Yao Bayesian Skill
SkillDocs & knowledgeConvert 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.
Available today. Use it from your connected AI after setup.
No other account needed.
Add ahel to your AI once: Claude, ChatGPT, Cursor, Claude Code or Codex. Then ask it to use this.
Then ask your AI: use the Yao Bayesian Skill skill
What this skill tells your AI
The instructions your AI receives, as published by yaojingang/yao-open-skills in skills/yao-bayesian-skill/SKILL.md and read by ahel’s review.
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
markdownplus bilingualhtmlreport
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
- Use
references/intake-contract.mdto convert the request into one structured decision brief. - If input is incomplete, read
references/multi-turn-dialogue-loop.md; start with a weak prior and ask the minimum next questions. - Use
references/evidence-prior-playbook.mdto grade evidence and choose the lightest valid update path. - Run
references/prior-hygiene-checklist.md; show only the 3-5 principles most relevant to this case. - Maintain the round log: user input, remaining gap, update path, probability change, and decision readiness.
- Run
scripts/bayesian_decision_report.pyfor canonical JSON orscripts/generate_report_bundle.pyformarkdown + html. - Finalize with
references/decision-report-contract.md,references/report-export-pipeline.md, andreferences/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 conversionreferences/multi-turn-dialogue-loop.md: incomplete-input handling and iterative questioningreferences/evidence-prior-playbook.md: evidence tiers, priors, update-path selectionreferences/prior-hygiene-checklist.md: default judgment priors for checking priors, evidence, and action intensityreferences/decision-report-contract.md: required report sections and schema alignmentreferences/report-export-pipeline.md: automatic HTML/Markdown generation and bilingual HTML rulesreferences/sensitivity-and-safety.md: sensitivity analysis and high-risk disclaimersscripts/bayesian_decision_report.py: canonical V0/V1 calculationscripts/generate_report_bundle.py: Chinese-first Markdown plus bilingual HTML
Signals
- GitHub stars
- 1k
- Forks
- 147
- Last commit
- Aug 2026
ahel review
K6low
bundled executables the agent is told to run
Automated review, not a security audit. Ruleset v1+k2.
Advanced
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yao-bayesian-skill- Source
- github.com/yaojingang/yao-open-skills