddings
• Multiple Memory Scopes - Categorize memories as convention, decision, or context
• Automatic Deduplication - Prevents duplicates via exact match and semantic similarity detection
• Compaction Context Injection - Injects conventions and decisions into session compaction for seamless continuity
• Automatic Memory Injection - Injects relevant project memories into user messages via semantic search with distance filtering and caching
• Project KV Store - Ephemeral key-value storage with TTL management for project state
• Bundled Agents - Ships with Code, Architect, and Librarian agents preconfigured for memory-aware workflows
• CLI Tools - Export, import, list, stats, cleanup, upgrade, status, and cancel commands via ocm-mem binary
• Dimension Mismatch Detection - Detects embedding model changes and guides recovery via reindex

Agents

The plugin bundles four agents that integrate with the memory system:

Agent	ID	Mode	Description
code	ocm-code	primary	Primary coding agent with memory awareness. Checks memory before unfamiliar code, stores architectural decisions and conventions as it works. Delegates planning operations to @librarian subagent.
architect	ocm-architect	primary	Read-only planning agent. Researches the codebase, delegates to @librarian for broad knowledge retrieval, designs implementation plans, then hands off to code via memory-plan-execute.
librarian	ocm-librarian	subagent	Expert agent for managing project memory. Handles post-compaction memory extraction and contradiction resolution.
auditor	ocm-auditor	subagent	Read-only code auditor with access to project memory for convention-aware reviews. Invoked via Task tool to review diffs, commits, branches, or PRs against stored conventions and decisions.

The auditor agent is a read-only subagent (temperature: 0.0) that can read memory but cannot write, edit, or delete memories or execute plans. It is invoked by other agents via the Task tool to review code changes against stored project conventions and decisions.

The architect agent operates in read-only mode (temperature: 0.0, all edits denied) with additional message-level read-only enforcement via the experimental.chat.messages.transform hook. After the user approves a plan, it calls memory-plan-execute which creates a new code session with the full plan as context.

Tools

Memory Tools

Tool	Description
memory-read	Search and retrieve project memories with semantic search
memory-write	Store a new project memory
memory-edit	Update an existing project memory
memory-delete	Delete a project memory by ID
memory-health	Health check, reindex, or upgrade the plugin to latest version
memory-plan-execute	Create a new Code session and send an approved plan as the first prompt

Project KV Tools

Ephemeral key-value storage for project state with automatic TTL-based expiration.

Tool	Description
memory-kv-set	Store a value with optional TTL (default 7 days)
memory-kv-get	Retrieve a value by key
memory-kv-list	List all active KV entries for the project. Optionally filter by key prefix.
memory-kv-delete	Delete a key-value pair by key

Ralph Loop Tools

Iterative development loops with automatic auditing. Runs in an isolated git worktree by default, or in the current directory with inPlace.

Tool	Description
ralph-cancel	Cancel an active Ralph loop by worktree name
ralph-status	Check status of Ralph loops. Supports restart to resume inactive loops.
memory-plan-ralph	Execute an architect plan using a Ralph iterative loop. Supports inPlace parameter.

Slash Commands

Command	Description	Agent
/review	Run a code review on current changes	auditor (subtask)
/ralph-loop	Start a Ralph loop (delegates to memory-plan-ralph)	code
/cancel-ralph	Cancel the active Ralph loop	code

CLI

Manage memories using the ocm-mem CLI. The CLI auto-detects the project ID from git and resolves the database path automatically.

ocm-mem <command> [options]

Global options (apply to all commands):

Flag	Description
--db-path <path>	Path to memory database
--project, -p <name>	Project name or SHA (auto-detected from git)
--dir, -d <path>	Git repo path for project detection
--help, -h	Show help

Commands

export

Export memories to file (JSON or Markdown).

ocm-mem export --format markdown --output memories.md
ocm-mem export --project my-project --scope convention
ocm-mem export --limit 50 --offset 100

Flag	Description
--format, -f	Output format: json or markdown (default: json)
--output, -o	Output file path (prints to stdout if omitted)
--scope, -s	Filter by scope: convention, decision, or context
--limit, -l	Max number of memories (default: 1000)
--offset	Pagination offset (default: 0)

import

Import memories from file.

ocm-mem import memories.json --project my-project
ocm-mem import memories.md --project my-project --force

Flag	Description
--format, -f	Input format: json or markdown (auto-detected from extension)
--force	Skip duplicate detection and import all

list

List all projects with memory counts.

ocm-mem list

stats

Show memory statistics for a project (scope breakdown).

ocm-mem stats
ocm-mem stats --project my-project

cleanup

Delete memories by criteria.

ocm-mem cleanup --older-than 90
ocm-mem cleanup --ids 1,2,3 --force
ocm-mem cleanup --scope context --dry-run
ocm-mem cleanup --all --project my-project

Flag	Description
--older-than <days>	Delete memories older than N days
--ids <id,id,...>	Delete specific memory IDs
--scope <scope>	Filter by scope: convention, decision, or context
--all	Delete all memories for the project
--dry-run	Preview what would be deleted without deleting
--force	Skip confirmation prompt

upgrade

Check for plugin updates and install the latest version.

ocm-mem upgrade

status

Show Ralph loop status for the current project.

ocm-mem status
ocm-mem status --project my-project

Flag	Description
--project, -p <name>	Project name or SHA (auto-detected from git)

cancel

Cancel a Ralph loop by worktree name.

ocm-mem cancel my-worktree-name
ocm-mem cancel --project my-project my-worktree-name

Flag	Description
--project, -p <name>	Project name or SHA (auto-detected from git)

Configuration

On first run, the plugin automatically copies the bundled config to your config directory:

• Path: ~/.config/opencode/memory-config.jsonc
• Falls back to: $XDG_CONFIG_HOME/opencode/memory-config.jsonc

The plugin supports JSONC format, allowing comments with // and /* */.

You can edit this file to customize settings. The file is created only if it doesn't already exist. If a config exists at the old location (~/.local/share/opencode/memory/config.json), it will be automatically migrated to the new location.

{
  "embedding": {
    "provider": "local",
    "model": "all-MiniLM-L6-v2",
    "dimensions": 384,
    "baseUrl": "",
    "apiKey": ""
  },
  "dedupThreshold": 0.25,
  "logging": {
    "enabled": false,
    "debug": false,
    "file": ""
  },
  "compaction": {
    "customPrompt": true,
    "maxContextTokens": 4000
  },
  "memoryInjection": {
    "enabled": true,
    "debug": false,
    "maxTokens": 2000,
    "cacheTtlMs": 30000
  },
  "messagesTransform": {
    "enabled": true,
    "debug": false
  },
  "executionModel": "",
  "auditorModel": "",
  "ralph": {
    "enabled": true,
    "defaultMaxIterations": 15,
    "cleanupWorktree": false,
    "defaultAudit": true,
    "model": "",
    "minAudits": 1
  }
}

For API-based embeddings:

{
  "embedding": {
    "provider": "openai",
    "model": "text-embedding-3-small",
    "apiKey": "sk-..."
  }
}

Options

Embedding

• embedding.provider - Embedding provider: "local", "openai", or "voyage"
• embedding.model - Model name
  • local: "all-MiniLM-L6-v2" (384d)
  • openai: "text-embedding-3-small" (1536d), "text-embedding-3-large" (3072d), or "text-embedding-ada-002" (1536d)
  • voyage: "voyage-code-3" (1024d) or "voyage-2" (1536d)
• embedding.dimensions - Vector dimensions (optional, auto-detected for known models)
• embedding.apiKey - API key for openai/voyage providers
• embedding.baseUrl - Custom endpoint (optional, defaults to provider's official API)

Storage

• dataDir - Directory for SQLite database storage (default: "~/.local/share/opencode/memory")
• dedupThreshold - Similarity threshold for deduplication (0–1, default: 0.25, clamped to 0.05–0.40)

Config Location

• Config file: ~/.config/opencode/memory-config.jsonc (or $XDG_CONFIG_HOME/opencode/memory-config.jsonc)
• Old config location (~/.local/share/opencode/memory/config.json) is automatically migrated on first load

Logging

• logging.enabled - Enable file logging (default: false)
• logging.debug - Enable debug-level log output (default: false)
• logging.file - Log file path. When empty, resolves to ~/.local/share/opencode/memory/logs/memory.log (default: ""). Logs remain in the data directory, only config has moved.

When enabled, logs are written to the specified file with timestamps. The log file has a 10MB size limit with automatic rotation.

Compaction

• compaction.customPrompt - Use a custom compaction prompt optimized for session continuity (default: true)
• compaction.maxContextTokens - Token budget for injected memory context with priority-based trimming (default: 4000)

Memory Injection

• memoryInjection.enabled - Inject relevant project memories into user messages via semantic search (default: true)
• memoryInjection.debug - Enable debug logging for memory injection (default: false)
• memoryInjection.maxResults - Maximum number of vector search results to retrieve (default: 5)
• memoryInjection.distanceThreshold - Maximum vector distance for a memory to be considered relevant; lower values are stricter (default: 0.5)
• memoryInjection.maxTokens - Token budget for the injected <project-memory> block (default: 2000)
• memoryInjection.cacheTtlMs - How long (ms) to cache results for identical queries (default: 30000)

Messages Transform

• messagesTransform.enabled - Enable the messages transform hook that handles memory injection and Architect read-only enforcement (default: true)
• messagesTransform.debug - Enable debug logging for messages transform (default: false)

Execution

• executionModel - Model override for plan execution sessions, format: provider/model (e.g. anthropic/claude-haiku-3-5-20241022). When set, memory-plan-execute uses this model for the new Code session. When empty or omitted, OpenCode's default model is used (typically the model field from opencode.json). Recommended: Set this to a fast, cheap model (e.g. Haiku or MiniMax) and use a smart model (e.g. Opus) for the Architect session — planning needs reasoning, execution needs speed.

Ralph

• ralph.enabled - Enable Ralph iterative development loops (default: true)
• ralph.defaultMaxIterations - Default max iterations for loops, 0 = unlimited (default: 15)
• ralph.cleanupWorktree - Auto-remove worktree on cancel (default: false)
• ralph.defaultAudit - Run auditor after each coding iteration by default (default: true)
• ralph.model - Model override for Ralph sessions (provider/model), falls back to executionModel (default: "")
• ralph.stallTimeoutMs - Watchdog stall detection timeout in milliseconds (default: 60000)
• ralph.minAudits - Minimum audit iterations required before completion (default: 1)

Top-level

• defaultKvTtlMs - Default TTL for KV store entries in milliseconds (default: 604800000 / 7 days)

Auditor

• auditorModel - Model override for the auditor agent (provider/model). When set, overrides the auditor agent's default model. When not set, uses platform default (default: "")

architect → code Workflow

Plan with a smart model, execute with a fast model. The architect agent researches and designs; the code agent implements.

After the architect presents a plan, the user approves via one of four execution modes:

• New session — Creates a new Code session via memory-plan-execute
• Execute here — Executes the plan in the current session (code agent takes over immediately)
• Ralph (worktree) — Runs the plan in an isolated git worktree with iterative coding/auditing via memory-plan-ralph
• Ralph (in place) — Same as Ralph worktree but runs in the current directory (no worktree isolation)

Set executionModel in your config to a fast model (e.g., Haiku) and use a smart model (e.g., Opus) for the architect session.

See the full workflow guide for setup details.

Ralph Loop

The Ralph loop is an iterative development system that alternates between coding and auditing phases:

• Coding phase — The Code agent works on the task
• Auditing phase — The Auditor agent reviews changes against project conventions
• Repeat — Findings from the audit feed back into the next coding iteration

The loop completes when the Code agent outputs the completion promise. It auto-terminates after maxIterations (if set) or after 3 consecutive errors.

By default, Ralph loops run in an isolated git worktree. Set inPlace: true to run in the current directory instead (skips worktree creation, auto-commit, and cleanup).

See the full documentation for details on the Ralph loop system.

Documentation

Full documentation available at chriswritescode-dev.github.io/opencode-manager/features/memory

Development

pnpm build      # Compile TypeScript to dist/
pnpm test       # Run tests
pnpm typecheck  # Type check without emitting

License

MIT