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yao-bayesian-skill姚贝叶斯技能

Agent Skill

yao-bayesian-skill 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

220

周安装

9

GitHub Stars

327

下载量

71
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:yao-bayesian-skill(姚贝叶斯技能)
来源仓库:https://github.com/yaojingang/yao-open-skills
仓库路径:skills/yao-bayesian-skill
安装命令:
npx skills add https://github.com/yaojingang/yao-open-skills --skill yao-bayesian-skill
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/yaojingang/yao-open-skills --skill yao-bayesian-skill

简介

yao-bayesian-skill 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。

  • 适用于贝叶斯相关的研究与数据筛选任务,可结合来源仓库和原始 README 核验具体用法。
  • 通过 npx skills add 命令从 GitHub 仓库安装,支持主流宿主环境集成。
  • 安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写操作。
  • 适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

SKILL.md

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

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.81%
按下载量换算25

Claude

31.2%
按下载量换算22

Cursor

17.94%
按下载量换算13

Gemini CLI

8.29%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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