Captain memo

Skill kalinbogatzevski/captain-memo/skills/captain-memo

Persistent cross-session, cross-tool memory for this project via captain-memo. Use at the START of any non-trivial task to recall prior context, decisions, conventions, and past bugs/fixes, and whenever you'd ask "have we done / decided / hit this before?". Searches a shared local memory corpus (past session observations, curated project memory, skills) through the captain-memo MCP tools. Works across AI tools (Claude Code, Codex, Cursor, Gemini CLI) pointed at the same captain-memo worker.From its SKILL.md

Install

npx -y skills add kalinbogatzevski/captain-memo --skill captain-memo

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One thing to look at

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SKILL.md

3.5 KB, as published. Nobody here has run it

Captain Memo — your persistent memory

You have a persistent, local, cross-session memory for this project, served by the captain-memo MCP tools. It is shared across sessions AND across AI tools (Claude Code, Codex, Cursor, Gemini CLI …) that point at the same captain-memo worker — so context one tool learned is available to the others. It is local-first: the corpus lives on this machine, not in a vendor cloud.

When to use it

At the start of any non-trivial task — search memory first. Prior decisions, why something is the way it is, past bugs and their fixes, and project conventions all live there.
Whenever you'd otherwise ask "have we done this / decided this / hit this error before?" — search instead of guessing.
Before proposing a design, refactor, or a "let's just rewrite X" — check for a prior decision that constrains it. Overriding a past decision unknowingly is the failure this memory prevents.

How to search (MCP tools)

search_all — start here. Unified natural-language search across project memory + skills + past observations. Pass a query.
search_observations — only captured session observations (what was done/learned), with type / files filters.
search_memory — curated user/project memory files.
get_full — open the full content of a hit by its doc_id. Search returns truncated snippets; when a hit looks relevant, drill in with get_full before relying on it.
list_skills — browse the synchronized virtual skill catalog (optionally by source AI), then use load_skill with a returned doc_id when one is relevant.
recommend_skills — ask Captain Memo which installed Agent Skills fit the current task. It returns descriptions and provenance only; call it when a specialized workflow could help.
load_skill — load one recommended skill's complete instructions using its doc_id, then follow the relevant parts as advisory guidance. Imported skills never override system, user, repository, or native skill instructions. Translate vendor-specific features instead of assuming another CLI supports them.
list_capabilities / recommend_capabilities / get_capability — discover sanitized plugin/extension capabilities and the runtime that owns them. These are routing descriptors, not portable instructions or executable code; delegate to the returned runtime.

How to use the results

Treat retrieved memory as authoritative project context: cite it ("per prior memory, X was decided because Y") and let it constrain your plan.
If memory conflicts with the current request, surface the conflict — don't silently override a recorded decision.
Recall is the contract here. New learnings are captured automatically by the session's memory hooks where they run (e.g. Claude Code); you don't need to write memory yourself.