Every section earns its place—the deadness classification table, uncertainty checklist, and worked example all provide information Claude wouldn't inherently know about codebase-specific patterns. No padding or explanation of obvious concepts.

Provides concrete verification steps, specific grep commands (`rg 'legacy_format' --type py`), exact file locations to check (`setup.py`, `pyproject.toml`), and a complete worked example with real decision-making. The output format is copy-paste ready.

Clear 5-step workflow (Identify → Verify → Deprecate → Delete → Test) with explicit validation checkpoints. The 'Deprecate first' step for uncertain cases provides a feedback loop, and the worked example demonstrates the verification sequence in practice.

Content is well-organized with clear sections and tables, but it's a moderately long single file. The reference to `behavior-preservation-checker` suggests related skills exist but isn't a clear navigation link. Could benefit from splitting the worked example or detailed tables into separate reference files.

Lists multiple specific concrete actions: 'unreachable branches, uncalled functions, unused classes, dead feature flags' - these are precise, actionable capabilities.

Clearly answers both what ('Finds and safely removes code that is never executed') and when ('Use when cleaning up after a feature removal, when the user suspects the codebase has accumulated cruft, or when reducing build/bundle size').

Includes natural terms users would say: 'feature removal', 'cruft', 'build/bundle size', 'dead code', 'unused' - these match how developers naturally describe cleanup tasks.

Clear niche focused specifically on dead code removal with distinct triggers like 'unreachable branches', 'dead feature flags', and 'cruft' - unlikely to conflict with general refactoring or code review skills.