capture

Skill

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Files1
  • @skills/capture/SKILL.md

/capture

Capture a single memory in the moment. Active verb: agent captures the moment of insight, like a photograph.

How to invoke

Call the origin MCP server's capture tool with the user's content as a complete, self-contained statement. Attach topic from cwd or the conversation — don't make the user type it.
text
capture(content="<args, written as a full sentence with WHY>",
        memory_type="<picked from the 6 types>",
        entity="<primary entity name, if any>",
        space=<inferred>)

memory_type — agent picks one of 6

The daemon classifies when a local model or API key is configured. In local memory mode it does not, so the agent picks the type from the content itself. Use this mapping:
TypeUse for
identityDurable facts about the user (role, company, language preference)
preference"I prefer X because Y" — a habit, a correction, a stylistic choice
decision"Going with A over B because C" — a specific choice with rationale
lessonRoot cause found, workaround discovered, technical insight earned
gotchaSharp edge, surprising behavior, a thing to watch out for
factDurable info about people, projects, tools — anchor to entity when possible
If two types fit, pick the one closest to why the memory matters. A decision also implies a preference, but decision is more specific.

entity — extract the anchor

Pick the single most important named thing in the content: a person, project, tool, place. Use the exact name. Example: "Alice prefers TDD because…" → entity="Alice". If the content has no named anchor, omit entity.

topic / space inference

  • cwd inside a repo → repo name (e.g. ~/Repos/origin/... → "origin").
  • Outside any repo → most recent topic from the conversation, or omit.
  • Always pass space when scope is known; if uncertain, run list_spaces later (post-PR-C) or omit.

Multiple entities or relations

The MCP capture tool takes a single primary entity. For additional entities or relations, use the dedicated MCP tools. If the content names more than one entity, capture the memory first, then for each additional entity:
create_entity(name="<entity>", entity_type="<person|project|tool|place>")
For a relation between two entities:
create_relation(from_entity="<a>", to_entity="<b>", relation_type="<verb>")
Skip these calls when the daemon has an LLM — its post-ingest enrichment covers extraction.

What to capture

  • Decisions: "Going with approach A because B"
  • Preferences: "Prefers TDD because catches regressions early"
  • Corrections: "Actually it's C, not D"
  • Identity / project facts: "Works on Origin, a local memory daemon for AI tools"

What NOT to capture

  • System prompts, boot logs, heartbeats
  • Transient task state ("currently working on...")
  • Tool output, command results, architecture dumps
  • Single-word acknowledgments
  • Things the user can trivially re-derive (file paths, recent git history)

Atomic ideas

One capture = one idea. "Prefers TDD" and "Uses pytest" are two captures, not one.

When to use

  • User explicitly says "remember this", "save that", "capture this".
  • User states a durable preference / decision / correction proactively (no ask required — that's the floor, not the trigger).

When NOT to use

  • End of session bulk store → use /handoff (multi-item batch).
  • Pulling memories back out → use /recall.

Post-capture contradiction signal

After capture returns, check response.triggered_revisions and response.auto_superseded.

auto_superseded (no action needed)

If auto_superseded is non-empty, the daemon already resolved the contradiction. Surface it as informational:
text
Note: auto-superseded mem_X. Origin replaced a prior protected memory because
trust=high and similarity > 0.9. No action needed.
No accept/dismiss call required. The revision was applied automatically.

triggered_revisions (human review needed)

If triggered_revisions is non-empty (and auto_superseded is empty), render an inline block to the user:
text
Stored mem_new.

This capture topic-matches a protected memory now flagged for revision:
  - mem_target_abc

Action: accept (replace original content) | dismiss (drop the revision) | leave (decide later)
Inline verb map:
  • accept: accept_revision(target_source_id="mem_target_abc")
  • dismiss: dismiss_revision(target_source_id="mem_target_abc")
  • leave: no call; surfaces again in next /brief
Both fields can technically be non-empty in a single response (multiple protected matches), but in practice only one fires per capture: auto_superseded fires when trust=full and similarity > 0.9, triggered_revisions fires otherwise.
If neither field is non-empty, the capture stored cleanly with no conflicts.
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