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knowledge-agent

de thedotmack

Build and query AI-powered knowledge bases from claude-mem observations. Use when users want to create focused "brains" from their observation history, ask questions about past work patterns, or compile expertise on specific topics.

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SKILL.mdLeída en 71ddd11

Knowledge Agent

Build and query AI-powered knowledge bases from claude-mem observations.

What Are Knowledge Agents?

Knowledge agents are filtered corpora of observations compiled into a conversational AI session. Build a corpus from your observation history, prime it (loads the knowledge into an AI session), then ask it questions conversationally.

Think of them as custom "brains": "everything about hooks", "all decisions from the last month", "all bugfixes for the worker service".

Workflow

Step 1: Build a corpus
build_corpus name="hooks-expertise" description="Everything about the hooks lifecycle" project="claude-mem" concepts="hooks" limit=500

Filter options:

  • project — filter by project name
  • types — comma-separated: decision, bugfix, feature, refactor, discovery, change
  • concepts — comma-separated concept tags
  • files — comma-separated file paths (prefix match)
  • query — semantic search query
  • dateStart / dateEnd — ISO date range
  • limit — max observations (default 500)
Step 2: Prime the corpus
prime_corpus name="hooks-expertise"

This creates an AI session loaded with all the corpus knowledge. Takes a moment for large corpora.

Step 3: Query
query_corpus name="hooks-expertise" question="What are the 5 lifecycle hooks and when does each fire?"

The knowledge agent answers from its corpus. Follow-up questions maintain context.

Step 4: List corpora
list_corpora

Shows all corpora with stats and priming status.

Tips

  • Focused corpora work best — "hooks architecture" beats "everything ever"
  • Prime once, query many times — the session persists across queries
  • Reprime for fresh context — if the conversation drifts, reprime to reset
  • Rebuild to update — when new observations are added, rebuild then reprime

Maintenance

Rebuild a corpus (refresh with new observations)
rebuild_corpus name="hooks-expertise"

After rebuilding, reprime to load the updated knowledge:

Reprime (fresh session)
reprime_corpus name="hooks-expertise"

Clears prior Q&A context and reloads the corpus into a new session.

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Instálala a mano

Deska ejecuta esto por ti, para cada agente que elijas. Para ejecutarlo tú en una terminal:

npx skills add thedotmack/claude-mem --skill knowledge-agent

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