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Diagnose MemMesh connectivity and correctness — is the MCP server reachable, is the key/config valid, do read and write actually work? Use when memory operations fail, searches return empty unexpectedly, observe/save errors occur, or to confirm the plugin is wired correctly.
默认使用会先检查来源的 Prompt；你也可以切换为直接命令，或下载本地副本。
决定是否安装前，请先阅读 SKILL.md，以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt；运行前请先检查来源。
npx skills add https://github.com/ThinkfleetAI/memmesh --skill health命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地？可下载 SkillsMP 当前能够提供的文件。
正在显示 SKILL.md
| name | health |
| description | Diagnose MemMesh connectivity and correctness — is the MCP server reachable, is the key/config valid, do read and write actually work? Use when memory operations fail, searches return empty unexpectedly, observe/save errors occur, or to confirm the plugin is wired correctly. |
Diagnose the MemMesh plugin when something seems off.
memmesh doctor # binary on PATH, MCP config written, skill present, hooks
If the MCP server isn't listed by the agent, the config didn't take — re-run
npx @thinkfleet/memmesh install --force and restart the tool.
Prove the engine actually works, end to end:
memory_save a throwaway item (type: "fact", scope: "session", content
"memmesh healthcheck <runid>").memory_search for "healthcheck <runid>" — assert it comes back.memory_delete (hard) the throwaway so nothing lingers.If step 1 fails with a cap error, you're at the free-tier 500-item limit — see
stats and suggest forget/dream.
| Symptom | Likely cause | Fix |
|---|---|---|
| No MemMesh tools visible | MCP config missing | memmesh install --force, restart tool |
rejected: ... cap | free-tier 500 cap hit | dream / forget, or upgrade tier |
| Search always empty | wrong projectId scope | check switch-project; try userId only |
| Hosted calls 401 | bad/missing MEMMESH_API_KEY | re-set key in config.toml |
State clearly what works and what doesn't — don't claim healthy if the round-trip didn't complete.
Surface emergent behavior patterns MemMesh has mined from a subject's history — recurring habits nobody predefined, each with prevalence, stability, and the evidence behind it. Use when the user asks "what patterns do you see", "what are this user's habits", or wants the patterns that drive predictions.
Load relevant MemMesh context before starting work — searches memory and, for a specific subject, assembles a token-budgeted bundle (profile + behavior patterns + forward predictions + top memories) in one call. Use when beginning a task, switching context, or when project history / past decisions / a subject's profile would help.
Query MemMesh's bi-temporal knowledge graph — multi-hop reasoning across entities, point-in-time "what did we believe on date X", and anticipatory retrieval via spreading activation. Use for questions no single stored fact answers, or to see how knowledge about an entity changed over time.
基于 SOC 职业分类
