context-use

Personal memory from real data exports (ChatGPT, Claude, Instagram, Google, etc.). Search and manage memories extracted from the user's data before responding to anything personal — past conversations, people, places, projects, habits, or events.

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Install skill "context-use" with this command: npx skills add onfabric/context-use/onfabric-context-use-context-use

context-use — Personal Memory CLI

Install: pip install context-use Requires OpenAI API key. Check: context-use config show. Set: context-use config set-key <key>.

When to Use

Use this skill when the user:

  • References past conversations, projects, or events ("remember when…", "we talked about…", "last time…")
  • Mentions people, places, or habits from their life
  • Asks something where their personal history would improve the answer
  • Wants to record something about themselves ("remember that I…")
  • Asks about their preferences, routines, or interests
  • Wants to import or process a data export (ChatGPT, Claude, Instagram, Google)
  • Asks "what do you know about me?" or similar

Do not use when the question is purely technical, general knowledge, or already answered in this session.

Bootstrap (first time)

If context-use memories list --limit 1 returns nothing, the user hasn't ingested data yet.

  1. Ask them for the path to their ZIP data export (they must download it themselves — see the provider table in Ingest).
  2. Run the pipeline:
    context-use pipeline --quick <provider> <path-to-zip>
    
  3. Generate a profile so the user can see what you now know about them:
    context-use agent profile
    
    Share the profile with the user — it builds trust and lets them correct anything wrong early.

Core Rule

Always search memories before responding to anything personal. Weave results naturally — never announce "I found this in your memories."

Commands

Search (primary)

context-use memories search "<query>" --top-k 5
context-use memories search "<query>" --from 2024-01-01 --to 2024-12-31

Use when: user references past conversations, projects, people, events; says "remember when…"; topic benefits from personal context. Skip when: purely technical question; general knowledge; already searched this session. If nothing relevant comes back, move on without mentioning it.

Browse

context-use memories list [--limit 20]
context-use memories get <uuid>

Create / Update / Archive

context-use memories create --content "..." --from 2024-03-01 --to 2024-03-31
context-use memories update <id> --content "..."
context-use memories archive <id1> <id2> --superseded-by <new-id>

Use when: user says "remember that I…"; memory needs correction; memories should merge. Skip when: info is transient or only relevant to current task.

Export

context-use memories export [--format json] [--out path/to/file.md]

Agent

context-use agent synthesise    # distill pattern memories from events
context-use agent profile       # compile first-person user profile
context-use agent ask "..."     # free-form memory task

Suggest synthesise after ingesting new data.

Ingest

User must download their own export (ZIP, don't unzip):

ProviderExport location
ChatGPTSettings → Data Controls → Export Data
ClaudeSettings → Account → Export Data
InstagramSettings → Accounts Center → Download your information (JSON)
Googletakeout.google.com → select products → ZIP
context-use pipeline --quick <provider> <path-to-zip>   # last 30 days
context-use pipeline <provider> <path-to-zip>            # full history, batch API

Providers: chatgpt, claude, instagram, google. Verify: context-use memories list --limit 5.

Errors

ErrorAction
"OpenAI API key not configured"Ask user for key → context-use config set-key <key>
Rate limits (quick mode)Drop --quick to use batch API
Export not readyNormal for Instagram/Google — user waits
context-use not foundpip install context-use
No memories foundGuide user through Bootstrap
Unknown providerMust be: chatgpt, claude, instagram, google
File not foundVerify path with ls, confirm ZIP location

Source Transparency

This detail page is rendered from real SKILL.md content. Trust labels are metadata-based hints, not a safety guarantee.

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