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yao-bayesian-skill

Convert uncertain real-world choices into an auditable Bayesian evidence-to-action report with priors, evidence grading, posterior update, action thresholds, sensitivity checks, multi-turn decision logs, and Markdown plus bilingual HTML output. Do not use for Bayes theorem tutoring, homework, generic brainstorming with no report, or final licensed medical, legal, or financial advice.

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1,323
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MIT
Last commit
Aug 28, 2026

skills/yao-bayesian-skill/SKILL.md

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Yao Bayesian Skill

Use This Skill For

  • structure a vague choice into hypothesis, time horizon, success metric, and actions
  • set a prior, grade evidence, update posterior, compare action thresholds, and recommend next information
  • start from incomplete input with a weak prior, then improve the judgment through multi-turn questioning
  • export one synchronized Chinese-first markdown plus bilingual html report

Do Not Route Here

  • Bayes theorem tutoring or homework-only calculations
  • broad research or brainstorming with no explicit decision report
  • final professional medical, legal, or investment advice

Default Workflow

  1. Use references/intake-contract.md to convert the request into one structured decision brief.
  2. If input is incomplete, read references/multi-turn-dialogue-loop.md; start with a weak prior and ask the minimum next questions.
  3. Use references/evidence-prior-playbook.md to grade evidence and choose the lightest valid update path.
  4. Run references/prior-hygiene-checklist.md; show only the 3-5 principles most relevant to this case.
  5. Maintain the round log: user input, remaining gap, update path, probability change, and decision readiness.
  6. Run scripts/bayesian_decision_report.py for canonical JSON or scripts/generate_report_bundle.py for markdown + html.
  7. Finalize with references/decision-report-contract.md, references/report-export-pipeline.md, and references/sensitivity-and-safety.md.

Iteration And Implementation Constraints

When extending this skill: state assumptions before coding, keep the smallest valid workflow, touch only files required by the request, and define user-visible success checks before editing. Typical checks: incomplete input yields a weak prior plus follow-up questions; each round is logged; the report explains belief changes; HTML/Markdown still render the intended guidance.

Output Contract

  • Produce a decision report, not a formula dump; mark numbers as observed, estimated, or assumed.
  • Put the plain-language conclusion and action recommendation before technical sections.
  • Include weak evidence, dependence risk, sensitivity, prior-hygiene checks, and high-risk disclaimers when relevant.
  • For multi-turn use, log prior, posterior, readiness, gaps, and formula/update path for each round.
  • Reports default to Simplified Chinese; HTML also supports Chinese/English switching, sticky navigation, collapsible advanced sections, and top-right Print / Save as PDF.
  • Printing or saving HTML as PDF should expand folded sections first.

Reference Map

  • references/intake-contract.md: request-to-brief conversion
  • references/multi-turn-dialogue-loop.md: incomplete-input handling and iterative questioning
  • references/evidence-prior-playbook.md: evidence tiers, priors, update-path selection
  • references/prior-hygiene-checklist.md: default judgment priors for checking priors, evidence, and action intensity
  • references/decision-report-contract.md: required report sections and schema alignment
  • references/report-export-pipeline.md: automatic HTML/Markdown generation and bilingual HTML rules
  • references/sensitivity-and-safety.md: sensitivity analysis and high-risk disclaimers
  • scripts/bayesian_decision_report.py: canonical V0/V1 calculation
  • scripts/generate_report_bundle.py: Chinese-first Markdown plus bilingual HTML

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