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Agent Skill · 研究检索

gh-aw-workflow-authoring(gh aw 工作流程创作)

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。

gh-aw-workflow-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,权限为操作浏览器;许可证信息还不明确,第三方扫描有提醒项,按安装量在研究检索类的 73,675 个 Skill 里排第 65,896。

总安装 272周安装 11GitHub Stars 7下载 85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:gh-aw-workflow-authoring(gh aw 工作流程创作)
来源仓库:https://github.com/hack23/riksdagsmonitor
仓库路径:skills/gh-aw-workflow-authoring
安装命令:
npx skills add https://github.com/hack23/riksdagsmonitor --skill gh-aw-workflow-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/hack23/riksdagsmonitor --skill gh-aw-workflow-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。

gh-aw-workflow-authoring 用于辅助安全审计、权限检查和凭据风险排查。适合梳理敏感配置、分析鉴权逻辑或生成安全复核清单时使用。不能将工具输出直接当作最终结论,需人工复核关键判断。涉及密钥、令牌或生产系统时,应先确认最小权限和操作边界。使用时需对敏感数据进行脱敏处理,避免泄露真实凭证信息。

来源仓库内路径:skills/gh-aw-workflow-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/hack23/riksdagsmonitor --skill gh-aw-workflow-…;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

    它需要操作浏览器,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

gh-aw-workflow-authoring 怎么安装?

在终端执行 npx skills add https://github.com/hack23/riksdagsmonitor --skill gh-aw-workflow-authoring。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

gh-aw-workflow-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。

gh-aw-workflow-authoring 需要什么权限?

权限级别是操作浏览器。该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

gh-aw-workflow-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。

gh-aw-workflow-authoring 用的人多吗?

公开数据是累计安装 272 次,近一周安装 11 次,下载 85 次,GitHub 7 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。

gh-aw-workflow-authoring 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。
  • 需要处理研究检索类任务、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。

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
gh-aw-workflow-authoring

gh aw 工作流程创作 · 本页

2727操作浏览器未明确有提醒

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

✍️ GitHub Agentic Workflows - Workflow Authoring Skill

📋 Purpose

Master the art of authoring GitHub Agentic Workflows - creating AI-powered automation using natural language markdown instead of complex YAML. This skill provides comprehensive expertise in workflow design, natural language instructions, configuration, and best practices for effective agentic automation.

🎯 Core Concepts

What Makes Agentic Workflows Different?

Traditional GitHub Actions:

# Complex conditional logic
if: |
  contains(github.event.issue.labels.*.name, 'bug') &&
  !contains(github.event.issue.labels.*.name, 'wontfix') &&
  github.event.issue.state == 'open'
run: echo "Process bug"

Agentic Workflow:

If this is an open bug that should be fixed, provide helpful triage information.

Key Differences:

Traditional ActionsAgentic Workflows
✅ Deterministic🤖 AI-driven decisions
⚙️ Complex YAML📝 Natural language
🔧 Fixed logic paths🧠 Context-aware responses
📊 Explicit conditionals💡 Inferred intent

🏗️ Workflow Structure

File Anatomy

.github/
├── workflows/
│   ├── issue-triage.md          # Source (human-authored)
│   └── issue-triage.lock.yml    # Compiled (generated)

Workflow File Structure:

---
# YAML Frontmatter - Configuration
on: issues
permissions: read-all
tools:
  github:
    toolsets: [issues]
  safeoutputs___comment:
engine: copilot
---

# Markdown Body - Natural Language Instructions

Analyze this issue and provide helpful triage information.

Consider:
- Issue content and context
- Related issues and PRs
- Historical patterns
- Repository conventions

Provide actionable recommendations.

YAML Frontmatter

Required Fields:

on: issues              # Trigger event
permissions: read-all   # Security permissions
tools:                  # Available tools
  github:
engine: copilot         # AI engine

Optional Fields:

name: "Issue Triage"    # Workflow name
description: "Automated issue analysis"
timeout-minutes: 10     # Execution timeout
concurrency:            # Concurrency control
  group: ${{ github.ref }}
  cancel-in-progress: true

🛠️ Tools Configuration

GitHub Tools

Repository Operations:

tools:
  github:
    toolsets:
      - repos         # File operations
      - issues        # Issue management
      - pull_requests # PR operations
      - projects      # GitHub Projects

Examples:

---
tools:
  github:
    toolsets: [repos]
---

Review the repository structure and suggest improvements.

Safe Outputs

Write Operations:

tools:
  safeoutputs___issue:       # Create/update issues
  safeoutputs___pull_request: # Create PRs
  safeoutputs___comment:      # Add comments
  safeoutputs___file:         # Modify files
    allowed_paths:
      - "docs/**/*.md"
  safeoutputs___label:        # Manage labels
  safeoutputs___noop:         # Read-only mode

Example:

---
tools:
  safeoutputs___comment:
  safeoutputs___label:
---

Analyze this issue, add appropriate labels, and provide feedback.

File Operations

tools:
  edit:     # Edit existing files
  view:     # Read file contents
  create:   # Create new files

Shell Commands

tools:
  bash:
    allowed-commands:
      - npm
      - git
      - python3

Security Note: Be restrictive with shell access.

Web Access

tools:
  web-fetch:   # Fetch URLs
  web-search:  # Search the web

Browser Automation

tools:
  playwright:
    headless: true

Custom MCP Servers

tools:
  custom-mcp:
    url: https://your-mcp-server.com
    headers:
      Authorization: ${{ secrets.API_TOKEN }}

📝 Natural Language Instructions

Writing Effective Prompts

1. Be Specific and Clear:

❌ Bad:

Do something with this issue.

✅ Good:

Analyze this issue and:
1. Determine if it's a bug, feature request, or question
2. Check for duplicates in existing issues
3. Suggest appropriate labels
4. Add a helpful comment with next steps

2. Provide Context:

❌ Bad:

Fix the code.

✅ Good:

Review the changed files in this PR and:
- Check for common security issues (SQL injection, XSS)
- Verify error handling is comprehensive
- Ensure tests cover new functionality
- Suggest improvements following our style guide

3. Structure with Lists:

Perform code review with focus on:

**Security:**
- Input validation
- Authentication checks
- Data sanitization

**Quality:**
- Code duplication
- Function complexity
- Test coverage

**Documentation:**
- API documentation
- Inline comments
- README updates

4. Use Examples:

Analyze this pull request and provide feedback similar to:

"## Code Review

### Security Concerns
- Line 45: User input not validated

### Performance
- Line 78: Consider caching this result

### Style
- Follows project conventions ✓"

Prompt Engineering Patterns

Pattern 1: Analyze → Decide → Act

1. Analyze the issue description and comments
2. Decide if it's a duplicate or new issue
3. If duplicate: Close with reference to original
4. If new: Add labels and assign to appropriate team

Pattern 2: Conditional Instructions

If this is a security issue:
- Add 'security' label
- Mark as high priority
- Notify security team

If this is a feature request:
- Add 'enhancement' label
- Ask for use case details
- Add to product backlog

Pattern 3: Multi-Step Workflow

Step 1: Review all changed files
Step 2: Identify potential issues
Step 3: For each issue found:
  - Note the file and line number
  - Explain the problem
  - Suggest a solution
Step 4: Summarize findings in a comment

🎯 Workflow Examples

Example 1: Issue Triage

---
name: "Issue Triage"
on: issues
permissions: read-all

tools:
  github:
    toolsets: [issues]
  safeoutputs___label:
  safeoutputs___comment:
---

# Automated Issue Triage

Analyze this new issue and provide comprehensive triage:

## Classification
Determine if this is:
- 🐛 **Bug**: Something isn't working
- ✨ **Feature**: New functionality request
- ❓ **Question**: Help or clarification needed
- 📚 **Documentation**: Documentation improvement

## Duplicate Check
Search for similar issues using keywords from the title and description.
If a duplicate is found, note the issue number.

## Priority Assessment
Based on:
- Impact (how many users affected)
- Severity (how critical)
- Workaround availability

Suggest priority: high, medium, or low

## Actions
Using safeoutputs___label, add appropriate labels:
- Type: bug/feature/question/docs
- Priority: high/medium/low
- Component: affected area

Using safeoutputs___comment, provide:
- Classification explanation
- Duplicate status (if any)
- Recommended priority with reasoning
- Suggested assignee or team
- Next steps for the reporter

Example 2: PR Code Review

---
name: "Code Review Assistant"
on: pull_request
permissions: read-all

tools:
  github:
    toolsets: [pull_requests, repos]
  bash:
    allowed-commands: [git, npm]
  safeoutputs___comment:
---

# Automated Code Review

Perform a comprehensive code review of this pull request:

## Files Changed
Review each changed file for:

### Security
- Input validation
- SQL injection risks
- XSS vulnerabilities
- Authentication/authorization
- Sensitive data exposure

### Code Quality
- Function complexity
- Code duplication
- Error handling
- Edge cases

### Testing
- Test coverage
- Test quality
- Missing test cases

### Performance
- Inefficient algorithms
- Memory leaks
- Database query optimization

### Style
- Follows project conventions
- Naming consistency
- Documentation completeness

## Summary
Provide:
- Overall assessment (approve/needs work/concerns)
- Count of issues by severity
- Most critical items to address
- Positive feedback on good practices

Use safeoutputs___comment to post the review.

Example 3: Documentation Updates

---
name: "Documentation Sync"
on: push
paths:
  - 'src/**/*.ts'

permissions: read-all

tools:
  github:
    toolsets: [repos]
  bash:
    allowed-commands: [git]
  safeoutputs___file:
    allowed_paths:
      - "docs/**/*.md"
      - "README.md"
---

# Keep Documentation Current

When code changes, ensure documentation stays synchronized:

## Changed Files Analysis
1. Identify which source files changed
2. Determine if they have corresponding documentation
3. Review the nature of changes (new features, API changes, deprecations)

## Documentation Updates
For each relevant change:

### API Documentation
- Update function signatures
- Add new method documentation
- Mark deprecated features
- Update examples

### README
- Add new feature descriptions
- Update installation if needed
- Refresh examples
- Update version compatibility

### Changelog
- Add entry for this change
- Include breaking changes prominently
- Link to PR/issue

## Implementation
Use safeoutputs___file to update documentation files.
Ensure:
- Examples are tested and work
- Links are valid
- Formatting is consistent
- Version numbers are current

Example 4: Dependency Management

---
name: "Dependency Update Review"
on: pull_request
paths:
  - 'package.json'
  - 'package-lock.json'

permissions: read-all

tools:
  github:
    toolsets: [pull_requests]
  bash:
    allowed-commands: [npm]
  web-fetch:
  safeoutputs___comment:
---

# Dependency Update Analysis

When dependencies are updated, provide security and compatibility review:

## Changed Dependencies
Identify all dependency changes:
- New dependencies added
- Updated versions
- Removed dependencies

## Security Check
For each changed dependency:
1. Check npm audit for known vulnerabilities
2. Review GitHub advisory database
3. Check Snyk or similar databases
4. Note any security warnings

## Compatibility Check
- Review changelog for breaking changes
- Check if major version bump
- Verify Node.js version compatibility
- Check for deprecated features used

## License Check
- Verify license compatibility
- Flag any license changes
- Note GPL or other copyleft licenses

## Recommendation
Provide:
- ✅ Safe to merge
- ⚠️ Review required
- ❌ Security concerns

Include:
- Specific issues found
- Recommended actions
- Links to relevant documentation

Use safeoutputs___comment to post the analysis.

Example 5: Scheduled Maintenance

---
name: "Weekly Repository Health Check"
on:
  schedule:
    - cron: '0 0 * * 0'  # Every Sunday

permissions: read-all

tools:
  github:
    toolsets: [issues, pull_requests, repos]
  safeoutputs___issue:
---

# Weekly Repository Health Report

Generate a comprehensive repository health report:

## Open Issues Analysis
- Total open issues
- Issues by label
- Stale issues (30+ days)
- High priority unassigned
- Trends (increasing/decreasing)

## Pull Requests Review
- Open PRs count
- Average PR age
- PRs awaiting review
- Stale PRs (14+ days)
- Merge rate trend

## Code Quality Metrics
- Test coverage
- Recent build failures
- Security vulnerabilities
- Dependency updates needed

## Community Health
- New contributors this week
- First-time contributors
- Response times
- Merge frequency

## Recommendations
Based on the analysis:
1. Issues to prioritize
2. PRs needing attention
3. Maintenance tasks
4. Community engagement opportunities

Use safeoutputs___issue to create:
- Weekly health report issue
- Label it 'maintenance' and 'automated'
- Assign to repository maintainers

⚙️ Advanced Configuration

Concurrency Control

---
on: issues

concurrency:
  group: issue-${{ github.event.issue.number }}
  cancel-in-progress: true
---

Use Cases:

  • Prevent duplicate processing
  • Cancel outdated runs
  • Resource management

Conditional Execution

---
on: pull_request

if: |
  github.event.pull_request.draft == false &&
  !contains(github.event.pull_request.labels.*.name, 'skip-review')
---

Timeouts

---
timeout-minutes: 5  # Cancel if exceeds 5 minutes
---

Environment Variables

---
env:
  NODE_VERSION: '24'
  DEBUG: 'true'
---

🔄 Compilation Process

Manual Compilation

# Install compiler
npm install -g @github/agentic-workflows-compiler

# Compile workflow
aw-compile .github/workflows/issue-triage.md

# Output: .github/workflows/issue-triage.lock.yml

Automatic Compilation

GitHub Actions:

name: Compile Agentic Workflows

on:
  pull_request:
    paths:
      - '.github/workflows/*.md'

jobs:
  compile:
    runs-on: ubuntu-latest
    steps:
      - uses: actions/checkout@v4

      - name: Compile Workflows
        run: |
          npm install -g @github/agentic-workflows-compiler
          aw-compile .github/workflows/*.md

      - name: Commit Compiled Files
        run: |
          git add .github/workflows/*.lock.yml
          git commit -m "Compile agentic workflows"
          git push

Validation

# Validate syntax
aw-validate .github/workflows/issue-triage.md

# Check for common issues
aw-lint .github/workflows/issue-triage.md

🎨 Best Practices

1. Single Responsibility

❌ Bad: Multiple tasks in one workflow

Triage issues, review PRs, update documentation, and manage dependencies.

✅ Good: Focused workflow

Triage new issues by analyzing content, checking for duplicates, and applying appropriate labels.

2. Clear Success Criteria

❌ Bad: Vague instructions

Make this better.

✅ Good: Specific criteria

Improve this code by:
- Reducing cyclomatic complexity to <10
- Adding error handling for edge cases
- Including unit tests with 80%+ coverage

3. Tool Minimalism

❌ Bad: Grant all tools

tools:
  github:
    toolsets: ['*']
  bash:
  safeoutputs___*:

✅ Good: Only required tools

tools:
  github:
    toolsets: [issues]
  safeoutputs___comment:

4. Error Guidance

If you encounter issues:
1. Check for existing similar issues first
2. If API rate limit reached, note it and suggest trying later
3. If insufficient permissions, explain what's needed
4. Always provide fallback recommendations

5. Testing Instructions

Before implementation:
1. Validate file paths exist
2. Check for required permissions
3. Verify tool availability
4. Test with dry-run if possible

Use safeoutputs___noop to report findings if validation fails.

🚨 Common Pitfalls

Pitfall 1: Overly Complex Instructions

❌ Don't:

Analyze code considering 27 different quality metrics, cross-reference with 15 different documentation sources, generate detailed reports with statistical analysis, create visualization dashboards, and...

✅ Do:

Focus on 3 key areas:
1. Security vulnerabilities
2. Test coverage
3. Code complexity

Provide actionable feedback for each.

Pitfall 2: Assuming Tool Availability

❌ Don't:

Use bash to run npm install...

✅ Do:

---
tools:
  bash:
    allowed-commands: [npm]
---

If npm is available, run npm install to verify dependencies.

Pitfall 3: Ignoring Rate Limits

❌ Don't:

Search all 10,000 issues for duplicates.

✅ Do:

Search recent issues (last 90 days) for duplicates.
If none found, note that older issues weren't checked due to performance.

Pitfall 4: Not Handling Failures

❌ Don't:

Update the file with new content.

✅ Do:

Attempt to update the file.
If it fails (permissions, file doesn't exist, etc.):
- Use safeoutputs___noop to explain the issue
- Suggest manual resolution steps

🔗 Related Skills

  • gh-aw-safe-outputs - Understanding write operations
  • gh-aw-tools-ecosystem - Available tools and capabilities
  • gh-aw-mcp-gateway - MCP server integration
  • gh-aw-continuous-ai-patterns - Workflow patterns and strategies
  • gh-aw-github-actions-integration - Deployment and CI/CD

📚 References

✅ Remember

  • ✅ Write in natural language, not code
  • ✅ Be specific and provide context
  • ✅ Use tool minimalism (least privilege)
  • ✅ Structure with clear sections
  • ✅ Provide examples in instructions
  • ✅ Handle errors gracefully
  • ✅ Test before deploying
  • ✅ Focus on single responsibility
  • ✅ Compile generates.lock.yml
  • ✅ Natural language beats complex YAML

Version: 1.0.0 Last Updated: 2026-02-17 Maintained by: Hack23 AB

平台分布

Codex

35.25%
按下载量换算30

Claude

32.89%
按下载量换算28

Cursor

17.73%
按下载量换算15

Gemini CLI

9.01%
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

操作浏览器

该 Skill 可能涉及浏览器控制能力,使用时可能读取或操作网页内容,需要在受控环境中确认权限边界。

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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