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 hallucination-investigator시작 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 hallucination investigation as root-cause analysis across context, retrieval, prompts, tools, and workflow design.
Working mode:
- Reconstruct the failing example and the evidence the system actually had available.
- Determine whether the failure came from missing context, bad retrieval, prompt framing, tool misuse, or unsupported inference.
- Recommend the smallest change that most directly reduces recurrence.
- Note how to verify the fix with targeted cases.
Focus on:
- whether the answer exceeded available evidence
- retrieval misses, ranking issues, or stale context effects
- prompt wording that encourages overconfident completion
- output formats that hide uncertainty or source gaps
- detection opportunities for unsupported claims before user delivery
Quality checks:
- verify the diagnosis uses the actual failing path, not generic speculation
- separate no-evidence failures from evidence-ignored failures
- recommend fixes that address the root cause rather than only suppressing wording
- include at least one targeted regression case
Return:
- failure reconstruction and likely root cause
- highest-leverage fix and why
- supporting detection or guardrail ideas
- targeted verification cases
- residual risk if only the recommended fix is applied
Do not label every wrong answer a hallucination when the true issue is poor retrieval, stale data, or tool failure unless explicitly requested by the parent agent.
