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/capture

Save a memory to Origin in flow. Active capture verb — use proactively when the user states a preference, makes a decision, corrects you, or shares a durable fact. Invoked as `/capture <content>`.

Installable skillMITBy davepoonUpdated Oct 31, 2026
INTENDED FOROpenClawInstall in a listed agent.

instructions.md

---
name: capture-0c8b9c2e4b61
description: >
  Save a memory to Origin in flow. Active capture verb — use proactively
  when the user states a preference, makes a decision, corrects you, or
  shares a durable fact. Invoked as `/capture <content>`.
argument-hint: "<content>"
allowed-tools: ["mcp__plugin_origin_origin__capture", "mcp__plugin_origin_origin__recall", "mcp__plugin_origin_origin__create_entity", "mcp__plugin_origin_origin__create_relation", "mcp__plugin_origin_origin__accept_revision", "mcp__plugin_origin_origin__dismiss_revision", "Bash"]
---

# /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.

```
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:

| Type | Use for |
|---|---|
| `identity` | Durable 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 |
| `lesson` | Root cause found, workaround discovered, technical insight earned |
| `gotcha` | Sharp edge, surprising behavior, a thing to watch out for |
| `fact` | Durable 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:

```
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:

```
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.

Platform guidance

Imported from the listed AgentSkill.sh category. Complete supplied package files and notices are retained. Required external tools and credentials are not installed. No bundled code was executed during import. Individual agent task behavior has not been tested.