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code-refactoring-tech-debt

You are a technical debt expert specializing in identifying, quantifying, and prioritizing technical debt in software projects. Analyze the codebase to uncover debt, assess its impact, and create acti

1.43x
Quality

60%

Does it follow best practices?

Impact

73%

1.43x

Average score across 3 eval scenarios

SecuritybySnyk

Passed

No findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./plugins/AI-Agents-Safe-Coding-Skills-claude/skills/code-refactoring-tech-debt/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

48%Weight 40%Scale 1-5

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

The body lays out a coherent, well-sequenced technical-debt analysis framework with concrete thresholds and output formats, but it is held back by heavy padding with knowledge Claude already possesses, illustrative rather than executable examples, and no offloading of template content into reference files. The absence of actual measurement tooling commands leaves the skill's core analytical step under-specified.

Suggestions

Cut the textbook definitions of code smells, test-quality issues, and documentation debt, keeping only the quantification instructions and thresholds Claude wouldn't naturally apply.

Add executable measurement commands (e.g., specific complexity/duplication/coverage tool invocations) instead of name-dropping sonarqube/dependabot/codecov with no usage guidance.

Move the example dashboards, ROI calculation templates, and YAML quality-gate configs into reference files (e.g., references/templates.md) and keep SKILL.md as a lean overview.

DimensionReasoningScore

Conciseness

The ~380-line body restates textbook concepts Claude already knows (code-smell taxonomies like "Exact duplicates (copy-paste)", "High cyclomatic complexity (>10)", "Feature envy", and definitions of brittle/flaky tests) and pads sections with illustrative blocks of invented figures ("Annual Cost: 240 hours × $150/hour = $36,000"), spanning many sections rather than isolated instances.

2 / 5

Actionability

Concrete thresholds, quantification instructions, and an explicit output format are provided, but the code examples are illustrative patterns with `pass` bodies and the core measurement step offers no executable commands — tools like "sonarqube", "dependabot", and "codecov" are only name-dropped, leaving key details missing.

3 / 5

Workflow Clarity

A clear eight-step numbered sequence (Inventory → Impact → Metrics → Plan → Implementation → Prevention → Communication → Success Metrics) with an explicit Output Format checklist and KPI targets serving as implicit checkpoints; the workflow is analytical rather than destructive/batch, so the validation cap does not apply, though no explicit verify or error-recovery steps exist.

4 / 5

Progressive Disclosure

Eight well-organized numbered sections provide good structure, but the skill is a monolithic single file — the example dashboards, ROI templates, and YAML gate configurations clearly belong in separate reference files, and no bundle files exist to offload them.

3 / 5

Total

12

/

20

Passed

Description

53%Weight 40%Scale 1-5

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description communicates a clear, fairly distinct capability (technical debt analysis and remediation) but is weakened by a truncated final phrase, second-person voice, and the complete absence of any "use when" trigger guidance. It reads as a persona statement rather than a trigger-optimized skill description.

Suggestions

Add an explicit trigger clause, e.g. "Use when the user mentions technical debt, tech debt, code quality degradation, or asks for a remediation/refactoring roadmap."

Rewrite in third person ("Identifies, quantifies, and prioritizes technical debt...") and complete the truncated final action ("create actionable remediation plans").

Include natural synonyms such as "tech debt", "legacy code", and "refactoring roadmap" to improve trigger-term coverage.

DimensionReasoningScore

Specificity

The description lists several concrete actions ("identifying, quantifying, and prioritizing technical debt", "Analyze the codebase", "assess its impact", "create acti[onable plans]") matching anchor 4, but the second-person voice ("You are a technical debt expert") incurs the mandated 1-point penalty, and the final action is truncated mid-word.

3 / 5

Completeness

The "what" is clear (identify, quantify, prioritize, and remediate technical debt), but there is no "Use when..." clause or equivalent trigger guidance at all, capping this dimension at 3 per the judging guidelines.

3 / 5

Trigger Term Quality

Relevant keywords like "technical debt", "codebase", and "debt" are present, but common natural variations users would say — "tech debt", "refactoring", "legacy code", "code quality" — are missing, matching the anchor for some relevant keywords without synonyms.

3 / 5

Distinctiveness Conflict Risk

"Technical debt" establishes a clear niche with mostly distinct triggers, carrying only minor overlap risk with closely related refactoring or code-review skills; not 5 because no trigger phrases sharpen that boundary.

4 / 5

Total

13

/

20

Passed

Validation

93%

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

Validation — 15 / 16 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

15

/

16

Passed

Repository

administrakt0r/AI-Agents-Safe-Coding-Skills

Path

plugins/AI-Agents-Safe-Coding-Skills-claude/skills/code-refactoring-tech-debt/SKILL.md

Reviewed

Table of Contents

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