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Agent Skill · 前端设计

accelint-skill-manager(加速技能经理)

accelint-skill-manager 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。

accelint-skill-manager 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 2,216。

总安装 2,642周安装 109GitHub Stars 10下载 863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:accelint-skill-manager(加速技能经理)
来源仓库:https://github.com/gohypergiant/agent-skills
仓库路径:skills/accelint-skill-manager
安装命令:
npx skills add https://github.com/gohypergiant/agent-skills --skill accelint-skill-manager
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/gohypergiant/agent-skills --skill accelint-skill-manager

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。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息的整理与分析。适合在需要围绕仓库状态或代码变更进行协作时使用,支持多宿主环境。可结合来源仓库和原始 README 进一步核验具体用法和功能范围。安装前建议确认权限、维护状态及是否涉及联网或文件操作。

accelint-skill-manager 属于前端设计类 Skill,可作为该场景下的辅助能力补充。

来源仓库内路径:skills/accelint-skill-manager

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/gohypergiant/agent-skills --skill accelint-ski…;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

accelint-skill-manager 怎么安装?

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

accelint-skill-manager 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。

accelint-skill-manager 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。

accelint-skill-manager 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。

accelint-skill-manager 用的人多吗?

公开数据是累计安装 2,642 次,近一周安装 109 次,下载 863 次,GitHub 10 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。

accelint-skill-manager 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
accelint-skill-manager

加速技能经理 · 本页

2,64210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

Skill Manager

NEVER Do When Creating Skills

  • NEVER write tutorials explaining basics - Assume Claude knows standard concepts, libraries, and patterns. Focus on expert-only knowledge.
  • NEVER put triggering information in body - "When to use" guidance belongs ONLY in the description field. The body is loaded after activation decision.
  • NEVER dump everything in SKILL.md - Use progressive disclosure: core workflow in SKILL.md (<500 lines ideal), detailed content in references/, loaded on-demand.
  • NEVER use generic warnings - "Be careful" and "avoid errors" are useless. Provide specific anti-patterns with concrete reasons.
  • NEVER use same freedom level for all tasks - Creative domains (design, architecture) need high freedom with principles. Fragile operations (file formats, APIs) need low freedom with exact scripts.
  • NEVER explain standard operations - Assume Claude knows how to read files, write code, use common libraries. Focus on non-obvious decisions and edge cases.
  • NEVER include obvious procedures - "Step 1: Open file, Step 2: Edit, Step 3: Save" wastes tokens. Include only domain-specific workflows Claude wouldn't know.
  • NEVER skip the anti-patterns section — It's half of expert knowledge. A skill without "NEVER Do" is missing what makes it valuable: the mistakes experts learned the hard way.
  • NEVER write a vague description — "A skill for X" causes false positives and missed activations. The description must include concrete trigger phrases users actually say.
  • NEVER mix creation and audit concerns — Creating a skill, refactoring a skill, and auditing a skill are distinct workflows. Each has different inputs, outputs, and success criteria.

Before Creating a Skill, Ask

Apply these tests to ensure the skill provides genuine value:

Knowledge Delta Test

  • Does this capture what takes experts years to learn? If explaining basics or standard library usage, it's redundant.
  • Am I explaining TO Claude or arming Claude? Skills should arm agents with expert knowledge, not teach them concepts.
  • Is every paragraph earning its context space? Token economy matters - shared with system prompts, conversation history, and other skills.

Activation Economics

  • Does the description answer WHAT, WHEN, and include KEYWORDS? Vague descriptions mean the skill never gets activated.
  • Would an agent reading just the description know exactly when to use this? If unclear, the skill is invisible.

Freedom Calibration

  • What happens if the agent makes a mistake? High consequence = low freedom (exact scripts). Low consequence = high freedom (principles).
  • Is there one correct way or multiple valid approaches? One way = prescriptive. Multiple ways = guidance with examples.

Token Efficiency

  • Can this be compressed without losing expert knowledge? References loaded on-demand save context.
  • Are there repetitive procedures that could become scripts? Reusable code belongs in scripts/, not repeated in instructions.

How to Use

This skill uses progressive disclosure to minimize context usage:

1. Start with the Workflow (SKILL.md)

Follow the 4-step workflow below for skill creation or refactoring.

2. Reference Implementation Details (AGENTS.md)

Load AGENTS.md for file system conventions, naming patterns, and structural rules.

3. Load Specific References as Needed

Each workflow step below notes which reference files to load. Only load what you need for the current step:

Do NOT load all references at once — load only the ones relevant to your current step.

Which Workflow Should You Follow?

Choose based on your task:

  • Creating a new skill from scratch → Follow Skill Creation Workflow (Steps 1-4)
  • Improving an existing skill → Jump to Step 4 (Edit the Skill)
  • Auditing a skill for quality → Follow Skill Audit Workflow

Skill Creation Workflow

To create or refactor a skill, follow the "Skill Creation Workflow" in order, skipping steps only if there is a clear reason why they are not applicable.

Copy this checklist to track progress:

- [ ] Step 1: Understanding - Gather concrete examples of skill usage
- [ ] Step 2: Planning - Identify reusable scripts, references, assets
- [ ] Step 3: Initializing - Check existing skills, create directory structure
- [ ] Step 4: Editing - Write agent-focused content with procedural knowledge and update CHANGELOG

Include what rules from this skill are being applied, and why, in your summary.

Step 1: Understanding the Skill with Concrete Examples

Skip this step only when the skill's usage patterns are already clearly understood. It remains valuable even when working with an existing skill.

To create an effective skill, clearly understand concrete examples of how the skill will be used. This understanding can come from either direct user examples or generated examples that are validated with user feedback.

Example: Building an image-editor skill, ask:

  • "What functionality? Editing, rotating, other?"
  • "Usage examples?"
  • "Trigger phrases: 'Remove red-eye', 'Rotate image'—others?"

Ask 2-3 concrete questions first (functionality, examples, trigger phrases), then follow up based on their answers rather than front-loading all questions.

Conclude when there is a clear sense of the functionality the skill should support.

Step 2: Planning the Reusable Skill Contents

To turn concrete examples into an effective skill, analyze each example by:

  1. Considering how to execute on the example from scratch
  2. Identifying what scripts, references, and assets would be helpful when executing these workflows repeatedly

Examples:

  • pdf-editor skill for "Rotate this PDF" → store scripts/rotate-pdf.sh to avoid rewriting code each time
  • frontend-app-builder for "Build a todo app" → store assets/hello-world/ boilerplate template
  • big-query for "How many users logged in today?" → store references/schema.md with table schemas

Analyze each concrete example to create a list of reusable resources: scripts, references, and assets.

Step 3: Initializing the Skill

MANDATORY: Load references/file-system.md before creating directory structure.

For new skills: Copy the template in assets/skill-template/ as a starting point and customize it.

For existing skills being refactored: Skip directly to Step 4 — the skill already exists.

Before creating, check for existing skills that overlap:

ls -la .claude/skills 2>/dev/null || echo "No project skills found"
ls -la ~/.claude/skills 2>/dev/null || echo "No global skills found"

If relevant skills exist, mention them briefly: "I found [list] — should any of these be included or merged?"

Follow the conventions in AGENTS.md and reference files for directory structure and naming.

Step 4: Edit the Skill

MANDATORY: Load references/skill.md for description field conventions and frontmatter rules.

When editing the (newly-generated or existing) skill, remember that the skill is being created for another instance of an agent to use. Focus on including information that would be beneficial and non-obvious to an agent. Consider what procedural knowledge, domain-specific details, or reusable assets would help another agent instance execute these tasks more effectively.

Calibrate freedom to task fragility:

Task TypeFreedom LevelGuidance FormatExample
Creative/DesignHigh freedomPrinciples, thinking patterns, anti-patterns"Commit to a bold aesthetic"
Code ReviewMedium freedomGuidelines with examples, decision frameworks"Priority: security > logic > performance"
File OperationsLow freedomExact scripts, specific steps, no variation"Use exact command: pandoc --flag"

The test: "If the agent makes a mistake, what's the consequence?"

  • High consequence (file corruption, data loss) → Low freedom with precise scripts
  • Medium consequence (suboptimal code, style issues) → Medium freedom with examples
  • Low consequence (aesthetic choices, multiple valid approaches) → High freedom with principles

If you are updating an existing skill you can use the templates in assets/skill-template/ as a reference for larger structural changes and alignment. Consistency is imperative so lean towards aggressive reformatting to achieve adherence.

When updating an existing skill, ensure that the frontmatter metadata.version value is bumped. If the scope of the change is substantial do a major change 1.0 to 2.0, otherwise minor 1.0 to 1.1.

Version Control:

  • Major (1.0 → 2.0): Substantial rewrites, breaking changes, complete restructuring
  • Minor (1.0 → 1.1): New sections, significant additions, refinements
  • Patch (1.0.0 → 1.0.1): Bug fixes, typo corrections (optional third digit)

CHANGELOG Maintenance: After updating a skill, update or create CHANGELOG.md using "Keep a Changelog" format:

# Changelog

## [X.Y.Z] - YYYY-MM-DD

### Added
- New features/capabilities with rationale

### Changed
- Modifications with why (always include rationale)

### Fixed
- Bug fixes with explanation

### Version
- Version bump note

Document what changed and why — the rationale is critical for future maintainers. Link to evaluation results when improvements stem from testing. The CHANGELOG version must match the frontmatter metadata.version.

Skill Audit Workflow

When auditing or reviewing an existing skill (not creating from scratch), follow this structured approach:

1. Frontmatter Audit

Check each field against requirements:

  • name: lowercase, hyphens only, ≤64 chars, matches directory name
  • description: starts with "Use when", includes WHAT/WHEN/KEYWORDS, has concrete trigger phrases
  • license: present (optional but recommended)
  • metadata.version: present, meaningful, and matches CHANGELOG.md latest version

2. Structure Audit

Compare against expected sections: NEVER Do, Before [Action] Ask, How to Use, Main Workflow. Note missing sections.

3. CHANGELOG and Version Audit

Check CHANGELOG.md presence and quality:

  • Missing CHANGELOG: Flag as missing documentation
  • Version mismatch: Verify CHANGELOG latest version matches frontmatter metadata.version
  • Missing rationale: Ensure changes include WHY, not just WHAT
  • Format compliance: Check for proper "Keep a Changelog" structure
  • Empty sections: Verify Added/Changed/Fixed sections have meaningful content

4. Knowledge Delta Test

For each content block, ask: "Does Claude already know this?" Mark as REDUNDANT or EXPERT-ONLY. Calculate the percentage of redundant content. If >50% redundant, recommend substantial revision.

5. Produce Actionable Output

  • Provide specific improvement recommendations ranked by priority
  • Include a concrete improved description (not just criticism)
  • Provide an improved SKILL.md alongside the audit report

平台分布

Codex

36.44%
按下载量换算314

Claude

29.22%
按下载量换算252

Cursor

21.31%
按下载量换算184

Gemini CLI

10.27%
按下载量换算89

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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