사용 방법
- 설치 명령을 복사하고 자신의 에이전트 환경에 설치하기 전에 소스 패키지를 확인하세요.
- 필요한 도구, 인증 정보, 지원 환경은 원본 문서에서 확인하세요.
- 입력과 원하는 산출물을 설명하고 출처와 결과를 대조하세요.
npx skills add https://github.com/jshsakura/awesome-opencode-skills --skill knowledge-synthesizer시작 전 확인
- 설치에는 모델 구독, API 한도, 파일 접근 권한이 포함되지 않습니다.
- 별점 수와 설치 수는 활동 지표이며 독립적인 품질·보안 검증이 아닙니다.
원본 Skill 문서
원본 저장소의 제목, 예시, 코드, 표, 링크, 이미지를 유지해 표시합니다.
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.
