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Agent Skill · 前端设计

spec-builder(规格构建者)

spec-builder 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-builder 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,第三方扫描已通过,按安装量在前端设计类的 10,216 个 Skill 里排第 6,126。

总安装 549周安装 22GitHub Stars 公开资料未说明下载 178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-builder(规格构建者)
来源仓库:https://github.com/ilamanov/skills
仓库路径:skills/spec-builder
安装命令:
npx skills add https://github.com/ilamanov/skills --skill spec-builder
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/ilamanov/skills --skill spec-builder

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-builder 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 中围绕仓库状态、代码变更或协作事项进行整理。可通过 npx skills add 命令从指定仓库安装并使用该技能。

安装前建议确认权限范围、维护状态,以及是否会触发联网或文件读写操作。可结合来源仓库和原始 README 进一步核验具体用法和功能边界。

来源仓库内路径:skills/spec-builder

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/ilamanov/skills --skill spec-builder;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-builder 怎么安装?

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

spec-builder 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-builder 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-builder 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-builder 用的人多吗?

公开数据是累计安装 549 次,近一周安装 22 次,下载 178 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。

spec-builder 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

  • 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-builder

规格构建者 · 本页

549—需要联网未明确通过

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

Spec Builder

Transform vague ideas into concrete, actionable spec documents through structured interviews.

Workflow

Phase 1: Gather Initial Context

First, prompt for the idea:

What's the idea you'd like to turn into a spec?
Describe it however it exists in your head right now - it can be vague.

Then ask background questions to calibrate the interview depth:

AskUserQuestion:
1. "What's your background?"
   - Technical (developer/engineer)
   - Semi-technical (PM, designer, technical founder)
   - Non-technical (business, creative, general user)

2. "What's the goal for this spec?"
   - MVP/prototype to test the idea
   - Full product spec for development
   - Implementation plan for an AI coding agent
   - Pitch document for stakeholders
   - Personal reference to clarify my thinking

Phase 2: Deep Interview

Conduct the interview using AskUserQuestion with batched questions (2-4 related questions per batch).

Rules:

  • Never assume - if something is ambiguous, ask
  • Provide sensible default options for every question
  • Add "(Recommended)" to the best default option
  • Anticipate needs the user hasn't considered
  • Adapt question depth based on user's technical level

Question calibration by user background:

TopicTechnical UserNon-Technical User
Architecture"REST vs GraphQL vs tRPC?"Skip - decide yourself
Data storage"SQL vs NoSQL? Which DB?""Does it need to remember data between sessions?"
UI framework"React, Vue, or Svelte?"Skip - decide yourself
Hosting"Serverless, containers, or VMs?"Skip - decide yourself
Auth"OAuth, magic links, or password?""How should users log in?" (plain language options)
Scale"Expected concurrent users?""How many people might use this at once?"

Prioritize load-bearing decisions:

Not all decisions carry equal weight. Some are cheap to revisit later; others are foundational — they shape the core architecture, UX, or physical design and are expensive or painful to redo. The interview must identify which decisions are load-bearing for *this specific product*, surface them, and get explicit user approval before moving on. This applies to all product types.

The test: "If we change this after launch/production, does it require significant rework, data migration, retooling, or redesign?" If yes, it's load-bearing and must be discussed upfront. If not, it can be iterated on later and doesn't need deep interview time.

What counts as load-bearing varies by product. A few examples to calibrate your judgment:

  • Storage & data architecture (software) — where content lives, when uploads happen, what's the source of truth
  • Async processing patterns (software) — how long-running operations are tracked, who polls, how progress is communicated
  • Concurrency model (software) — whether the system is designed for parallel workloads from the start, since retrofitting this is a rewrite
  • Core mechanism & form factor (hardware) — how the thing fundamentally works, its dimensions, power source
  • Manufacturing process & materials (hardware) — injection molding vs CNC vs 3D print changes cost, tolerances, and lead times
  • Regulatory & certification requirements (hardware) — designing for compliance after the fact means costly redesigns
  • UI/UX model (any) — sometimes trivial to change (colors, copy), sometimes load-bearing (e.g., a real-time collaborative interface vs. async workflow, or a feed-based layout that the entire data model is built around)
  • Third-party dependencies (any) — switching providers often means rewriting integrations and handling different data formats
  • Auth & identity model (software/services) — migrating users between auth systems is extremely disruptive

These are examples, not a checklist. For each product, think from first principles about what's "poured in concrete" vs. "rearranging furniture," and focus the interview accordingly.

For technical users, ask about load-bearing decisions directly. For non-technical users, simplify the concept but still get their approval — e.g., instead of "Should the frontend poll via request IDs or use server-sent events?", ask "When a generation takes 30 seconds, should the user see a live progress update or just get notified when it's done?"

Spend interview time proportionally to how hard a decision is to reverse. Don't deep-dive on aspects that are trivially changeable for this product unless the user raises them.

Interview domains to cover (adapt based on product type):

For software products:

  • Core functionality (what does it do?)
  • User types and permissions
  • Key user flows (step by step)
  • Data model (what entities exist, how they relate)
  • Integrations (external services, APIs, fallback strategies)
  • Edge cases and error handling
  • Security and privacy requirements
  • Platform (web, mobile, desktop, CLI)

For physical products:

  • Core functionality
  • User interaction (how do you use it?)
  • Manufacturing considerations
  • Safety requirements
  • Packaging and delivery

For all products:

  • Load-bearing decisions identified for this specific product (see above)

For all products:

  • Success criteria (how do we know it works?)
  • Constraints (budget, timeline, must-haves)
  • Anti-goals (what it explicitly should NOT do)

Example batched question:

AskUserQuestion (batch):
1. "Who are the main users of this product?"
   - Single user type (just me / general public)
   - Two distinct roles (e.g., admin + regular user)
   - Multiple user types (need to define each)

2. "Do users need accounts?"
   - No accounts needed (Recommended for MVP)
   - Simple accounts (email/password)
   - Social login (Google, GitHub, etc.)
   - Enterprise SSO

Phase 3: Draft Review

After covering core questions (~10-15 batches), present a draft outline:

Here's the spec outline based on our conversation so far:

## [Product Name] - Spec Outline

**Overview:** [1-2 sentences]

**Core Features:**
1. [Feature A]
2. [Feature B]
...

**User Types:** [list]

**Key Flows:** [list main workflows]

**Technical Approach:** [high-level decisions]

**Open Questions:** [things still unclear]

---

Does this capture your vision? What's missing or wrong?

Then use AskUserQuestion to get feedback:

1. "How does this outline look?"
   - Looks good, continue with details
   - Missing something important (I'll explain)
   - Some parts are wrong (I'll clarify)
   - Let's pivot direction

Phase 4: Deep Dive

Based on feedback, ask detailed follow-up questions on:

  • Unclear areas from the outline
  • Edge cases and error states
  • Specific UI/UX details
  • Technical constraints
  • Anything marked as "Open Questions"

Continue until confident all ambiguity is resolved.

Phase 5: Write Spec

Write the final spec to spec-<product-name>.md in the current directory.

Spec format principles:

  • Detailed enough for an AI coding agent to implement
  • Skimmable for human review (use headers, bullets, tables)
  • No vague language - every requirement must be concrete
  • Include explicit anti-goals and out-of-scope items
  • Write as a standalone document - never mention the interview process or reference "our conversation"

Spec structure (adapt sections based on product type):

# [Product Name] Spec

## Overview

[2-3 sentences: what it is, who it's for, core value prop]

## Goals & Non-Goals

### Goals

- [Concrete goal 1]
- [Concrete goal 2]

### Non-Goals (explicitly out of scope)

- [What this product will NOT do]

## User Types

[Table or list of user types and their permissions/capabilities]

## Core Features

### Feature 1: [Name]

**Purpose:** [Why this feature exists]
**Behavior:**

- [Specific behavior 1]
- [Specific behavior 2]
  **UI:** [Description or wireframe reference]

[Repeat for each feature]

## User Flows

### Flow 1: [Name]

1. User does X
2. System responds with Y
3. User sees Z
   ...

[Repeat for key flows]

## Data Model

[Tables, entities, relationships - for software]
[Components, materials - for physical products]

## Technical Decisions

[Architecture choices, technologies, integrations]
[Explicitly document every load-bearing decision (storage, async patterns, concurrency, etc.) and note that it was discussed and approved during the interview]
[For non-technical users, describe these in plain language; for physical products, skip]

## Edge Cases & Error Handling

- When X happens, the system should Y
- If Z fails, show error message: "..."

## Open Questions

[Anything that still needs resolution before building]

## Future Considerations

[Ideas mentioned but explicitly deferred]

Key Principles

  1. Load-bearing decisions first - Identify and resolve architectural decisions that are hard to undo before spending time on details that are easy to change later. The interview's primary job is to surface these and get explicit approval.
  2. Be thorough - Ask many questions. 10-20 batches is normal for a complex product.
  3. Never assume - If two interpretations are possible, ask which one.
  4. Provide defaults - Every question should have reasonable options with a recommended choice.
  5. Adapt depth - Technical users get technical questions; non-technical users get plain language. But even non-technical users must approve load-bearing decisions — just explain them simply.
  6. Surface unknowns - Ask about things the user probably hasn't considered yet.
  7. Stay concrete - The final spec should have zero vague requirements.

Self-Note

Before finalizing the spec, ask yourself:

  • "What are the load-bearing decisions I haven't surfaced yet? Is there anything in this spec that would be painful to change once built — and that I haven't explicitly confirmed with the user?"
  • "What are the edge cases I didn't consider?"

平台分布

Codex

37.84%
按下载量换算67

Claude

28.05%
按下载量换算50

Cursor

18.65%
按下载量换算33

Gemini CLI

8.63%
按下载量换算15

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

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。目前只有一个公开来源,建议同时核对源仓库。

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