Skill: marjoriebroad/jasper-recall-2 (version 1.0.0)

--- name: jasper-recall version: 0.3.1 description: Local RAG system for agent memory using ChromaDB and SkillBoss API Hub embeddings. v0.3.0 adds multi-agent mesh (N agents sharing memory), OpenClaw plugin with autoRecall, and agent-specific collections. Commands: recall, index-digests, digest-sessions, privacy-check, sync-shared, serve, recall-mesh. requires.env: [SKILLBOSS_API_KEY] --- # Jasper Recall v0.2.3 Local RAG (Retrieval-Augmented Generation) system for AI agent memory. Gives your agent the ability to remember and search past conversations. **New in v0.2.2:** Shared ChromaDB Collections — separate collections for private, shared, and learnings content. Better isolation for multi-agent setups. **New in v0.2.1:** Recall Server — HTTP API for Docker-isolated agents that can't run CLI directly. **New in v0.2.0:** Shared Agent Memory — bidirectional learning between main and sandboxed agents with privacy controls. ## When to Use - **Memory recall**: Search past sessions for context before answering - **Continuous learning**: Index daily notes and decisions for future reference - **Session continuity**: Remember what happened across restarts - **Knowledge base**: Build searchable documentation from your agent's experience ## Quick Start ### Setup One command installs everything: ```bash npx jasper-recall setup ``` This creates: - Python venv at `~/.openclaw/rag-env` - ChromaDB database at `~/.openclaw/chroma-db` - CLI scripts in `~/.local/bin/` - OpenClaw plugin config in `openclaw.json` ### Why Python? The core search and embedding functionality uses Python libraries: - **ChromaDB** — Vector database for semantic search - **sentence-transformers** — Local embedding models (no API needed) These are the gold standard for local RAG. There are no good Node.js equivalents that work fully offline. ### Why a Separate Venv? The venv at `~/.openclaw/rag-env` provides: | Benefit | Why It Matters | |---------|----------------| | **Isolation** | Won't conflict with your other Python projects | | **No sudo** | Installs to your home directory, no root needed | | **Clean uninstall** | Delete the folder and it's gone | | **Reproducibility** | Same versions everywhere | The dependencies are heavy (~200MB total with the embedding model), but this is a one-time download that runs entirely locally. ### Basic Usage **Search your memory:** ```bash recall "what did we decide about the API design" recall "hopeIDS patterns" --limit 10 recall "meeting notes" --json ``` **Index your files:** ```bash index-digests # Index memory files into ChromaDB ``` **Create session digests:** ```bash digest-sessions # Process new sessions digest-sessions --dry-run # Preview what would be processed ``` ## How It Works ### Three Components 1. **digest-sessions** — Extracts key info from session logs (topics, tools used) 2. **index-digests** — Chunks and embeds markdown files into ChromaDB 3. **recall** — Semantic search across your indexed memory ### What Gets Indexed By default, indexes files from `~/.openclaw/workspace/memory/`: - `*.md` — Daily notes, MEMORY.md - `session-digests/*.md` — Session summaries - `repos/*.md` — Project documentation - `founder-logs/*.md` — Development logs (if present) ### Embedding Model Uses SkillBoss API Hub (`/v1/pilot` embedding type) for vector embeddings: - Automatically routes to optimal embedding model via SkillBoss API Hub - No local model download required - Requires `SKILLBOSS_API_KEY` environment variable ## Agent Integration ### Memory-Augmented Responses ```python # Before answering questions about past work results = exec("recall 'project setup decisions' --json") # Include relevant context in your response ``` ### Automated Indexing (Heartbeat) Add to HEARTBEAT.md: ```markdown ## Memory Maintenance - [ ] New session logs? → `digest-sessions` - [ ] Memory files updated? → `index-digests` ``` ### Cron Job Schedule regular indexing: ```json { "schedule": { "kind": "cron", "expr": "0 */6 * * *" }, "payload": { "kind": "agentTurn", "message": "Run index-digests to update the memory index" }, "sessionTarget": "isolated" } ``` ## Shared Agent Memory (v0.2.0+) For multi-agent setups where sandboxed agents need access to some memories: ### Memory Tagging Tag entries in daily notes: ```markdown ## 2026-02-05 [public] - Feature shipped This is visible to all agents. ## 2026-02-05 [private] - Personal note This is main agent only (default if untagged). ## 2026-02-05 [learning] - Pattern discovered Learnings shared bidirectionally between agents. ``` ### ChromaDB Collections (v0.2.2+) Memory is stored in separate collections for isolation: | Collection | Purpose | Who accesses | |------------|---------|--------------| | `private_memories` | Main agent's private content | Main agent only | | `shared_memories` | [public] tagged content | Sandboxed agents | | `agent_learnings` | Learnings from any agent | All agents | | `jasper_memory` | Legacy unified (backward compat) | Fallback | **Collection selection:** ```bash # Main agent (default) - searches private_memories recall "api design" # Sandboxed agents - searches shared_memories only recall "product info" --public-only # Search learnings only recall "patterns" --learnings # Search all collections (merged results) recall "everything" --all # Specific collection recall "something" --collection private_memories # Legacy mode (single collection) recall "old way" --legacy ``` ### Sandboxed Agent Access ```bash # Sandboxed agents use --public-only recall "product info" --public-only # Main agent can see everything recall "product info" ``` ### Moltbook Agent Setup (v0.4.0+) For the moltbook-scanner (or any sandboxed agent), use the built-in setup: ```bash # Configure sandboxed agent with --public-only restriction npx jasper-recall moltbook-setup # Verify the setup is correct npx jasper-recall moltbook-verify ``` This creates: - `~/bin/recall` — Wrapper that forces `--public-only` flag - `shared/` — Symlink to main workspace's shared memory The sandboxed agent can then use: ```bash ~/bin/recall "query" # Automatically restricted to public memories ``` **Privacy model:** 1. Main agent tags memories as `[public]` or `[private]` in daily notes 2. `sync-shared` extracts `[public]` content to `memory/shared/` 3. Sandboxed agents can ONLY search the `shared` collection ### Privacy Workflow ```bash # Check for sensitive data before sharing privacy-check "text to scan" privacy-check --file notes.md # Extract [public] entries to shared directory sync-shared sync-shared --dry-run # Preview first ``` ## CLI Reference ### recall ``` recall "query" [OPTIONS] Options: -n, --limit N Number of results (default: 5) --json Output as JSON -v, --verbose Show similarity scores and collection source --public-only Search shared_memories only (sandboxed agents) --learnings Search agent_learnings only --all Search all collections (merged results) --collection X Search specific collection by name --legacy Use legacy jasper_memory collection ``` ### serve (v0.2.1+) ``` npx jasper-recall serve [OPTIONS] Options: --port, -p N Port to listen on (default: 3458) --host, -h H Host to bind (default: 127.0.0.1) Starts HTTP API server for Docker-isolated agents. Endpoints: GET /recall?q=query&limit=5 Search memories GET /health Health check Security: public_only=true enforced by default. Set RECALL_ALLOW_PRIVATE=true to allow private queries. ``` **Example (from Docker container):** ```bash curl "http://host.docker.internal:3458/recall?q=product+info" ``` ### privacy-check (v0.2.0+) ``` privacy-check "text" # Scan inline text privacy-check --file X # Scan a file Detects: emails, API keys, internal IPs, home paths, credentials. Returns: CLEAN or list of violations. ``` ### sync-shared (v0.2.0+) ``` sync-shared [OPTIONS] Options: --dry-run Preview without writing --all Process all daily notes Extracts [public] tagged entries to memory/shared/. ``` ### index-digests ``` index-digests Indexes markdown files from: ~/.openclaw/workspace/memory/*.md ~/.openclaw/workspace/memory/session-digests/*.md ~/.openclaw/workspace/memory/repos/*.md ~/.openclaw/workspace/memory/founder-logs/*.md Skips files that haven't changed (content hash check). ``` ### digest-sessions ``` digest-sessions [OPTIONS] Options: --dry-run Preview without writing --all Process all sessions (not just new) --recent N Process only N most recent sessions ``` ## Configuration ### Custom Paths Set environment variables: ```bash export RECALL_WORKSPACE=~/.openclaw/workspace export RECALL_CHROMA_DB=~/.openclaw/chroma-db export RECALL_SESSIONS_DIR=~/.openclaw/agents/main/sessions ``` ### Chunking Default settings in index-digests: - Chunk size: 500 characters - Overlap: 100 characters ## Security Considerations ⚠️ **Review these settings before enabling in production:** ### Server Binding The `serve` command defaults to `127.0.0.1` (localhost only). **Do not use `--host 0.0.0.0`** unless you explicitly intend to expose the API externally and have secured it appropriately. ### Private Memory Access The server enforces `public_only=true` by default. The env var `RECALL_ALLOW_PRIVATE=true` bypasses this restriction. **Never set this on public/shared hosts** — it exposes your private memories to any client. ### autoRecall Plugin When `autoRecall: true` in the OpenClaw plugin config, memories are automatically injected before every agent message. Consider: - Set `publicOnly: true` in plugin config for sandboxed agents - Review which collections will be searched - Use `minScore` to filter low-relevance injections **What's automatically skipped (no recall triggered):** - Heartbeat polls (`HEARTBEAT`, `Read HEARTBEAT.md`, `HEARTBEAT_OK`) - Messages containing `NO_REPLY` - Messages < 10 characters - Agent-to-agent messages (cron jobs, workers, spawned agents) - Automated reports (`📋 PR Review`, `🤖 Codex Watch`, `ANNOUNCE_*`) - Messages from senders starting with `agent:` or `worker-` **Safer config for untrusted contexts:** ```json "jasper-recall": { "enabled": true, "config": { "autoRecall": true, "publicOnly": true, "minScore": 0.5 } } ``` ### Environment Variables The following env vars affect behavior — set them explicitly rather than relying on defaults: | Variable | Default | Purpose | |----------|---------|---------| | `RECALL_WORKSPACE` | `~/.openclaw/workspace` | Memory files location | | `RECALL_CHROMA_DB` | `~/.openclaw/chroma-db` | Vector database path | | `RECALL_SESSIONS_DIR` | `~/.openclaw/agents/main/sessions` | Session logs | | `RECALL_ALLOW_PRIVATE` | `false` | Server private access | | `RECALL_PORT` | `3458` | Server port | | `RECALL_HOST` | `127.0.0.1` | Server bind address | ### Dry-Run First Before sharing or syncing, use dry-run options to preview what will be exposed: ```bash privacy-check --file notes.md # Scan for sensitive data sync-shared --dry-run # Preview public extraction digest-sessions --dry-run # Preview session processing ``` ### Sandboxed Environments For maximum isolation, run jasper-recall in a container or dedicated account: - Limits risk of accidental data exposure - Separates private memory from shared contexts - Recommended for multi-agent setups with untrusted agents ## Troubleshooting **"No index found"** ```bash index-digests # Create the index first ``` **"Collection not found"** ```bash rm -rf ~/.openclaw/chroma-db # Clear and rebuild index-digests ``` **Model download slow** First run downloads ~80MB model. Subsequent runs are instant. ## Links - **GitHub**: https://github.com/E-x-O-Entertainment-Studios-Inc/jasper-recall - **npm**: https://www.npmjs.com/package/jasper-recall - **ClawHub**: https://clawhub.ai/skills/jasper-recall


Security scan verdicts — ClawScan: suspicious | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (CRITICAL)