| name | llm-artifacts-detection |
| description | Detects common LLM coding agent artifacts in codebases. Identifies test quality issues, dead code, over-abstraction, and verbose LLM style patterns. Use when cleaning up AI-generated code or reviewing for agent-introduced cruft. |
| user-invocable | false |
LLM Artifacts Detection
Detect and flag common patterns introduced by LLM coding agents that reduce code quality.
Detection Categories
Agent Prompts
Use these prompts to spawn focused detection agents:
Tests Agent
Analyze the test files for LLM-introduced test quality issues:
1. **DRY Violations**: Look for setup/teardown code repeated across multiple test functions instead of using fixtures or shared helpers. Flag patterns like:
- Identical object creation in multiple tests
- Repeated mock configurations
- Copy-pasted database setup
2. **Library Testing**: Identify tests that validate standard library or framework behavior rather than application code. Signs:
- No imports from the application codebase
- Testing built-in functions or third-party library methods
- Assertions about stdlib behavior
3. **Mock Boundaries**: Flag mocking that's too deep or too shallow:
- Too deep: Mocking internal implementation details, private methods
- Too shallow: Mocking at the wrong layer, missing integration points
- Wrong level: Unit test mocks in integration tests or vice versa
For each issue found, report: [FILE:LINE] ISSUE_TITLE
Dead Code Agent
Scan the codebase for dead code and cleanup opportunities:
1. **Unused Code**: Find functions, classes, and variables with no references:
- Functions never called
- Classes never instantiated
- Module-level variables never read
- Unreachable code after returns
2. **TODO/FIXME Comments**: Flag all TODO, FIXME, HACK, XXX comments that indicate incomplete work
3. **Backwards Compat Cruft**: Look for patterns suggesting removed features:
- Variables renamed with _unused, _old, _deprecated suffixes
- Re-exports only for backwards compatibility
- Comments like "# removed", "# legacy", "# deprecated"
- Empty functions/classes kept "for compatibility"
4. **Orphaned Tests**: Tests for code that no longer exists:
- Test files with no corresponding source
- Test functions testing deleted features
For each issue found, report: [FILE:LINE] ISSUE_TITLE
Abstraction Agent
Review the codebase for over-engineering introduced by LLM agents:
1. **Over-Abstraction**: Identify unnecessary abstraction layers:
- Wrapper classes that just delegate to one method
- Interfaces/protocols with only one implementation
- Abstract base classes with single concrete class
- Factory functions that always return the same type
2. **Copy-Paste Drift**: Find 3+ similar code blocks that should be parameterized:
- Nearly identical functions with minor variations
- Repeated patterns that could be a single function with parameters
- Similar class methods across multiple classes
3. **Over-Configuration**: Flag configuration for non-configurable things:
- Feature flags that are never toggled
- Environment variables always set to one value
- Config options with no production variation
- Overly generic code for single use case
For each issue found, report: [FILE:LINE] ISSUE_TITLE
Style Agent
Check for verbose LLM-style patterns that reduce code clarity:
1. **Obvious Comments**: Comments that restate what the code clearly does:
- "# increment counter" above counter += 1
- "# return the result" above return result
- Docstrings that repeat the function name
2. **Over-Documentation**: Excessive documentation on trivial code:
- Full docstrings on simple getters/setters
- Parameter descriptions for obvious args
- Return value docs for self-evident returns
3. **Defensive Overkill**: Unnecessary defensive programming:
- try/except around code that cannot fail
- Null checks on values that can't be null
- Type checks after type hints guarantee the type
- Validation of already-validated inputs
4. **Unnecessary Type Hints**: Type hints that add no value:
- Type hints on obvious literal assignments
- Redundant hints on variables immediately clear from context
- Over-annotated internal/local variables
For each issue found, report: [FILE:LINE] ISSUE_TITLE
Usage
- Load this skill when reviewing AI-generated code
- Spawn agents for specific detection categories as needed
- Use reference files for detailed criteria and examples
- Report issues in format:
[FILE:LINE] ISSUE_TITLE
When to Apply
- Cleaning up code written by AI coding agents
- Post-generation code review
- Reducing code bloat from iterative AI generation
- Identifying patterns that reduce maintainability
