requesting-code-review
Dispatch code review subagents with focused context to catch issues before they compound.
pytest-coverage
Run pytest with coverage reporting to identify and eliminate untested code lines.
Full skill instructions
The goal is for the tests to cover all lines of code.
Generate a coverage report with:
pytest --cov --cov-report=annotate:cov_annotate
If you are checking for coverage of a specific module, you can specify it like this:
pytest --cov=your_module_name --cov-report=annotate:cov_annotate
You can also specify specific tests to run, for example:
pytest tests/test_your_module.py --cov=your_module_name --cov-report=annotate:cov_annotate
Open the cov_annotate directory to view the annotated source code. There will be one file per source file. If a file has 100% source coverage, it means all lines are covered by tests, so you do not need to open the file.
For each file that has less than 100% test coverage, find the matching file in cov_annotate and review the file.
If a line starts with a ! (exclamation mark), it means that the line is not covered by tests. Add tests to cover the missing lines.
Keep running the tests and improving coverage until all lines are covered.
Dispatch code review subagents with focused context to catch issues before they compound.
Evaluate code review feedback with technical rigor before implementing, avoiding performative agreement and blind implementation.
Isolated git worktrees with smart directory selection and safety verification.
Structured workflow for completing development branches with test verification and merge/PR options.
review
Conducts multi-axis code review. Use before merging any change. Use when reviewing code written by yourself, another agent, or a human. Use when you need to assess code quality across multiple dimensions before it enters the main branch.
Standardized git commits using Conventional Commits specification with intelligent diff analysis and message generation.
Structures git workflow practices. Use when making any code change. Use when committing, branching, resolving conflicts, or when you need to organize work across multiple parallel streams.
Code review focused exclusively on over-engineering. Finds what to delete: reinvented standard library, unneeded dependencies, speculative abstractions, dead flexibility. One line per finding: location, what to cut, what replaces it. Complements correctness-focused review, this one only hunts complexity.
Generate Excalidraw diagrams from natural language descriptions in multiple formats.
Whole-repo audit for over-engineering. Like ponytail-review, but scans the entire codebase instead of a diff: a ranked list of what to delete, simplify, or replace with stdlib/native equivalents. One-shot report, does not apply fixes.
Systematic code review practices for constructive feedback, bug detection, and team knowledge sharing.
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