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Skill Details

Runtime
(claude-5-opus)
Example user message
[userMessage]: Our support RAG answers: “Enterprise customers can request a 30-day data retention period.” The retrieved evidence contains: 2026 Enterprise Data Policy: retention is configurable from 7–30 days. 2025 Security FAQ: enterprise retention is fixed at 7 days. 2026 policy metadata says it supersedes the 2025 FAQ. Check whether the answer is grounded and provide the safest final response.
Example agent response
Evidence Assessment The claim is supported by the supplied 2026 Enterprise Data Policy and its stated supersession metadata. Authoritative evidence The 2026 Enterprise Data Policy states that retention is configurable from 7–30 days. Its metadata states that it supersedes the 2025 Security FAQ. Conflicting evidence The 2025 FAQ states a fixed 7-day period, but the supplied metadata identifies that document as superseded. Claim Check Answer claim Evidence Support Enterprise customers can request a 30-day retention period 2026 Enterprise Data Policy Directly supported Retention is configurable 2026 Enterprise Data Policy Directly supported 7-day retention is mandatory 2025 Security FAQ Contradicted by the superseding policy Grounded Answer Enterprise customers can configure data retention for 7–30 days, so a 30-day retention period is supported by the current 2026 Enterprise Data Policy. The older 7-day statement comes from a superseded FAQ and should not be treated as the current policy. Decision: SUPPORTED — based on the supplied authoritative 2026 source and supersession metadata.
🟧 Claude Skill

Build Reliable Rag With Grounded Answers

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CLAUDE-5-OPUS
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Build reliable RAG systems that retrieve and verify relevant evidence, preserve source context, ground answers in retrieved content, and detect unsupported claims. Design query, retrieval, reranking, context assembly, citation or attribution, and answer-generation workflows with measurable evaluation, failure analysis, regression checks, and traceable change impact. Optimize quality, latency, and cost while validating retrieval and answer faithfulness across real-world edge cases.
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Added 4 days ago
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