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Yao Bayesian Skill

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yaojingang
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.

Overview

Publisheryaojingang
Repositoryyao-open-skills
Skill nameyao-bayesian-skill
Stars
1.3K
Forks
149
Bundled files
35
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 35 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by yaojingang on GitHub. Read the source before you install it.

Installation

Install the Yao Bayesian Skill AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/yaojingang/yao-open-skills.git /tmp/yao-open-skills
mkdir -p .claude/skills
cp -r /tmp/yao-open-skills/skills/yao-bayesian-skill .claude/skills/yao-bayesian-skill
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Yao Bayesian Skill in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Yao Bayesian Skill on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Yao Bayesian Skill is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

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

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Yao Bayesian Skill AI skill do?

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.

Why use Yao Bayesian Skill on TypingMind?

Because you install it once and use it with any model. Yao Bayesian Skill is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Yao Bayesian Skill in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/yaojingang/yao-open-skills/tree/main/skills/yao-bayesian-skill. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Yao Bayesian Skill?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Yao Bayesian Skill?

As many as you like. As long as a model supports skills, you can use Yao Bayesian Skill with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Yao Bayesian Skill AI skill free?

Yes. It is published on GitHub by yaojingang under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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