Resolve Knowledge Gaps

Resolve Knowledge Gaps

This skill allows the agent to identify, prioritize, and fill knowledge gaps by systematically consulting available sources — from workspace context to external documentation and web search — then synthesizing a clear, citable answer.

Steps

1. Enumerate the gaps. List every specific question that needs answering before action can continue. Be precise — "understand X" is not a gap; "what is the API schema for X?" is.
2. Prioritize by blocking severity. Questions that block immediate action come first. Informational questions can be deferred.
3. Consult sources in order of priority:
   • Tier 1 (fastest) → Workspace files: .meta/.os/, runbooks, .db/.system.board.yaml, .meta/.os/.system.identity/
   • Tier 2 → KI (Knowledge Items) from past conversations
   • Tier 3 → Official documentation, package READMEs, changelogs
   • Tier 4 (slowest) → Web search, NotebookLM ingestion
4. Stop when the gap is filled. Do not over-research. Once a question is answered with sufficient confidence, move on.
5. Assign confidence levels. For each answer: High (verified from authoritative source) | Medium (inferred) | Low (uncertain).
6. Log unresolved gaps. If a gap cannot be filled, flag it explicitly — do not proceed on assumption.
7. Synthesize. Combine all findings into a concise briefing that directly answers the original questions.
8. Output the synthesis with sources cited.

Output Format

research_result:
  topic: "<topic>"
  answers:
    - question: "<question>"
      answer: "<answer>"
      confidence: "high | medium | low"
      source: "<where this came from>"
  unresolved_gaps:
    - "<question that could not be answered>"
  synthesis: "<paragraph summarizing all findings>"

Notes

• Always check Tier 1 (workspace) before going external — the answer is often already there.
• For large document corpora, escalate to notebooklm toolbox for 1M-token context analysis.
• Low-confidence answers must be flagged to the user before being acted upon.