'evidence' 검색 결과

Phase 1 of the Gaia evidence verification pipeline. Use this skill whenever you need to gather, consolidate, or refresh raw evidence for named skills in the registry. Trigger phrases: "collect evidence", "populate the data lake", "gather sources", "run ev-collection", "Phase 1", "compile the evidence index", "refresh the unified lake", "aggregate skill evidence", "build the evidence database". Also invoke as the first step before running ev-star-verification, ev-adversarial-audit, or ev-link-validation — nothing downstream is meaningful without a fresh, compiled index. Covers GitHub repo links, stargazer signals, YouTube showcases, arXiv papers, peer reviews, benchmark results, blog/newsletter posts, and self-attestation artifacts.

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Run this skill for Phase 3 of the evidence verification pipeline — the adversarial audit step. Use when you need to check the evidence data lake for bad data before ingestion: dead links, wrong URL formats (tree/ vs blob/), subjective wording ("elite", "high-quality"), stale migration notes, benchmark catalog misuse/vendor-claim leakage, or skills whose star evidence conflicts with classified evidence level. Triggers on phrases like: "audit the data lake", "adversarial check", "ev-adversarial-audit", "check for noise in evidence", "flag bad evidence", "run the audit phase", "quality check the by-type files", or any reference to Phase 3 of the pipeline.

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医学证据等级排序与编排层 skill - evidence grading orchestrator. 当用户请求"证据等级 / GRADE / 证据排序 / 医学证据评估 / 系统评价排序 / 临床证据排序 / 证据金字塔 / 给 PMID 打分 / Practice Guideline 优先 / Cochrane 优先 / 反向证据交叉验证 / evidence grading / quality of evidence / evidence pyramid / GRADE assessment / Cochrane review ranking / clinical evidence ranking"时,**调用本 skill 进行医学证据自动分级,自动选择最佳信息源**。本 skill 是编排层(L2)·不直接打 NCBI/Europe PMC/ClinicalTrials API,而是编排 6 个底层原子 skill(pubmed-eutils / europepmc-search / clinical-trials-v2 / aact-bulk-trials / bioc-fulltext-fetch / pubtator-entity-search)的召回结果,按证据金字塔(指南 > Meta > RCT > Cohort > Case-Control > Case Report)做 GRADE A/B/C/D 自动评级,自动剔除 editorial/letter/comment。优先使用 BioMCP MCP server 做 fan-out(genomoncology/biomcp);无 BioMCP 时走自建 slow-path 兜底。跨平台无锁(Claude Code / Codex / Gemini CLI)。

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Builds and maintains a DRAFT impact log from notes, messages, status updates and completed work: one row per outcome with its evidence and evidence level, date, who benefited and the source it traces to, plus a gap list of outcomes that still lack evidence, structured so a later review, appraisal or promotion case can draw on it. Use when the user asks to "start an impact log", "add this to my impact log", "log what I achieved this quarter", "pull my wins out of these notes", "turn these messages into evidence for my review" or "what do I have evidence for so far". Do not use for a performance rating, ranking, pay or promotion decision, the skill records evidence and never judges it; for the review narrative itself, use performance-review-drafter; for a role profile built from the work, use job-description-drafter instead. Drafts for human review; never approves, authorises or signs off.

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기존 테스트와 부족한 부분을 점검합니다. 요구 사항, 업무 규칙, 결함을 식별 번호와 실행 결과에 연결하고 테스트 대장으로 검증 여부를 추적합니다.

• 기존 테스트와 부족한 부분을 점검합니다
• 결함 수정의 재발 방지를 확인합니다
• 클라이언트와 서버의 계약 검증을 살핍니다

목적에 맞게 Paperclip의 Runner 평가와 제품 전체 E2E 평가를 선택하고 증거, 실행 이력, 비용, 실패 분류를 바탕으로 검증과 결과 해석, 보고를 진행합니다.

• Runner 평가와 제품 E2E 평가를 선택합니다
• 인증 정보 없이 평가 목록을 확인합니다
• 증거와 실행 기록으로 실패를 해석합니다

이미지, 문서, 영상에서 필요한 문자와 수치, 시간 순서를 추출하고 페이지나 시각과 연결해 검증합니다. 반복 확인을 줄이고 근거를 추적할 수 있는 답변으로 정리합니다.

• 문서의 수치 추출과 확인
• 영상의 사건을 시각과 함께 정리
• 이미지 속 라벨 확인

Review an AI team's work against its acceptance criteria using collected evidence. Match requirements to task results or artifacts, distinguish verified facts from agent claims, and identify uncertainty or missing work before recommending completion.

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• Review evidence before closing an AI team run
• Check whether deliverables meet acceptance criteria
• Separate verified results from agent claims

Run a local check of test evidence and retain source paths in the result. The workflow stops when required evidence is missing, keeping the findings tied to their sources.

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• Checking local test evidence
• Keeping source paths in check results
• Stopping a check when evidence is missing

Review papers, drafts, and research ideas with evidence-linked feedback focused on improvement. Audit low-stakes assessment rubrics, trace supporting evidence, and check rater agreement and uncertainty without ranking people or recommending consequential decisions.

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• Prepare evidence-linked feedback on a paper draft
• Review strengths and limitations of a research idea
• Check assessment criteria and evidence traceability

Retrieve public evidence and linked publications for a supported genetic variant, or look up gene–disease relationships. Preserve sources, conflicting assertions, and explicit search outcomes so qualified professionals can review the findings.

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• Review public evidence for a single genetic variant
• Find publications linked to a resolved variant
• Look up gene–disease relationships

Use a constructive thinking partner to review assumptions, separate evidence from interpretation, and test alternative explanations. Refine conclusions and wording so claims match the available evidence and support decisions under uncertainty.

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• Checking assumptions before an important decision
• Reviewing whether evidence supports a conclusion
• Testing alternative explanations and counterexamples

Manage multi-step financial research with a clear objective, acceptance criteria, and linked evidence. Track findings across turns, audit whether each criterion is supported, and report unresolved gaps while keeping the workflow limited to research.

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• Compare strategies or assets against shared criteria
• Review the evidence supporting an investment thesis
• Resume a research task across multiple turns

Coordinate compliance work across multiple standards and regulations. Use a company profile to identify relevant frameworks, map shared controls, prepare mock audits, and build a unified evidence checklist showing where documents can be reused.

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• Starting a compliance program across multiple frameworks
• Planning an annual audit calendar
• Preparing for a certification audit

Investigate a topic through multiple sources, including primary evidence and counterarguments. Save research materials and notes to files, compare conflicting findings, and produce a cited report that explains conclusions, uncertainty, and limits of the evidence.

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• Check the evidence behind a claim
• Review research papers on a topic
• Compare conflicting sources and findings

Review how evidence can be altered during authorized security exercises on Windows and Linux. Covers logs, timestamps, memory, disk records, and network traces, alongside the signs defenders use to detect manipulation.

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• Planning authorized evidence manipulation tests
• Reviewing Windows and Linux forensic artifacts
• Checking detection coverage for altered evidence

Turn broad life sciences questions into focused research plans. Resolve names and identifiers for genes, diseases, or compounds, select relevant research skills, and combine evidence into a concise answer that explains uncertainty and useful follow-up analyses.

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• Reviewing evidence linking a gene to a disease
• Combining evidence about a variant and its associated traits
• Researching protein structure, function, and drug interactions

Evaluate scientific papers and claims by examining study design, statistics, bias, and the strength of supporting evidence. Helps distinguish supported conclusions from overstatements and provides constructive recommendations for improving research methods and interpretation.

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• Assessing the evidence behind a paper's conclusions
• Finding bias and statistical interpretation errors
• Comparing studies with conflicting findings

Analysis of Competing Hypotheses. Operationalizes Richards Heuer's CIA-tradition technique for systematically narrowing among multiple hypotheses against evidence. Builds an explicit hypothesis-vs-evidence matrix and focuses on disconfirmation rather than confirmation — the central insight: hypotheses cannot be proven, only disconfirmed; the surviving hypothesis is the one with the least disconfirming evidence. Spawns parallel hypothesizers (in isolation, across hypothesis-generation angles) and parallel evidence-gatherers (across evidence classes), then synthesizes into a matrix, diagnosticity analysis, sensitivity analysis, and falsification milestones. Produces feedback only — no code, no tickets, no artifacts.

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Reviews marketing, packaging, web or sustainability text against the environmental-claim rules the user supplies (house policy, regulator guidance extract, industry code) and returns a DRAFT claims review: every environmental claim quoted verbatim with location and family, the evidence the text or evidence pack offers for it with date and scope, the supplied rule passages that bear on each claim, observations as read, and separate question lists for legal and for marketing. No compliance, greenwashing or substantiation verdict. Use when the user asks to "review these green claims", "check this copy against our environmental claims policy", "what evidence do we have for carbon neutral here", "list the sustainability claims in this brochure" or "prepare questions for legal on this eco campaign". Do not use for mapping general factual claims to evidence, use claims-evidence-map instead. Drafts for human review; never approves, authorises or signs off.

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diff-time で「影響範囲を repo 全体で調査した証拠」「失敗系を検証した証拠」「外部依存・レート制限・キャッシュ整合を確認した証拠」の欠落を検出する evidence-sufficiency 観点。defect そのものは既存 skill へ委譲し、本 skill は「そのリスク種別を調査した証拠が差分・PR 本文・テストに残っているか」の meta 評価のみを行う。証拠が同一 diff に同梱（テスト・canary・grep 記録）されていれば充足とみなす

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Discover, build, verify, and optionally export (HTML, optional PDF) the evidence manifest of one SDD Composy task in evidence_required, routing it toward review_required. Use when acceptance evidence must be assembled or checked — 'juntar as evidências da task', 'gerar o relatório de evidências', 'verify the evidence manifest'. Do NOT use to run tests (sdd-qa), review code (sdd-review), or inspect the trace (sdd-trace).

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OpenClaw의 기능 분류와 QA 근거를 대조하여 품질, 기능 충족도, 장기 지원 평가를 재검토하고 입력 데이터를 검증해 성숙도 점수표 문서를 갱신합니다.

• 기능 영역별 성숙도를 재검토합니다
• 예상 사용 절차의 충족도를 확인합니다
• QA 근거로 평가 문서를 갱신합니다

REA의 분석 처리와 캐시 설계를 검토합니다. 결과의 정확성과 근거 접근성을 유지하면서 처리 시간, CPU, 메모리, 에이전트가 다루는 정보량을 개선합니다.

• 분석 처리가 느린 원인 조사
• 캐시 설계 검토
• CPU와 메모리 부하 절감