菜单
Import memories into MemMesh from an exported file, a native MEMORY.md / CLAUDE.md, an ADR/decision log, or a mem0 export. Use when migrating from another project, restoring a backup, or seeding a new project with existing knowledge.
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 import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。
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
正在显示 SKILL.md
| name | import |
| description | Import memories into MemMesh from an exported file, a native MEMORY.md / CLAUDE.md, an ADR/decision log, or a mem0 export. Use when migrating from another project, restoring a backup, or seeding a new project with existing knowledge. |
Load durable knowledge into MemMesh.
Accept: a MemMesh export (Markdown or JSONL), a native MEMORY.md /
CLAUDE.md, an ADR folder, or a mem0 export dump.
For prose / notes / decisions, memory_observe each item so the engine
re-extracts and builds the knowledge graph:
{ "name": "memory_observe", "arguments": { "text": "<one fact/decision>", "projectId": "<repo>" } }
For a MemMesh JSONL backup where you must preserve exact ids/timestamps, use
memory_save per row instead.
Project rules/decisions → scope: "project" with projectId. Personal
preferences → scope: "user" with userId. Batch by scope so it's consistent.
memory_observe dedupes re-observed text, so a re-run is safe. After import,
run stats to confirm the count, and peek a couple of known facts to confirm
they're retrievable.
Importing a full mem0/Zep setup (not just a file)? Use
memmesh-migrate— it audits call sites, maps the API, and reconciles counts.