file-test-bug

Creates a GitHub issue in microsoft/github-copilot-for-azure for integration test failures.

Works with

Claude CodeCursorClineWindsurfCodexGooseGitHub CopilotZed

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Install Skill

Run in your terminal

$npx skills add https://github.com/microsoft/github-copilot-for-azure --skill file-test-bug

0

installs

0

this week

180

stars

Installation Guide

How to use file-test-bug on Cursor

AI-first code editor with Composer

1

Prerequisites

Before installing skills in Cursor, ensure your development environment meets these requirements:

  • Cursor installed and configured on your machine
  • Node.js 16+ with npm — verify with node --version
  • Active project directory where you want to add file-test-bug
2

Run the install command

Execute the skills CLI command in your project's root directory to begin installation:

$npx skills add https://github.com/microsoft/github-copilot-for-azure --skill file-test-bug

Fetches file-test-bug from microsoft/github-copilot-for-azure and configures it for Cursor.

3

Select Cursor when prompted

The CLI shows a list of agents. Use arrow keys and space to select Cursor:

◆ Which agents do you want to install to?
│ ── Universal (.agents/skills) ────────────────
│ · Cline · Codex · Goose · Windsurf
│ ●Cursor(selected)
│ · Cursor · Aider · Continue
4

Verify installation

Confirm successful installation by checking the skill directory location:

.cursor/skills/file-test-bug

Restart Cursor to activate file-test-bug. Access via /file-test-bug in your agent's command palette.

Security Notice

We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.

Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.

Documentation

File Test Bug

Creates a GitHub issue in microsoft/github-copilot-for-azure for integration test failures.

Input

  • Skill name (required): e.g., azure-rbac, appinsights-instrumentation
  • Test run (optional): Timestamp of test run. Defaults to most recent with logs for the skill.

Steps

  1. Ask user for skill name if not provided
  2. Parse tests/reports/junit.xml for failures matching the skill
  3. Find test run directory (specified or most recent with matching logs)
  4. Read agent-metadata.md from tests/reports/test-run-<timestamp>/<skillname>-<testname>/
  5. For each failure, read the actual line of code from the test file using the location (file:line) from junit.xml
  6. REQUIRED - Write diagnosis BEFORE creating issue:
    • Analyze the agent-metadata.md to understand what the agent did
    • Compare agent behavior to what the test expected (from the assertion)
    • Identify the root cause (skill issue, test issue, or model behavior)
    • Write 2-3 sentences per failed test explaining WHY it failed
    • Suggest potential fixes (update skill, update test, or update fixtures)
  7. Create issue via github-mcp-server-create_issue:
owner: microsoft
repo: github-copilot-for-azure
title: Integration test failure in <skill-name>
labels: ["bug", "integration-test"]
body: |
  ## Failed Tests
  - <test-name>: <error message>
  
  ## Diagnosis
  
  ### Root Cause
  <1-2 sentences explaining WHY the test failed based on agent-metadata.md analysis>
  
  ### Analysis per Test
  - **<test-name>**: <what agent did vs what test expected>
  
  ### Suggested Fix
  <one of: update skill, update test assertions, provide test fixtures>

  ## Details
  ### <test-name>
  **Error:** <failure from junit.xml>
  **Location:** <file:line>
  ```typescript
  <actual line of code from the test file at the specified line number>

<full contents of agent-metadata.md file, verbatim>

Important

Include the complete, unmodified contents of each agent-metadata.md file in the issue body. Do NOT summarize or truncate the logs. Wrap each log in a <details> block with the test name as the summary.

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Use Cases

Task Automation & Efficiency

Automate repetitive workflows and reduce manual effort

Example

Generate reports, summarize documents, draft communications

Save 3-5 hours per week on routine tasks

Knowledge Enhancement

Learn new skills, understand complex topics, get expert guidance

Example

Explain concepts, provide examples, suggest learning resources

Accelerate learning and skill development by 2x

Quality Improvement

Enhance output quality through reviews, suggestions, and refinements

Example

Review drafts, suggest improvements, catch errors

Improve work quality by 30-40% with less effort

Implementation Guide

Prerequisites

  • Claude Desktop or compatible AI client with skill support
  • Clear understanding of task or problem to solve
  • Willingness to iterate and refine outputs

Time Estimate

15-45 minutes depending on use case complexity

Steps

  1. 1Install skill using provided installation command
  2. 2Test with simple use case relevant to your work
  3. 3Evaluate output quality and relevance
  4. 4Iterate on prompts to improve results
  5. 5Integrate into regular workflow if valuable

Common Pitfalls

  • Expecting perfect results without iteration
  • Not providing enough context in prompts
  • Using skill for tasks outside its intended scope
  • Accepting outputs without review and validation

Best Practices

✓ Do

  • +Start with clear, specific prompts
  • +Provide relevant context and constraints
  • +Review and refine all outputs before using
  • +Iterate to improve output quality
  • +Document successful prompt patterns

✗ Don't

  • Don't use without understanding skill limitations
  • Don't skip validation of outputs
  • Don't share sensitive information in prompts
  • Don't expect skill to replace human judgment

💡 Pro Tips

  • Be specific about desired format and style
  • Ask for multiple options to choose from
  • Request explanations to understand reasoning
  • Combine AI efficiency with human expertise

When to Use This

✓ Use when

Use when skill capabilities match your task, clear ROI on time saved, and you can validate outputs. Best for repetitive tasks, learning, and quality improvement.

✗ Avoid when

Avoid when task requires deep expertise you can't validate, involves sensitive decisions, or when learning process is more valuable than speed of completion.

Learning Path

  1. 1Familiarize yourself with skill capabilities and limitations
  2. 2Start with low-risk, non-critical tasks
  3. 3Progress to more complex and valuable use cases
  4. 4Build expertise through regular use and experimentation

Related Skills

Reviews

4.634 reviews
  • N
    Naina NdlovuDec 16, 2024

    Solid pick for teams standardizing on skills: file-test-bug is focused, and the summary matches what you get after install.

  • D
    Dhruvi JainDec 4, 2024

    file-test-bug is among the better-maintained entries we tried; worth keeping pinned for repeat workflows.

  • O
    OshnikdeepNov 23, 2024

    Useful defaults in file-test-bug — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • G
    Ganesh MohaneOct 14, 2024

    Registry listing for file-test-bug matched our evaluation — installs cleanly and behaves as described in the markdown.

  • M
    Min LopezSep 25, 2024

    Useful defaults in file-test-bug — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • S
    Sakshi PatilSep 21, 2024

    file-test-bug fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.

  • I
    Ishan YangSep 9, 2024

    Registry listing for file-test-bug matched our evaluation — installs cleanly and behaves as described in the markdown.

  • A
    Alexander HaddadAug 28, 2024

    Useful defaults in file-test-bug — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.

  • M
    Min FloresAug 16, 2024

    Registry listing for file-test-bug matched our evaluation — installs cleanly and behaves as described in the markdown.

  • C
    Chaitanya PatilAug 12, 2024

    file-test-bug has been reliable in day-to-day use. Documentation quality is above average for community skills.

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