Agent skill

Yao Expert Skill

by yaojingang in yaojingang/yao-open-skills

Create expert-level learning reports and tutorials from any domain, industry, technology, role, market, product idea, or vague field question.

MITAuto-check passedDocuments & Office

Install Yao Expert Skill

skills CLI
$ npx skills add yaojingang/yao-open-skills --skill yao-expert-skill -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install yaojingang/yao-open-skills yao-expert-skill --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/yaojingang/yao-open-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/yao-expert-skill .claude/skills/yao-expert-skill && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
yao-expert-skill
GitHub stars
1.3k
Token cost
~1.7k tokens
SKILL.md length
776 words
Files
42 (incl. scripts, references)
Skills in repo
16
Repo updated
First seen
Licence
MIT

At a glance

Create expert-level learning reports and tutorials from any domain, industry, technology, role, market, product idea, or vague field question.

  • Works in 7 steps: Read references/domain-expert-method.md;… → Read… → Draft the canonical report in Markdown… → …
  • The user wants to quickly build domain expertise
  • SKILL.md covers Own The Following Job, Inputs, Do Not Route Here and Default Workflow, plus 3 more sections
  • Understand an industry

What it does

Yao Expert Skill is an agent skill from yaojingang/yao-open-skills. Create expert-level learning reports and tutorials from any domain, industry, technology, role, market, product idea, or vague field question. Use when the user wants to quickly build domain expertise, understand an industry, generate a structured expert study report, build a keyword library, design Feynman self-tests, or export the result as Markdown, DOCX, PDF, and HTML. Do not use for short factual answers, pure business model diagnosis, standalone beginner tutorials with no domain-structure research, simple…

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 47 other files, including scripts and reference files (for example `README.md`, `agents/interface.yaml` and `evals/semantic_config.json`).

It sits in Documents & Office, covering Word documents, Document parsing and Product strategy. It works with Microsoft Word. The repository describes itself as: OpenYao public skills collection: reusable AI assets for decision-making, business analysis, tutorials, research evidence gathering, and document generation. The licence is MIT.

When your agent uses it

  • The user wants to quickly build domain expertise
  • Understand an industry
  • Generate a structured expert study report
  • Build a keyword library

Example prompts

  • “/yao-expert-skill”

Workflow steps

7 steps, taken from the first numbered list in SKILL.md.

  1. Read references/domain-expert-method.md; capture assumptions and the expert-learning brief.
  2. Read references/research-and-source-quality.md; build a source plan and verify current facts when the domain is time-sensitive.
  3. Draft the canonical report in Markdown using templates/expert-report-template.md.
  4. Add the tutorial path, keyword teaching cards, concept map, representative people/company/case map, Feynman tests, evidence register, and…
  5. Read references/report-and-tutorial-contract.md; check section coverage, evidence labels, and learning sufficiency.
  6. Read references/export-and-layout-quality.md; run scripts/export_expert_report.py for Markdown, DOCX, PDF, and HTML.
  7. Run scripts/validate_artifacts.py and fix layout, table, anchor, overflow, citation, and local-path issues before delivery.

What it can do on your machine

Read from SKILL.md and the folder at commit 093996e. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/, which the agent can run.

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Yao Expert Skill loads about 1.7k tokens when it runs, and up to ~9k if it reads all its reference files. Until then it costs about 145 tokens; SKILL.md has 776 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~145
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~9k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from yaojingang/yao-open-skills at commit 093996e, republished under its MIT licence (© yaojingang). 776 words, ~1,742 tokens.

Download SKILL.mdSave it as .claude/skills/yao-expert-skill/SKILL.md (or your agent's skills folder). This skill also uses 41 other files; get the full folder from GitHub.
name
yao-expert-skill
description
Create expert-level learning reports and tutorials from any domain, industry, technology, role, market, product idea, or vague field question. Use when the user wants to quickly build domain expertise, understand an industry, generate a structured expert study report, build a keyword library, design Feynman self-tests, or export the result as Markdown, DOCX, PDF, and HTML. Do not use for short factual answers, pure business model diagnosis, standalone beginner tutorials with no domain-structure research, simple file conversion, or unsourced opinion writing.
metadata.author
Yao Team
metadata.maturity_tier
production
metadata.artifact_family
expert-learning-report

Yao Expert Skill

Turn a domain, industry, technology, role, product direction, or fuzzy idea into an expert learning packet: one structured report, one tutorial path, a keyword system, Feynman tests, and four polished export formats.

Own The Following Job

  • Normalize the user's topic into domain, region, purpose, audience, time horizon, output depth, and exclusions.
  • Build domain expertise from structure first: boundary, classifications, value chain, actors, demand, supply, competition, lifecycle, policy, technology, capital, risks, and change variables.
  • Use authority-first research and separate fact, inference, hypothesis, and unknown.
  • Generate 50-100 keyword teaching cards. Each keyword must include a plain-language one-liner, concept explanation, bottom logic, real example, practical application, role/effect, related people/companies/institutions when relevant, common misconception, and evidence.
  • Explain difficult concepts and underlying logic with simple analogies plus real domain examples, so a newcomer can understand how the field works rather than only memorize terms.
  • Begin every report with a reader-facing 导读摘要 that introduces the learning material, highlights, reading path, and structural logic before the formal report sections.
  • Write each major module with a natural introductory paragraph and transitions before tables, so the report reads as coherent learning material instead of a hard glossary or matrix dump.
  • Generate 10 Feynman questions with reference answers and a scoring rubric.
  • Produce Markdown, Word, PDF, and HTML artifacts, with layout checks for tables, borders, overflow, anchors, fixed left-side navigation, and local-path leakage.

Inputs

Expect one or more of:

  • a domain, industry, technology, market, role, company direction, or vague idea
  • geography, language, audience, use case, time horizon, and desired depth
  • existing notes, links, papers, reports, screenshots, or source constraints
  • requested output formats, naming, style, deadline, and privacy constraints

When the user gives only a topic, do not stall. Use the defaults in references/domain-expert-method.md, state the assumptions, and continue unless a missing input would materially change the package.

Do Not Route Here

  • one-off factual answers or quick explanations
  • generic web research that does not produce an expert learning packet
  • pure business model work; use a business model skill instead
  • beginner tutorial creation with no industry/domain structure; use a tutorial skill instead
  • finished-file conversion with no report or tutorial design
  • legal, medical, financial, or safety advice as a final recommendation; keep those as educational research with source and uncertainty notes

Default Workflow

  1. Read references/domain-expert-method.md; capture assumptions and the expert-learning brief.
  2. Read references/research-and-source-quality.md; build a source plan and verify current facts when the domain is time-sensitive.
  3. Draft the canonical report in Markdown using templates/expert-report-template.md.
  4. Add the tutorial path, keyword teaching cards, concept map, representative people/company/case map, Feynman tests, evidence register, and uncertainty log.
  5. Read references/report-and-tutorial-contract.md; check section coverage, evidence labels, and learning sufficiency.
  6. Read references/export-and-layout-quality.md; run scripts/export_expert_report.py for Markdown, DOCX, PDF, and HTML.
  7. Run scripts/validate_artifacts.py and fix layout, table, anchor, overflow, citation, and local-path issues before delivery.
Show full SKILL.md (312 more words)Show less

Output Contract

The normal output set is:

  • {basename}.md: canonical expert learning report and tutorial packet
  • {basename}.docx: Word document export with readable tables and restrained report styling
  • {basename}.pdf: PDF export checked for page layout and table overflow risk
  • {basename}.html: standalone HTML report with a fixed left-side numbered navigation menu and section anchors
  • a short delivery note with assumptions, source coverage, uncertainty, validation result, and next learning steps

Quality Gates

  • The topic boundary includes wide, narrow, exclusion, and data/source scope.
  • The report begins with 导读摘要, including introduction, highlights, reading path, and logic overview; Markdown, DOCX, PDF, and HTML exports must all preserve this opening summary.
  • Every major module has a reader-facing introduction before dense tables or matrices.
  • Key claims are backed by source tier, date, and confidence.
  • Every major judgment is labeled as fact, inference, hypothesis, or unknown.
  • Keyword teaching cards cover demand, product, technology, value chain, business model, competition, policy, finance, operations, risks, and trends.
  • Every keyword teaching card explains: what it means, how to understand it in one sentence, why it exists, how it works, where it appears in the real domain, how to apply it, what role it plays, which people/companies/institutions are associated with it when relevant, and what beginners often misunderstand.
  • Representative people, companies, institutions, products, and cases are included as learning anchors, with role labels and source notes rather than unsupported rankings.
  • The tutorial can take a beginner from orientation to self-check, not just list terms.
  • HTML contains a fixed left-side navigation tree with ordered indices, compact four-character Chinese anchor labels, transparent background, and no standalone sidebar panel styling.
  • PDF exports remove the HTML navigation node before printing and hide browser print chrome; no navigation labels, file:// paths, dates, or browser page footers should appear.
  • DOCX/PDF/HTML exports exist and pass scripts/validate_artifacts.py, or remaining failures are named precisely.

Reference Map

  • references/domain-expert-method.md
  • references/research-and-source-quality.md
  • references/report-and-tutorial-contract.md
  • references/export-and-layout-quality.md
  • templates/expert-report-template.md
  • templates/expert-report.css
  • templates/report-html-shell.html
  • scripts/export_expert_report.py
  • scripts/validate_artifacts.py
  • evals/trigger_cases.json

© yaojingang, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 41 other files (scripts, references) in skills/yao-expert-skill of yaojingang/yao-open-skills.

  • SKILL.md
  • README.md
  • agents/interface.yaml
  • evals/semantic_config.json
  • evals/trigger_cases.json
  • input/expert_brief_template.json
  • manifest.json
  • reference-materials/README.md
  • reference-materials/industry_expert_skill_design.docx
  • reference-materials/industry_learning_deep_research_report.docx
  • references/domain-expert-method.md
  • references/export-and-layout-quality.md
  • references/report-and-tutorial-contract.md
  • references/research-and-source-quality.md
  • reports/artifact-design-profile.md
  • … and 27 more

Open the folder on GitHubat commit 093996e

Compare with similar skills

Yao Expert Skill next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Yao Expert Skill compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Yao Expert Skill this skillyaojingang/yao-open-skills1.3k—~1.7kAutomated safety check: PassMIT
MarkitdownImCa0/just-laws78114 repos~3.2kAutomated safety check: NotesMIT
DOCX ToolkitXiaomiMiMo/MiMo-Code14k—~2.4kAutomated safety check: PassApache-2.0
Markitdownjimmc414/Kosmos5952 repos~1.7kAutomated safety check: PassNone
Liteparsebastani-inc/atomic855—~1.4kAutomated safety check: PassMIT
Industry Bid Document WriterGet00/BiaoShu-SKILL173—~4.6kAutomated safety check: PassApache-2.0

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Works with

Questions about Yao Expert Skill

What does Yao Expert Skill do?

Create expert-level learning reports and tutorials from any domain, industry, technology, role, market, product idea, or vague field question. Yao Expert Skill is an agent skill from yaojingang/yao-open-skills. Create expert-level learning reports and tutorials from any domain, industry, technology, role, market, product idea, or vague field question.

When should I use Yao Expert Skill?

Yao Expert Skill fits situations like: the user wants to quickly build domain expertise; understand an industry; generate a structured expert study report; build a keyword library.

How do I install Yao Expert Skill in Claude Code?

Run `npx skills add yaojingang/yao-open-skills --skill yao-expert-skill -a claude-code`. Or copy the skill folder (skills/yao-expert-skill in yaojingang/yao-open-skills) into .claude/skills/yao-expert-skill in your project. Claude Code loads it when a task matches its description.

How do I install Yao Expert Skill in Codex?

Run `npx skills add yaojingang/yao-open-skills --skill yao-expert-skill -a codex`. Or copy the skill folder (skills/yao-expert-skill in yaojingang/yao-open-skills) into .agents/skills/yao-expert-skill in your project. Codex loads it when a task matches its description.

Can I use Yao Expert Skill in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add yaojingang/yao-open-skills --skill yao-expert-skill -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/yao-expert-skill, .gemini/skills/yao-expert-skill, .github/skills/yao-expert-skill and .opencode/skills/yao-expert-skill in your project.

What does Yao Expert Skill need to run?

SKILL.md names no scripts, command-line tools or credentials: Yao Expert Skill is instructions for the agent only.

Does Yao Expert Skill access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Yao Expert Skill safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Yao Expert Skill use?

Yao Expert Skill is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Yao Expert Skill use?

About 1.7k tokens (SKILL.md is roughly 7k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 7.3k tokens, read only when the agent opens those files.

What are the alternatives to Yao Expert Skill?

Skills that share tags, products or a category with Yao Expert Skill: Markitdown (ImCa0/just-laws, 781 stars), DOCX Toolkit (XiaomiMiMo/MiMo-Code, 14k stars), Markitdown (jimmc414/Kosmos, 595 stars) and Liteparse (bastani-inc/atomic, 855 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Yao Expert Skill?

yaojingang (a GitHub user) maintains it in yaojingang/yao-open-skills, which has 1,323 GitHub stars. The repository holds 16 skills in this directory. The repository was last updated on August 28, 2026.

Source: yaojingang/yao-open-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.