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knowledge-agentlisted

Build and query AI-powered knowledge bases from keepmind 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.
ManuelStaggl/keepmind · ★ 1 · AI & Automation · score 72
Install: claude install-skill ManuelStaggl/keepmind
# Knowledge Agent Build and query AI-powered knowledge bases from keepmind 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 ```text build_corpus name="hooks-expertise" description="Everything about the hooks lifecycle" project="keepmind" 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 ```text 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 ```text 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 ```text list_corpora ``` Shows all cor