memesh-review
Review and optimize the MeMesh memory database. Analyzes health score, finds stale or noisy memories, shows work patterns, and suggests human-reviewed cleanup…
Use MeMesh to remember, recall, and manage AI knowledge across sessions, and to exchange task-focused messages with local agents. Triggers when the user asks to remember something, recall past decisions, forget outdated info, learn from mistakes, analyze work patterns, contact
$ npx -y skills add PCIRCLE-AI/memesh-llm-memory --skill memesh --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/memeshContext preview
The summary Claude sees to decide when to auto-load this skill.
Use MeMesh to remember, recall, and manage AI knowledge across sessions, and to exchange task-focused messages with local agents. Triggers when the user asks to remember something, recall past decisions, forget outdated info, learn from mistakes, analyze work patterns, contact
name: memesh description: Use MeMesh to remember, recall, and manage AI knowledge across sessions, and to exchange task-focused messages with local agents. Triggers when the user asks to remember something, recall past decisions, forget outdated info, learn from mistakes, analyze work patterns, contact another agent, or handle a memesh_message or legacy memesh_message_available notification. Also triggers when the user asks "what do you remember", "where did we leave off", or wants to catch up on a project; when a session starts and project context is needed; and proactively when you make important decisions, fix bugs, learn lessons worth preserving, or owe another agent a requested result or disposition. user-invocable: true
Persistent memory for AI agents. The point is continuity: the next session starts where this one stopped, instead of re-spending thousands of tokens re-discovering project state — and the human never has to re-explain it.
1. MCP tools available? (remember, recall, forget, learn in your tool list) → YES: use MCP tools directly (fastest, structured I/O) → NO: continue to step 2 2. CLI available? Run: memesh status → Works: use CLI commands below → "command not found": Run: npx @pcircle/memesh status → Works: use npx @pcircle/memesh <command> for all commands below
All examples below use CLI. MCP tools accept the same parameters as JSON objects.
| Tool | Purpose | |---|---| | `work_package` | Prepare one bounded untrusted `digest` (calendar cluster) or `transcript` package from the newest Claude Code session under the client's single matching MCP workspace root; submit exactly one strict result or defer. Submit only stages pending human review and retains bounded redacted source turns for comparison; agents cannot apply or reject. No hidden reasoning, raw transcript, transcript path, API key, LLM, embedding, or vector data is exposed or used; hashes identify freshness and workspace scope rather than authentication. | | `remember` | Store knowledge as an entity with observations, tags, and relations; `note` (free text) derives title/observations/name; `replace: true` rewrites a named memory, keeping history | | `recall` | Search stored knowledge; empty query lists recent memories | | `forget` | Archive an entity or remove one exact observation | | `export` | Export memories as portable JSON | | `import` | Import a JSON export with the required skip, append, or overwrite strategy | | `learn` | Record a structured lesson with error, fix, root cause, and prevention | | `task_state` | Read or update user-stated goal, next step, blocker, and finished work | | `briefing` | Assemble the current project's work topology, closing with a capped index of its durable memories | | `user_patterns` | Analyze work schedule, tool preferences, and focus areas | | `improvement` | Propose an evidence-linked product improvement or read its status; only a human may accept or reject it | | `message` | Discover live agents in one project, then contact one exact recipient with a bounded, untrusted payload. Native size and availability failures are distinct; acceptance, discovery, polling, and fetching do not acknowledge |
Four moments. Everything else in this file is detail.
Use the `message` tool when another local agent needs a durable, exact-recipient handoff rather than an inferred memory. `discover` is a bounded project-scoped read of live registrations (session/principal/host/project, declared model and work or explicit unknown, active lease); it performs no send, fetch, ACK, replay, or receipt work and reports router outages explicitly. `send`, `poll`, `fetch`, `intake`, `ack`, `disposition`, `activation`, and `receipts` are independent lifecycle actions: fetching or host acceptance never implies acknowledgement or workflow acceptance.
Size and routing rules:
Repo: PCIRCLE-AI/memesh-llm-memory
Review and optimize the MeMesh memory database. Analyzes health score, finds stale or noisy memories, shows work patterns, and suggests human-reviewed cleanup…