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codebase-cleanup-tech-debt

Identify technical debt from actual code and change history, estimate its impact, and prioritize bounded improvements with explicit assumptions.

52

Quality

57%

Does it follow best practices?

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SecuritybySnyk

Passed

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tessl review fix ./skills/codebase-cleanup-tech-debt/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

56%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 is well-structured and actionable with concrete quantification guidance and illustrative code, but it is notably verbose for an analysis skill and keeps all material in a single inlined file with no progressive disclosure to supporting references.

Suggestions

Trim the debt-category enumerations and example cost calculations to assume Claude's existing knowledge of technical-debt types, keeping only the quantification guidance and thresholds.

Move the detailed example calculations, metric dashboards, and remediation templates into reference files (e.g., references/templates.md) and link to them from a leaner SKILL.md overview.

DimensionReasoningScore

Conciseness

At ~400 lines the body is noticeably verbose, with padded enumerations of debt categories (code, architecture, testing, documentation, infrastructure debt) and long illustrative cost calculations that largely restate concepts Claude already knows.

2 / 5

Actionability

The skill provides concrete, specific guidance — quantification formulas, ROI calculations, metric YAML schemas, and runnable facade-migration Python — with only minor gaps; the hypothetical framing is explicitly flagged rather than presented as fact.

4 / 5

Workflow Clarity

An explicit 8-step sequence (inventory through success metrics) is clearly ordered with a 'Stop and ask for clarification' checkpoint; it lacks per-step validation feedback loops, so it sits at 4 rather than 5.

4 / 5

Progressive Disclosure

Section structure is clear, but no references/scripts/assets bundle exists and all 400 lines (example calculations, configs, code) are inlined in SKILL.md, so content that would benefit from splitting into reference files is not disclosed progressively.

3 / 5

Total

13

/

20

Passed

Description

58%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 states a clear, third-person purpose with concrete actions and a distinct technical-debt niche, but lacks an explicit 'Use when' trigger clause and broader natural synonyms, capping completeness and trigger-term quality.

Suggestions

Add an explicit 'Use when...' trigger clause naming natural user phrases (e.g., 'Use when the user asks about technical debt, legacy code, refactoring priorities, or code cleanup').

Broaden trigger terms with synonyms such as 'refactoring', 'legacy code', and 'code cleanup' to improve keyword coverage.

DimensionReasoningScore

Specificity

The description names the domain and three concrete actions ('Identify technical debt from actual code and change history, estimate its impact, and prioritize bounded improvements'), with only minor coverage gaps; it stops short of the comprehensive multi-action enumeration of a 5.

4 / 5

Completeness

The 'what' is clear (identify, estimate impact, prioritize) but there is no 'Use when...' or equivalent explicit trigger clause, which caps completeness at 3 per the rubric guideline.

3 / 5

Trigger Term Quality

'technical debt' is a strong natural keyword a user would say, but common synonyms like 'refactoring', 'legacy code', or 'code cleanup' are missing, leaving keyword coverage partial.

3 / 5

Distinctiveness Conflict Risk

'technical debt analysis' with the 'bounded improvements / explicit assumptions' framing is a mostly distinct niche with only minor overlap risk against general refactoring skills.

4 / 5

Total

14

/

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.

Validation15 / 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
sickn33/agentic-awesome-skills
Reviewed

Table of Contents

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