code-repair-generation-combo
Automatically repair buggy code and generate comprehensive tests for Python, Java, and C++ programs. Use when users need to fix logic errors or runtime errors in functions, modules, or repositories. Accepts specifications via natural language descriptions, existing test cases, or input/output examples. Generates corrected code, creates or updates tests to verify correctness and prevent regressions, and produces a detailed report explaining the bug, fix, and testing strategy. Triggers on requests like "fix this bug", "repair this code", "debug this function", or "this code is broken".
89
85%
Does it follow best practices?
Impact
95%
1.14xAverage score across 3 eval scenarios
Passed
No known issues
Quality
Discovery
100%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This is an excellent skill description that hits all the marks. It provides specific capabilities (bug repair, test generation, reporting), explicit language scope, clear trigger terms that match natural user language, and comprehensive guidance on when to activate. The description is well-structured and avoids vague language while remaining concise.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Lists multiple specific concrete actions: 'repair buggy code', 'generate comprehensive tests', 'fix logic errors or runtime errors', 'generates corrected code', 'creates or updates tests', 'produces a detailed report'. Also specifies supported languages (Python, Java, C++). | 3 / 3 |
Completeness | Clearly answers both what (repair code, generate tests, produce reports for Python/Java/C++) AND when with explicit 'Use when...' clause and 'Triggers on...' examples providing clear activation guidance. | 3 / 3 |
Trigger Term Quality | Excellent coverage of natural terms users would say: 'fix this bug', 'repair this code', 'debug this function', 'this code is broken', plus domain terms like 'logic errors', 'runtime errors', 'functions', 'modules', 'repositories'. | 3 / 3 |
Distinctiveness Conflict Risk | Clear niche combining bug repair + test generation for specific languages. The combination of debugging AND test generation with explicit language scope (Python, Java, C++) distinguishes it from general coding skills or testing-only skills. | 3 / 3 |
Total | 12 / 12 Passed |
Implementation
70%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill provides a solid, well-organized workflow for code repair and test generation with good progressive disclosure and clear validation checkpoints. However, it could be more concise by removing explanations of concepts Claude already knows (bug type definitions) and more actionable by providing complete, executable code examples rather than pseudocode summaries of fixes.
Suggestions
Replace the pseudocode examples with complete, executable code showing the actual buggy code, the fix, and the generated test file
Remove the 'Identify the bug type' section explaining what logic errors and runtime errors are - Claude already knows this
Condense the 'Understand the Bug' and 'Diagnose the Root Cause' sections which have overlapping content
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The skill is reasonably efficient but includes some unnecessary elaboration. Phrases like 'Walk through the code execution mentally or with examples' and detailed bullet lists explaining obvious concepts (what logic errors vs runtime errors are) add tokens without value for Claude. | 2 / 3 |
Actionability | Provides a clear workflow structure and mentions specific tools (Read, Edit, Bash) and commands (pytest, mvn test), but the examples are pseudocode summaries rather than executable code. The actual fix implementations are described abstractly ('Change range(1, n) to range(1, n+1)') rather than shown as complete, copy-paste ready code blocks. | 2 / 3 |
Workflow Clarity | Excellent multi-step workflow with clear sequencing (6 numbered phases), explicit validation checkpoints ('Ensure all tests pass - If tests fail, revisit the fix'), and feedback loops. The workflow covers diagnosis through verification with appropriate validation at each stage. | 3 / 3 |
Progressive Disclosure | Well-structured with clear overview sections and appropriate references to external files (references/python-testing.md, assets/bug-fix-report-template.md). References are one level deep and clearly signaled. Content is appropriately split between the main skill and supporting materials. | 3 / 3 |
Total | 10 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- ArabelaTso/Skills-4-SE
- Commit
0f00a4f
- Reviewed
Table of Contents
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