test-driven-hook-debugging

Debugging and fixing shell hooks by writing isolated test suites first, then using test failures to pinpoint logic bugs

5 stars

Best use case

test-driven-hook-debugging is best used when you need a repeatable AI agent workflow instead of a one-off prompt.

Debugging and fixing shell hooks by writing isolated test suites first, then using test failures to pinpoint logic bugs

Teams using test-driven-hook-debugging should expect a more consistent output, faster repeated execution, less prompt rewriting.

When to use this skill

  • You want a reusable workflow that can be run more than once with consistent structure.

When not to use this skill

  • You only need a quick one-off answer and do not need a reusable workflow.
  • You cannot install or maintain the underlying files, dependencies, or repository context.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/test-driven-hook-debugging/SKILL.md --create-dirs "https://raw.githubusercontent.com/vamseeachanta/workspace-hub/main/.agents/skills/workspace-hub/learned/test-driven-hook-debugging/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/test-driven-hook-debugging/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How test-driven-hook-debugging Compares

Feature / Agenttest-driven-hook-debuggingStandard Approach
Platform SupportNot specifiedLimited / Varies
Context Awareness High Baseline
Installation ComplexityUnknownN/A

Frequently Asked Questions

What does this skill do?

Debugging and fixing shell hooks by writing isolated test suites first, then using test failures to pinpoint logic bugs

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# Test-Driven Hook Debugging

When a shell hook has subtle logic bugs (e.g., git operations failing silently in non-repo contexts), write a focused test suite in Python using `subprocess` to call the hook in controlled scenarios. Run tests to see the failure mode, then trace the gap between test expectations and hook behavior. Use guard clauses (e.g., `git rev-parse --git-dir` before `git log`) to handle edge cases. Re-run tests atomically after each fix to confirm the change. This approach isolates the bug and prevents regressions better than manual testing.

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