Agent skill

Open Source Project Article

by digoal in digoal/blog

Analyze an open-source project from a repository URL and write a deeply sourced Chinese Markdown article.

GPL-2.0Auto-check passedDevelopment

Install Open Source Project Article

skills CLI
$ npx skills add digoal/blog --skill open-source-project-article -a claude-code

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

GitHub CLI
$ gh skill install digoal/blog open-source-project-article --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/digoal/blog.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/open-source-project-article .claude/skills/open-source-project-article && 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
open-source-project-article
GitHub stars
8.6k
Token cost
~1.3k tokens
SKILL.md length
574 words
Files
4 (incl. references)
Skills in repo
98
Repo updated
First seen
Licence
GPL-2.0

At a glance

Analyze an open-source project from a repository URL and write a deeply sourced Chinese Markdown article.

  • Works in 5 steps: Fetch and read the project README.md or… → Use DeepWiki MCP to analyze the… → Identify and ask necessary clarification… → …
  • The user asks to research a GitHub/open-source project
  • SKILL.md covers Non-Negotiable Source Order, Inputs, Evidence Workflow and Article Requirements, plus 2 more sections
  • Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Open Source Project Article is an agent skill from digoal/blog. Analyze an open-source project from a repository URL and write a deeply sourced Chinese Markdown article. Use when the user asks to research a GitHub/open-source project, read its README, use DeepWiki MCP for architecture analysis, search related articles, compare competitors, validate claims, and save the final article under the current project's markdown directory.

Its SKILL.md is about 1.3k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including reference files (for example `agents/openai.yaml`, `references/article-structure.md` and `references/validation-checklist.md`).

It sits in Development, covering Technical documentation and Markdown. It works with Model Context Protocol and GitHub. The repository describes itself as: AI,Opensource,Database,Business,Finance,Minds. git clone --depth 1 https://github.com/digoal/blog. The licence is GPL-2.0.

When your agent uses it

  • The user asks to research a GitHub/open-source project
  • Read its README
  • Use DeepWiki MCP for architecture analysis
  • Search related articles

Example prompts

  • “/open-source-project-article”

Workflow steps

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

  1. Fetch and read the project README.md or readme.md.
  2. Use DeepWiki MCP to analyze the repository architecture.
  3. Identify and ask necessary clarification questions, only when they materially affect article direction, audience, or output location. If…
  4. Search the web for related articles, docs, benchmarks, releases, comparisons, and case studies.
  5. Only then draft the article.

What it can do on your machine

Read from SKILL.md and the folder at commit 69fb793. 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

    No scripts in the folder and no shell commands in SKILL.md.

    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

Open Source Project Article loads about 1.3k tokens when it runs, and up to ~3.1k if it reads all its reference files. Until then it costs about 99 tokens; SKILL.md has 574 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~99
When it runs · the whole SKILL.md, loaded when a task matches
~1.3k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~3.1k

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); files beside SKILL.md are not scanned.

SKILL.md

The full file from digoal/blog at commit 69fb793, republished under its GPL-2.0 licence (© digoal). 574 words, ~1,253 tokens.

Download SKILL.mdSave it as .claude/skills/open-source-project-article/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
open-source-project-article
description
Analyze an open-source project from a repository URL and write a deeply sourced Chinese Markdown article. Use when the user asks to research a GitHub/open-source project, read its README, use DeepWiki MCP for architecture analysis, search related articles, compare competitors, validate claims, and save the final article under the current project's markdown directory.

Open Source Project Article

Use this skill to turn an open-source project URL into an evidence-grounded, article-ready Chinese Markdown file.

Non-Negotiable Source Order

Always gather evidence in this exact order:

  1. Fetch and read the project README.md or readme.md.
  2. Use DeepWiki MCP to analyze the repository architecture.
  3. Identify and ask necessary clarification questions, only when they materially affect article direction, audience, or output location. If not blocked, state assumptions and continue.
  4. Search the web for related articles, docs, benchmarks, releases, comparisons, and case studies.
  5. Only then draft the article.

Do not start with web search. Do not write from memory. Do not skip DeepWiki when the repository is supported by DeepWiki MCP.

Inputs

Require a repository URL or owner/repo. If the user omits it, ask for it.

Infer defaults unless risky:

  • Article language: Chinese.
  • Output location: markdown/ under the current project directory.
  • File name: repository name normalized to lowercase hyphen-case, e.g. pg-wait-tracer.md.
  • Article audience: DBA, architect, developer, technical decision maker.

Create markdown/ if missing.

Evidence Workflow

  1. Normalize the repository:
    • Convert GitHub URL to owner/repo.
    • Preserve the original URL for citations.
  2. Fetch README:
    • Prefer repository files or GitHub raw content.
    • Read README.md; if absent, try readme.md.
    • If README cannot be fetched, stop and report what was attempted.
  3. Ask DeepWiki:
    • Use mcp__deepwiki__read_wiki_structure first when available.
    • Use mcp__deepwiki__ask_question for architecture, core modules, data flow, extension points, tradeoffs, tests, and limitations.
    • Treat DeepWiki as architecture evidence, not as a substitute for README or code.
  4. Ask necessary questions:
    • Ask only if the answer changes the article materially, such as target audience, article style, competitor set, or whether to emphasize hands-on deployment vs strategic evaluation.
    • In default mode, avoid blocking on preferences; state reasonable assumptions and proceed.
  5. Search web:
    • Use primary sources first: official docs, repository docs, release notes, papers, benchmark reports, vendor docs.
    • Use secondary articles only to understand ecosystem interpretation or adoption cases.
    • For current project status, releases, stars, or ecosystem facts, verify live.
  6. Build an evidence pack:
    • README facts.
    • DeepWiki architecture findings.
    • Official or primary-source facts.
    • Benchmarks/data/cases with source links.
    • Competitor facts with source links.
    • Uncertainties and assumptions.
Show full SKILL.md (219 more words)Show less

Article Requirements

Read references/article-structure.md before drafting. Use it as the mandatory content checklist.

The article must include:

  • Clear thesis, not neutral feature listing.
  • Preconditions for the thesis to hold.
  • Alternative thesis or recommendation when those preconditions collapse.
  • Authoritative data or cases supporting the assumptions.
  • Authoritative data or cases supporting the thesis.
  • Background.
  • Scenario introduction.
  • Pain point analysis.
  • Sharp critique of traditional solutions.
  • Product solution.
  • Product principles and architecture.
  • Before/after effect comparison.
  • Competitor comparison.
  • Usage scenarios.
  • Best practices.
  • Hands-on steps.
  • Risks, limitations, and failure conditions.

For every major thesis, include this logic explicitly:

text
观点:...
成立前提:...
支撑证据:...
如果前提崩塌:应转向的其他观点/方案是...

Insert Mermaid or SVG diagrams at every core argument section. Prefer Mermaid unless SVG is clearly better. Diagrams must explain, not decorate.

Validation

Read references/validation-checklist.md before finalizing.

Validate:

  • Source order was followed.
  • Claims map to sources or are clearly marked as inference.
  • Data, cases, and benchmarks are quoted with context and limitations.
  • Competitor comparison is fair and sourced.
  • The article states what alternative viewpoint or product recommendation follows if core assumptions fail.
  • Hands-on commands match README/docs.
  • Mermaid syntax is plausible.
  • Output path is markdown/<slug>.md.

If validation finds weak evidence, revise the article before saving. If evidence remains unavailable, state the gap inside the article instead of inventing support.

Output

Save the article to:

text
<current-project>/markdown/<repo-slug>.md

After saving, report:

  • File path.
  • Evidence sources used.
  • Any unresolved evidence gaps.
  • Validation summary.

© digoal, GPL-2.0. 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 3 other files (references) in skills/open-source-project-article of digoal/blog.

  • SKILL.md
  • agents/openai.yaml
  • references/article-structure.md
  • references/validation-checklist.md

Open the folder on GitHubat commit 69fb793

Compare with similar skills

Open Source Project Article 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.

Open Source Project Article compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Open Source Project Article this skilldigoal/blog8.6k—~1.3kAutomated safety check: PassGPL-2.0
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Library Documentation Seekerwithkynam/vibecode-pro-max-kit1.1k2 repos~1kAutomated safety check: NotesMIT
Update .NET Supported OS Matrixdotnet/core22k—~4.1kAutomated safety check: PassMIT
README Badges and Headersjal-co/shieldcn916—~4.3kAutomated safety check: PassMIT
Githits MCPgithits-com/githits-cli114—~2kAutomated safety check: PassApache-2.0

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Questions about Open Source Project Article

What does Open Source Project Article do?

Analyze an open-source project from a repository URL and write a deeply sourced Chinese Markdown article. Open Source Project Article is an agent skill from digoal/blog. Analyze an open-source project from a repository URL and write a deeply sourced Chinese Markdown article.

When should I use Open Source Project Article?

Open Source Project Article fits situations like: the user asks to research a GitHub/open-source project; read its README; use DeepWiki MCP for architecture analysis; search related articles.

How do I install Open Source Project Article in Claude Code?

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

How do I install Open Source Project Article in Codex?

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

Can I use Open Source Project Article 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 digoal/blog --skill open-source-project-article -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/open-source-project-article, .gemini/skills/open-source-project-article, .github/skills/open-source-project-article and .opencode/skills/open-source-project-article in your project.

What does Open Source Project Article need to run?

SKILL.md names no scripts, command-line tools or credentials: Open Source Project Article is instructions for the agent only.

Does Open Source Project Article 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 Open Source Project Article 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. Review the folder before installing.

What licence does Open Source Project Article use?

Open Source Project Article is published under the GPL-2.0 licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Open Source Project Article use?

About 1.3k tokens (SKILL.md is roughly 5k 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 1.9k tokens, read only when the agent opens those files.

What are the alternatives to Open Source Project Article?

Skills that share tags, products or a category with Open Source Project Article: Markdown Without Hard Wraps (prisma/orm, 48k stars), Library Documentation Seeker (withkynam/vibecode-pro-max-kit, 1.1k stars), Update .NET Supported OS Matrix (dotnet/core, 22k stars) and README Badges and Headers (jal-co/shieldcn, 916 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Open Source Project Article?

digoal (a GitHub user) maintains it in digoal/blog, which has 8,587 GitHub stars. The repository holds 98 skills in this directory. The repository was last updated on September 28, 2026.

Source: digoal/blog on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.