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data-analysis

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Actualizado5 de julio de 2026 a las 08:23

Runs structured AI-native data analysis on tabular datasets (Excel / CSV / Parquet / DataFrame). Pluggable domain architecture — Step 0 reads `references/resolver.md` (a domain-neutral scoring mechanism) plus each registered domain's own `domains/<slug>/triggers.md` to detect which analytical domain applies; all domain knowledge and trigger words live in the domain packs, never in this Skill or the resolver. Drives every analysis through a deterministic 0+9-step workflow (Domain Detect → Profile → Signal Scan → Clarify → Frame → Hypothesize → Verify → Decompose → Synthesize → Follow-up). Hard rules against hallucination — LLM never computes numbers, every claim cites a verdict_id, state persists to JSON. Auto-produces default insights without asking the user what to analyze. Use whenever the user uploads structured data, asks for "analysis" / "insights" / "default insights" / "what does this say" / "默认洞察" / "分析这份数据", asks "why is X declining / growing / changing", or any structured-data analytical query that

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