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Agent Skill · 研究检索

pragmatic-docs(务实的文档)

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

pragmatic-docs 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 49,433。

总安装 652周安装 28GitHub Stars 公开资料未说明下载 228核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

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:pragmatic-docs(务实的文档)
来源仓库:https://github.com/vmvarela/skills
仓库路径:skills/pragmatic-docs
安装命令:
npx skills add https://github.com/vmvarela/skills --skill pragmatic-docs
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/vmvarela/skills --skill pragmatic-docs

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

用于辅助文档、README 和 Markdown 内容的整理与改写。适合提炼结构、统一术语或补齐章节内容。pragmatic-docs 属于研究检索类 Skill,可作为该场景下的辅助能力补充。通过 npx skills add 命令从 GitHub 安装并使用。需保留项目已有事实和路径,避免写成确定结论。

涉及对外文案时应控制语气,避免过度营销或夸大能力。

来源仓库内路径:skills/pragmatic-docs

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/vmvarela/skills --skill pragmatic-docs;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要执行命令,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

pragmatic-docs 怎么安装?

在终端执行 npx skills add https://github.com/vmvarela/skills --skill pragmatic-docs。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

pragmatic-docs 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

pragmatic-docs 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/vmvarela/skills --skill pragmatic-docs 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

pragmatic-docs 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

pragmatic-docs 用的人多吗?

公开数据是累计安装 652 次,近一周安装 28 次,下载 228 次。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

pragmatic-docs 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
pragmatic-docs

务实的文档 · 本页

652—执行命令未明确通过

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Pragmatic Documentation

Write documentation that respects the reader's time, explains *why* before *how*, uses real examples instead of abstract descriptions, and isn't afraid to have an opinion. Inspired by Philip Greenspun's approach: start with the big idea, show real code in context, acknowledge trade-offs honestly, and stop writing before the reader stops reading.

Core Principles

1. Start With Why

Every document opens with The Big Idea: what this thing is, why it exists, and what problem it solves — in 1–3 paragraphs. If you can't explain why someone should care in three paragraphs, you don't understand the project well enough.

Bad: "This module provides a flexible, extensible, enterprise-grade solution for..." Good: "Users kept asking the same five questions. This tool answers them automatically so maintainers can sleep."

2. Examples Over Abstractions

A single real example communicates more than three paragraphs of explanation. Show actual commands, real data, genuine output. Never invent foo, bar, WidgetFactory, or MyApp when you can show a concrete scenario.

Weave code into the narrative — don't banish it to a separate "Examples" ghetto. When explaining a data model, show the schema right there. When explaining a CLI, show the command and its output inline.

3. Opinions Are Valuable

Say what you think. "X is better than Y for this because..." is more useful than "X and Y are both options." Acknowledge trade-offs, recommend a path, explain your reasoning. Readers can disagree — but at least they have a position to evaluate.

4. Honest About Limitations

If something doesn't work well, say so. If there's a better tool for a specific use case, point to it. "The /news module is better if you want date-based display" is more helpful than pretending your module does everything.

5. Brevity Is Respect

A README over 300 lines is a sign that it should be split into separate docs. Don't pad with boilerplate sections. Every sentence should earn its place. If a section would be empty or contain a single trivial line — omit it.


Document Structure

Adapt this structure to context. Not every section applies to every project. Never include empty sections or sections with trivial content just to fill a template.

The Big Idea (required)

Always present. 1–3 paragraphs covering:

  • What is this?
  • Why does it exist? What problem does it solve?
  • Who is it for?

Write it so someone can read just this section and decide whether to keep reading. No jargon without immediate context. No "aims to provide" — just state what it does.

## What is this?

PhotoResize watches a directory for new images and resizes them to three
standard sizes for web delivery. We built it because our CMS required
manual image processing and editors were wasting 20 minutes per article
on something a script handles in 2 seconds.

Quick Start (when applicable)

The shortest possible path from "I found this" to "it works on my machine." Maximum 10 lines of commands. If setup genuinely requires more, the quick start shows the happy path and links to detailed installation docs.

## Quick Start

pip install photoresize
photoresize watch ./uploads --output ./public/images

Don't repeat what the package manager already tells the user. Don't list every flag. Just get them to a working state.

Under the Hood (when applicable)

How the thing works internally — but only when understanding internals actually helps the user. Architecture decisions explained narratively, not as a spec. Data models shown as actual schemas or type definitions, not UML diagrams or prose descriptions of fields.

Follow Greenspun's pattern: show the data model, then explain the interesting decisions. What constraints did you add and why? What did you choose *not* to store and why?

## Under the Hood

The core data model is simple — one table per feed source, one table
for processed items:

    create table feed_sources (
        source_id   serial primary key,
        url         text not null unique,
        check_interval_minutes  integer default 60
    );

We chose not to store the full article body because it doubles storage
without clear benefit — the original URL is always one click away.

Configuration / API (when applicable)

Only document what isn't obvious from types, signatures, or --help output. Focus on:

  • Non-obvious defaults and why they were chosen
  • Combinations of options that interact in surprising ways
  • The one config key that 90% of users will need to change

Don't reproduce your entire type system or CLI --help in Markdown. That's what --help is for.

Examples (recommended)

Real scenarios, not abstract demos. Each example should solve a problem someone actually has. Introduce each example with one sentence explaining *when* you'd use this pattern.

### Resizing for social media cards

Social platforms crop unpredictably. Force a 2:1 aspect ratio and let
the smart-crop algorithm pick the focal point:

    photoresize convert photo.jpg --aspect 2:1 --smart-crop --output card.jpg

Related Projects / Modules (when applicable)

Cross-references to alternatives or complementary tools. For each one, explain in one sentence *when* the reader should use that instead. This is not a competitors list — it's honest guidance.

## Related

- **ImageMagick** — better if you need arbitrary image transformations
  beyond resizing. We actually shell out to it under the hood.
- **sharp** — faster for Node.js projects; PhotoResize is for Python
  shops that want a CLI-first workflow.

Limitations / Future (optional)

Only if there are genuine, non-obvious limitations the user will hit. Don't include a roadmap of features you might never build.

## Limitations

- No WebP output yet (tracking in #142)
- Smart cropping works poorly on images with multiple faces

Writing Rules

Voice and Tone

  • Use active voice. "The server sends a response" not "A response is sent by the server."
  • First person is fine when sharing design rationale. "We chose X because..." or "I built this after..."
  • Write as one competent engineer explaining to another. Not as a marketing team, not as a legal department.
  • Humor and personality are welcome when they emerge naturally. Don't force it.

What to Include

  • Why decisions were made — not just what was decided.
  • Real commands, real data, real output.
  • Trade-offs — what you gave up and what you gained.
  • Cross-references as links, not as inlined content from other docs.
  • One sentence explaining each code block before showing it.

What to Omit

  • Badges beyond 2–3 genuinely useful ones (build status, version, license).
  • Table of contents for documents under 100 lines.
  • Sections that repeat information available via --help, type signatures, or JSDoc.
  • The words "aims to", "leverages", "utilizes", "facilitates", or "enterprise-grade."
  • Auto-generated API docs inlined into a README — link to them instead.
  • Empty template sections ("## Contributing", "## License" with no content).

Code in Documentation

  • Show code inline with the narrative, right after the sentence that explains it.
  • Use the actual language of the project for code blocks (not pseudocode).
  • Keep snippets short — 5–15 lines ideal. If longer, you're showing too much at once.
  • Annotate the *interesting* lines with comments. Don't comment the obvious.

Length Guidelines

DocumentTarget lengthNotes
README.md50–200 linesThe front door. Concise. Links out for details.
Module doc30–150 linesOne module = one concern = one doc.
CONTRIBUTING.md30–80 linesSetup + conventions + PR process. Nothing more.
Architecture doc100–300 linesThe Big Idea + data model + key decisions.

If a document exceeds its target, consider splitting rather than truncating. Two focused docs beat one sprawling one.


Anti-Patterns to Avoid

The Template Cemetery. A README with 15 sections, half of them containing "TODO" or a single sentence. Every section must earn its place.

The API Mirror. Documentation that reproduces every function signature and parameter type already visible in the code. Document *behavior*, *decisions*, and *gotchas* — not signatures.

The Corporate Voice. "This project aims to provide a comprehensive, scalable solution for..." — nobody talks like this. Say what the thing does.

The Completeness Trap. Trying to document every edge case and option upfront. Document the 80% path well. Let issues and discussions handle the edge cases.

The Changelog README. A README that's mostly a history of changes. That's what CHANGELOG.md and git log are for.

The Badge Wall. Twelve badges at the top of the README, half of them broken. Pick the 2–3 that genuinely help (CI status, npm version, license).


When to Apply This Skill

Use this approach when:

  • Creating a new README.md for any software project
  • Improving or rewriting existing documentation
  • Writing module-level docs in a docs/ directory
  • Creating CONTRIBUTING.md, architecture docs, or setup guides
  • Documenting a new feature, API, or service
  • Reviewing documentation for conciseness and usefulness

Adaptation by Project Type

Libraries/Packages: Lead with Quick Start (install + basic usage). The Big Idea explains *when* to reach for this library over alternatives.

CLIs: Lead with the single most common command. Show real terminal output. Document flags that aren't self-explanatory from --help.

APIs/Services: Lead with The Big Idea (what does this service do). Show a real request/response pair. Data model in Under the Hood.

Frameworks: Lead with The Big Idea (what this framework believes). Quick Start gets to "hello world." Under the Hood explains the mental model.

Internal tools: Be more honest about limitations. Your audience can't switch to a competitor — help them work around known issues.

适合场景

01

研究助手

02

事实核查

03

知识库问答

04

带来源的搜索总结

能力概览

能力 1

组合搜索和大模型调用

能力 2

支持多来源检索和总结

能力 3

强调引用来源和事实核查

能力 4

适合研究型 Agent 流程

平台分布

Codex

39.28%
按下载量换算90

Claude

28.71%
按下载量换算65

Cursor

17.35%
按下载量换算40

Gemini CLI

9.58%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/vmvarela/skills --skill pragmatic-docs 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。目前只有一个公开来源,建议同时核对源仓库。

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