dead-code-eliminator

Identify and analyze unused or redundant code including unused functions/methods, unused variables/imports, unreachable code, and redundant conditions. Use when cleaning up codebases, improving maintainability, reducing technical debt, or conducting code quality audits. Analyzes Python code using AST analysis and produces markdown reports listing dead code locations with line numbers, severity ratings, and recommendations. Triggers when users ask to find dead code, remove unused code, identify unused imports, find unreachable code, or clean up redundant logic.

2.06x

Quality

75%

Does it follow best practices?

Impact

93%

2.06x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./skills/dead-code-eliminator/SKILL.md

Quality

Content

50%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill provides highly actionable, executable guidance with clear tool commands and detection strategies. However, it suffers from severe verbosity - the inline report template and redundant explanations bloat the content significantly. The workflow is logical but lacks explicit validation gates, and content that should be in reference files is embedded inline.

Suggestions

Move the entire 'Generate Report' template section to a separate reference file (e.g., references/report-template.md) and link to it

Remove explanatory text about what dead code types are (e.g., 'Code that can never execute') - Claude knows this

Consolidate the 'Common False Positives' section with the 'Verify Findings' section to eliminate redundancy

Add explicit validation checkpoint: 'Before generating report, confirm at least 3 findings have been verified manually'

Dimension	Reasoning	Score
Conciseness	Extremely verbose at ~400+ lines with significant redundancy. The report template alone is ~150 lines of example output. Explains concepts Claude knows (what unreachable code is, what unused imports are). The 'Common False Positives' section repeats information already covered in verification steps.	1 / 3
Actionability	Provides fully executable bash commands and Python code snippets throughout. Tool installation, usage commands, and grep patterns are all copy-paste ready. The bundled scripts have clear invocation syntax with examples.	3 / 3
Workflow Clarity	Steps are clearly numbered (1-6) with logical sequence, but lacks explicit validation checkpoints. The 'Verify Findings' step exists but doesn't have a clear feedback loop for when verification fails. No explicit 'stop and check' gates before proceeding to report generation.	2 / 3
Progressive Disclosure	References external file (dead-code-patterns.md) appropriately, but the main skill file is monolithic with the massive report template inline. The report template and common false positives sections should be in separate reference files.	2 / 3
	Total	8 / 12 Passed

Description

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 (dead code types, AST analysis, markdown reports), comprehensive trigger terms that users would naturally say, explicit 'Use when' and 'Triggers when' clauses, and a clear niche that distinguishes it from general code analysis skills.

Dimension	Reasoning	Score
Specificity	Lists multiple specific concrete actions: 'unused functions/methods, unused variables/imports, unreachable code, redundant conditions' and specifies outputs like 'markdown reports listing dead code locations with line numbers, severity ratings, and recommendations.'	3 / 3
Completeness	Clearly answers both what (analyze unused/redundant code, produce markdown reports with line numbers and severity) AND when (explicit 'Use when...' clause plus 'Triggers when...' clause with specific user phrases).	3 / 3
Trigger Term Quality	Excellent coverage of natural terms users would say: 'find dead code', 'remove unused code', 'identify unused imports', 'find unreachable code', 'clean up redundant logic', plus domain terms like 'technical debt', 'code quality audits', 'maintainability.'	3 / 3
Distinctiveness Conflict Risk	Clear niche focused specifically on dead code analysis in Python using AST; distinct triggers like 'dead code', 'unused imports', 'unreachable code' are unlikely to conflict with general code review or other analysis skills.	3 / 3
	Total	12 / 12 Passed

Validation

90%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 10 / 11 Passed

Validation for skill structure

Criteria	Description	Result
skill_md_line_count	SKILL.md is long (564 lines); consider splitting into references/ and linking	Warning

	Total	10 / 11 Passed

Repository: ArabelaTso/Skills-4-SE
Commit: 0f00a4f

Reviewed: 4 months ago

Table of Contents

Discovery Implementation Validation

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