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Agent Skill · 研究检索

skill-authoring(技能创作)

用于辅助安全审计、权限检查、凭据风险、认证流程和常见漏洞排查。它适合让 Agent 梳理敏感配置、检查依赖风险、分析鉴权逻辑或生成安全复核清单。使用时不能把工具输出直接当最终结论,涉及密钥、令牌、用户数据或生产系统时,应先确认最小权限、脱敏方式和操作边界。

skill-authoring 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,权限为接触敏感数据;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 71,089。

总安装 196周安装 8GitHub Stars 公开资料未说明下载 63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:skill-authoring(技能创作)
来源仓库:https://github.com/contextware/skills
仓库路径:skills/skill-authoring
安装命令:
npx skills add https://github.com/contextware/skills --skill skill-authoring
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/contextware/skills --skill skill-authoring

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。

skill-authoring 协助创建跨平台、无感知于特定 Agent 的技能模板。适用于自定义工具封装与标准化输出格式设计,提升技能可维护性。要求遵循 SKILL_AUTHORING.md 规范,明确输入输出与脚本职责划分。发布前应严格审查敏感信息暴露风险,避免凭据硬编码或越权操作。

适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

来源仓库内路径:skills/skill-authoring

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/contextware/skills --skill skill-authoring;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

    它需要接触敏感数据,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

skill-authoring 怎么安装?

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

skill-authoring 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。

skill-authoring 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

skill-authoring 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。

skill-authoring 用的人多吗?

公开数据是累计安装 196 次,近一周安装 8 次,下载 63 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。

skill-authoring 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

  • 需要接触敏感数据,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

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 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
skill-authoring

技能创作 · 本页

196—接触敏感数据未明确通过

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 Authoring Skill

This skill helps you author new skills that are cross-platform and agent-agnostic. Use this when creating or reviewing skill definitions.

Prerequisites

Required Reading: Review the SKILL_AUTHORING.md guidelines for comprehensive authoring practices.

Workflow

Phase 1: Understand the Goal

Before writing a skill, clarify:

  1. What capability does this skill provide?
  2. What prerequisites are needed (env vars, runtime, MCP servers)?
  3. What scripts are needed to perform the work?
  4. What output should the agent produce?

Phase 2: Create the SKILL.md Structure

Every skill needs a SKILL.md file with frontmatter:

---
name: skill-name
description: Brief description
version: 1.0.0
mcp-servers: ["server-name"]  # Required MCP servers, use [] if none needed
allowed-tools: [tool1, tool2] # Tools the skill uses, enables lazy loading
tags: [category, ...]
---
[!IMPORTANT] Always specify mcp-servers and allowed-tools! - If your skill needs NO MCP servers, use mcp-servers: [] - If your skill only needs specific tools, list them in allowed-tools Without these fields, the agent falls into "Legacy Mode" which connects to ALL MCP servers, wasting resources and causing unnecessary connection errors.

Phase 3: Write the Workflow

Use these core principles:

  1. Describe WHAT, not HOW - Say what needs to happen, not tool-specific syntax
  2. Use natural language - Any agent should be able to read and follow
  3. Bundle self-contained scripts - No external dependencies
  4. Declare requirements - Use frontmatter for machine-readable deps
  5. Provide platform hints - But as suggestions, not requirements
  6. Include reference MCP server URLs - So agents without their own server can still proceed (see below)

Phase 4: Create Bundled Scripts

Place scripts in the scripts/ subdirectory. Scripts should:

  • Use only built-in runtime features (Node.js fetch, fs, path)
  • Accept input via command-line arguments and environment variables
  • Output JSON to stdout
  • Use proper exit codes (0 = success, 1 = error)

Phase 5: Add Platform Adaptation Notes

If your skill has platform-specific considerations (like MCP configuration), add a section:

## Platform Adaptation Notes

### Dynamic MCP Support
For agents that can add MCP servers during a session...

### Static MCP Configuration
For agents requiring config file + restart...

Phase 6: Document MCP Server URLs for Portability

Skills that depend on MCP servers must help other agents find and connect to the right server. The agent consuming your skill may not have the same MCP servers configured locally.

The pattern: Describe what capabilities are needed, list the required tools, and provide a reference MCP server URL as a working default. Be permissive — let the consuming agent decide whether to use its own local server or the reference one.

When writing the MCP Server Requirements section of your skill, use this pattern:

## MCP Server Requirements

This skill requires an MCP server that provides **[capability description]** (e.g., incident management, CRM integration).

**Required tools:** `toolA`, `toolB`, `toolC`

**Reference MCP Server:**
If you do not already have a locally configured MCP server that provides these tools, you can use the following reference endpoint:
- Transport: HTTP
- URL: `https://<server-name>.mcpgateway.online/mcp`

If you have your own MCP server that provides equivalent functionality, use that instead.

Why this matters: Without a reference URL, agents that don't have the server configured locally will stall — they have no way to proceed. With a reference URL, any agent can pick up the skill and start working immediately.

Key principles:

  • Be permissive: Don't insist agents use the reference URL. If they have a local match, that's fine.
  • Don't be directive: Don't tell agents they "must find their own server URL first" — this causes them to pick the wrong server or get stuck searching.
  • Describe capability, not identity: Focus on what tools are needed, not a specific server name. This allows agents to match against their own servers by capability.

Patterns to Avoid

❌ Avoid✅ Use Instead
create_sandbox({skillId: "..."})"Run the bundled script"
jq '.mcpServers =...' ~/.claude.json"Add to your MCP configuration"
Specific config file paths"Update your agent's MCP settings"
Tool-specific syntaxNatural language descriptions

Patterns to Use

PatternExample
Script execution"Run scripts/check-auth.js hubspot"
JSON contracts"The script outputs JSON with {status, data}"
Declarative MCP"Requires the 'nango' MCP server (HTTP transport)"
Capability hints"For agents with dynamic MCP support..."
User-blocking actions"Present the auth URL, then STOP AND WAIT for user confirmation"
Reference MCP URLs"If you don't have a local server with these tools, use this reference endpoint:..."
TMF Field Mapping"Use atType instead of @type for TMF OpenAPI fields"
[!TIP] TMF Standards Special Handling: For any skill related to TMF standards, always include advice that field names starting with @ (e.g., @type, @schemaLocation) are mapped to an at prefix (e.g., atType, atSchemaLocation) in the MCP middleware to ensure compatibility with AI agents.

Example: Good vs Bad

❌ Bad (Platform-Specific)

Create a Vercel sandbox using create_sandbox tool, then run:
run_command({ command: "node", args: ["scripts/auth.js"] })

✅ Good (Portable)

Run the bundled `scripts/auth.js` script with the provider name.
The script outputs JSON indicating authentication status.

Checklist Before Publishing

  • mcp-servers specified (use [] if none needed)
  • allowed-tools specified (enables lazy loading)
  • No platform-specific tool syntax in SKILL.md
  • No hardcoded config file paths
  • Scripts use only standard runtime features
  • MCP requirements documented declaratively with reference URL
  • Natural language workflow descriptions
  • Platform Adaptation Notes included (if applicable)
  • User-blocking actions have explicit STOP AND WAIT instructions
  • Tested on at least one agent platform

Resources

平台分布

Codex

38.29%
按下载量换算24

Claude

28.84%
按下载量换算18

Cursor

18%
按下载量换算11

Gemini CLI

9.54%
按下载量换算6

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

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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