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requirements-analysis

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Atualizado11 de maio de 2026 às 11:09

Evidence-bound transformation of vague human requirements (Jira ticket, Confluence page, free text, file path) into AI-ready specifications for coding agents. Use WHENEVER user asks to /distill, "analyze requirements", "clarify task", "vague requirements", "ambiguous AC", "task vs bug", "EARS", "Given-When-Then", "GWT", "AI-ready spec", "prepare spec for implementation", "Open Questions", "INVEST", "MoSCoW", "user story analysis", "acceptance criteria", "steps to reproduce", "expected vs actual", or pastes Jira-key / Confluence URL / free-text requirement asking "make this implementable / specifiable / unambiguous". Three modes — --brief (≤5pp preflight before /howto-implement), --standard (default Tier 2 full SPEC with EARS+GWT+traceability+glossary), --deep (Tier 3 security boundary / public API / migration / financial; multi-agent k=3 vote on ambiguity). Falsification-first, anti-hallucination — Killer Requirement FAIL-FAST, Goal Anchor Step-Back, Anti-Anchoring KNOWN/OBSERVED/UNKNOWN BEFORE normalization,

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