| name | mnemos-capture |
| description | Manually distill the current session into the Mnemos brain — decisions, facts, and corrections — without waiting for the SessionEnd capture hook. Use when the user says "/mnemos-capture", "capture this", "remember this", "save what we learned", "record this decision", or before a /clear, a context compaction, or ending a long session. |
Mnemos Capture
Manual counterpart to the SessionEnd capture hook. The hook reads the raw
transcript and runs it through extraction after the session is over. This skill
runs now, while you still hold the session in context — which means you can
distill what actually mattered instead of leaving a model to mine it out of a
20KiB transcript later.
Use it before /clear, before a compaction, or any time the user says a
conclusion is worth keeping.
Choosing a path
Prefer the MCP tools (mcp__mnemos__*) — they work identically against a
local and a hosted brain. Fall back to the CLI only when no mcp__mnemos__*
tool is available or every call errors; the CLI resolves its own DSN and may
target a different brain than the MCP server is serving.
Step 1 — Decide what is worth keeping
This is the whole job. The brain is only as useful as it is uncluttered, and
every junk claim dilutes recall for every future session.
Capture:
- Decisions, with the reasoning and the alternatives rejected.
- Facts discovered about the system that were not obvious from the code —
behaviors, constraints, version quirks, why something is the way it is.
- Corrections: things believed at the start of the session that turned out to
be wrong. These are the highest-value claims in the brain, because they
overwrite something that is already in there misleading people.
- Preferences and constraints the user stated.
Do not capture:
- Your own narration ("I'll now read the file", "Let me check the tests").
The capture hook filters assistant narration for a reason; do not
reintroduce it by hand.
- Anything already recorded in the repo — code structure, git history,
CLAUDE.md, ADRs. The brain is for what the repo does not say.
- Transient state: file paths you happened to open, test output, command
invocations that worked.
- Secrets, tokens, credentials, or customer data of any kind. If a fact cannot
be stated without a secret, omit the fact.
If nothing clears this bar, say so and write nothing. An honest "nothing worth
capturing this session" is a valid outcome.
Step 2 — Write it
Route each item to the tool that fits it:
- Decisions →
record_decision with the statement, the reasoning, the
alternatives considered, and a risk level. Link the beliefs it rests on when
you know their claim ids. A decision recorded here can have an outcome
attached later, which is how the brain learns whether it was right.
- Facts, corrections, narrative context →
process_text with a short
prose summary. Write it as standalone assertions a future session can
understand with zero context from this one — no "it", no "the above", no
"as discussed". One claim per sentence.
- A single durable fact the user explicitly asked to remember →
remember, which is the direct path and skips extraction.
Tag the work so it stays traceable: pass a run id derived from the session or
the branch when the tool accepts one.
CLI fallback
mnemos process --text "<distilled summary>"
mnemos process --llm --text "<distilled summary>"
mnemos decision record --statement "<statement>"
Step 3 — Confirm
Report back exactly what was written: how many claims were extracted, the
decision ids, and the run id. Then state what you deliberately left out and
why, in one line — that is how the user catches a capture that dropped
something they cared about.
If extraction returned zero claims from non-empty text, that is a failure, not
a no-op: the LLM provider is likely misconfigured. Say so and point at
mnemos doctor.
Failure modes
- Brain unreachable — report the error verbatim and suggest
mnemos doctor. Do not silently drop the capture; the user believes it was saved.
- Capture times out — the default budget is 4m (
MNEMOS_CAPTURE_TIMEOUT),
sized for a slow local model. Capture a shorter summary rather than retrying
the same payload.
- Duplicate content — re-running this skill in one session re-ingests what
the last run already took. Capture only what happened since the previous
run, and say which window you covered.