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debug-failing-test Skill

AI Agent SkillTypeScriptOpen source

Debug a failing test using an iterative logging approach, then clean up and document the learning. Published by microsoft in vscode-python-environments.

What is debug-failing-test Skill?

Debug a failing test using an iterative logging approach, then clean up and document the learning. Published by microsoft in vscode-python-environments. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
53/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Testing
  • Testing use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use debug-failing-test Skill

  • Use it for testing.

Built with

TypeScriptCopy skill directory

Editorial notes

Source

  • Creator: microsoft
  • Repository: microsoft/vscode-python-environments
  • Skill file: .github/skills/debug-failing-test/SKILL.md

What it does

Debug a failing test using an iterative logging approach, then clean up and document the learning.

Skill instructions

Debug a failing unit test by iteratively adding verbose logging, running the test, and analyzing the output until the root cause is found and fixed. Workflow Phase 1: Initial Assessment 1. Run the failing test to capture the current error message and stack trace 2. Read the test file to understand what is being tested 3. Read the source file being tested to understand the expected behavior 4. Identify the assertion that fails and what values are involved Phase 2: Iterative Debugging Loop Repeat until the root cause is understood: 1. Add verbose logging around the suspicious code: - Use console.log('[DEBUG]', ...) with descriptive labels - Log input values, intermediate states, and return values - Log before/after key operations - Add timestamps if timing might be relevant 2. Run the test and capture output 3. Assess the logging output: - What values are unexpected? - Where does the behavior diverge from expectations? - What additional logging would help narrow down the issue? 4. Decide

Explore related resources

Frequently asked questions

What is debug-failing-test?

debug-failing-test is a open-source AI agent skill with Copy skill directory. Debug a failing test using an iterative logging approach, then clean up and document the learning.

Who is debug-failing-test best for?

debug-failing-test is best for reusing agent instructions, scripts, and references, testing workflows.

How do I install debug-failing-test?

Install or run debug-failing-test using Copy skill directory. Check debug-failing-test for the latest setup command.

Is debug-failing-test actively maintained?

debug-failing-test may need a closer maintenance check before production use.

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Stars
132
Forks
51
Last commit
17 days ago
Repository age
2 years
License
MIT

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