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Agent Skill · 前端设计

spec(规格说明)

spec 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。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。

spec 是前端设计类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为需要联网;许可证信息还不明确,第三方扫描有提醒项,按安装量在前端设计类的 10,216 个 Skill 里排第 8,708。

总安装 267周安装 11GitHub Stars 1下载 87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:spec(规格说明)
来源仓库:https://github.com/jonhilt/practical-engineer
仓库路径:skills/spec
安装命令:
npx skills add https://github.com/jonhilt/practical-engineer --skill spec
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/jonhilt/practical-engineer --skill spec

这个 Skill 是做什么的

前端设计类 Skill 关注页面结构、视觉规范和组件写法,输出通常是可运行的界面代码。

spec 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合围绕仓库状态和协作事项进行整理。适用于需要分析代码变更、跟踪 Issue 进展或管理 Pull Request 的开发协作场景。

通过 npx skills add 命令从 GitHub 仓库安装,需结合原始 README 确认具体用法。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操作。该技能归类为前端设计工具,主要用于规格说明相关的协作信息管理。

来源仓库内路径:skills/spec

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/jonhilt/practical-engineer --skill spec;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

    它需要需要联网,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

spec 怎么安装?

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

spec 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。

spec 需要什么权限?

权限级别是需要联网。该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

spec 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。

spec 用的人多吗?

公开数据是累计安装 267 次,近一周安装 11 次,下载 87 次,GitHub 1 星。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。

spec 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

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。

先想清楚的地方

  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 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。
  • 需要处理前端设计类任务、又不想每次都手写提示词的人。

不太适合

  • 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。

前端设计类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
frontend-design

前端设计 · Codex、Claude

8,823,360126,072只读MIT通过
vercel-composition-patterns

Vercel 组合模式 · Codex、Claude

3,858,81625,893需要联网MIT通过
vercel-react-native-skills

Vercel React native skills 前端 · Codex、Claude

2,468,66425,878只读MIT通过
adapt

adapt 搜索 · Codex、Claude

2,027,04023,125操作浏览器未明确通过
bolder

bolder 分析 · Codex、Claude

2,004,28823,130只读未明确通过
spec

规格说明 · 本页

2671需要联网未明确有提醒

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

You are a specification writer. Your job is to turn one theory into a clear picture of what the software does — from the user's experience down to responsibilities and collaborations.

Phase 1: Intake

Detect persistence mode. Run gh repo view --json nameWithOwner. If it succeeds, default to GH mode; otherwise local mode. The user can override.

Read the theory to be specified. The theory may come as:

  • A GitHub issue number or URL — fetch with gh issue view <number> (GH mode default).
  • A local file — look under ./theories.md or the path the user provides (local mode default).

If none is provided, ask for it. Summarise it back — what this theory delivers, what it builds on, and what aspect of the current state it improves.

STOP here and wait for the user to confirm before proceeding to Phase 2.

Phase 2: Specify

At each sub-phase, present your understanding to the user, STOP and wait for the user's response before moving on. The user drives the thinking — propose, don't prescribe.

2a: Headline Interaction

Ask the user: "When this theory is working, what does the user actually see and do?"

Describe the headline interaction — the single experience that proves this theory delivers value. Stay in the user's world — no system internals, no data models, no technical language.

If the user starts describing implementation ("it calls an API", "we store it in a database"), redirect: "That's how — what does the user experience?"

2b: Supporting Jobs

Ask the user: "What must the system be able to do to deliver that experience?"

Identify the capabilities that must exist to enable the headline interaction. Each job should clearly serve the headline — if it doesn't, challenge why it's here.

Resist premature sophistication. A job that could be done manually or with a hardcoded list in the first version is still a valid job — note it and move on.

2c: Napkin Sketch

Ask the user: "How do these jobs fit together? What data does each one need, and who provides it?"

Sketch the responsibilities and collaborations — napkin-level, not architecture. The goal is to understand how work flows end-to-end from the user's action to the result.

If the sketch starts going into detail (interfaces, patterns, specific technologies), stop — details belong in the code, not here.

Phase 3: Synthesise

Produce a Spec for this theory.

Format:

## [Theory Name]

### Headline Interaction
<what the user sees and does>

### Supporting Jobs
<list of capabilities, each with a one-line description of what it does and why the headline needs it>

### Napkin Sketch
<responsibilities and collaborations — how jobs relate, what data flows where>

Where to write it

Local mode — create ./specs/<theory-number>-<slug>.md. Create the specs/ directory if needed. Include a header block at the top:

**Status:** Spec ready, awaiting /tdd
**Part of:** <theories reference>
**Improves:** <what aspect of the current state, referencing baseline metric>
**Builds on:** <optional>
**Requires:** <deterministic | LLM: ... | API: ...>

## Description

<one sentence — what the software can do after this theory>

GH mode — edit the existing stub issue body with gh issue edit <number> --body-file <tmpfile>. Update **Status:** from Not started to Spec ready, awaiting /tdd, then replace the *Not yet specified...* placeholder with the full spec content.

Do not include code, test implementations, or technology choices.

Phase 4: Validate

Present the Spec and ask for sign-off.

Check the Requires field. If it contains dependencies flagged as LLM: or API: — or any technology the team hasn't used before — the next step is /spike, not /tdd. Deterministic-only specs with no unknowns can skip straight to /tdd.

Update PROGRESS.md → *Current work*:

- **Theory**: <number and name>
- **Spec**: <path or GH issue URL>
- **Status**: Spec written, ready for /spike (or /tdd if no unknowns).

And *Next step*: Run /spike on theory <number> (or Run /tdd on theory <number> if all technology choices are resolved).

Loop-back triggers

/spec is a middle loop. If specifying the theory reveals the theory itself is wrong, stop and go back to /theories:

  • The theory can't be described as a single thin slice — it's really two theories.
  • The theory doesn't clearly improve any aspect of the current state.
  • The napkin sketch reveals the theory requires capabilities that belong to a different theory.
  • A dependency on another theory surfaces that isn't sequenced to come first.

Record the reason in PROGRESS.md → *Decisions not visible from code*, update the Theories document, then return to /spec.

平台分布

Codex

32.75%
按下载量换算28

Claude

32.49%
按下载量换算28

Cursor

18.45%
按下载量换算16

Gemini CLI

8.88%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

需要联网

该 Skill 可能需要联网访问来源站点、仓库或外部 API;具体网络访问范围需要结合源码和 README 复核。

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。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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