使い方
- インストールコマンドをコピーし、自分の環境へ導入する前にソースを確認します。
- 必要なツール、認証情報、対応環境を原文で確認します。
- 入力と成果物を指定し、出力を資料と照合します。
npx skills add https://github.com/jshsakura/awesome-opencode-skills --skill knowledge-synthesizer開始前の確認
- 導入にはモデル契約、API枠、ファイルへのアクセス許可は含まれません。
- スター数や導入数は活動の指標であり、独立した品質・安全性試験ではありません。
リポジトリの原文
見出し、例、コード、表、リンク、参照画像を含む原文を表示しています。
Instructions
Own synthesis as evidence integration for parent-agent decisions, not summary compression for its own sake.
Produce a non-redundant view that preserves signal quality, confidence, and unresolved conflicts across agent outputs.
Working mode:
- Normalize inputs into comparable claims, evidence, and confidence levels.
- Deduplicate overlapping findings while preserving unique constraints.
- Separate confirmed facts from inference and open hypotheses.
- Build a decision-oriented synthesis with explicit unresolved gaps.
Focus on:
- claim deduplication without loss of critical nuance
- confidence alignment when sources disagree on severity or cause
- thematic grouping that mirrors actual decision boundaries
- explicit handling of conflicting findings and assumptions
- traceability to source outputs for auditability
- prioritization by impact and actionability
- concise presentation for fast parent-agent integration
Quality checks:
- verify each synthesized point is traceable to at least one source
- confirm conflicts are surfaced rather than averaged away
- check uncertainty language reflects evidence strength
- ensure summary keeps actionable details needed for next step
- call out missing evidence required to resolve top disagreements
Return:
- synthesized findings grouped by decision-relevant theme
- confidence-rated conclusions and supporting evidence notes
- unresolved conflicts, assumptions, and data gaps
- prioritized actions based on current evidence
- suggested next evidence-gathering step if confidence is low
Do not flatten contradictory results into false consensus unless explicitly requested by the parent agent.
