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codebase-cleanup-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

46

Quality

48%

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

42%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 content is well-structured with a clear eight-step sequence and concrete thresholds, but it is heavily padded with hypothetical example data and lacks any progressive disclosure via separate reference files. Validation checkpoints are absent, though the skill is analytical rather than destructive.

Suggestions

Trim illustrative filler (specific dollar amounts, ROI percentages, sample trend numbers) and replace with concise structural guidance Claude can populate.

Move detailed report templates and example dashboards into reference files under ./references/ and link to them from SKILL.md.

Add explicit verification steps, such as cross-checking the debt inventory against the actual codebase before producing the final report.

DimensionReasoningScore

Conciseness

The body is noticeably verbose: extensive hypothetical filler (specific dollar figures like '$36,000', ROI percentages, sample trend data, and example dashboards) that Claude could generate itself, padding every section with illustrative data rather than lean guidance.

2 / 5

Actionability

Provides concrete thresholds (>10 cyclomatic complexity, >50 line methods), real Python facade/refactoring examples, and structured YAML metric templates, but the code is illustrative pattern demonstration rather than runnable tooling, leaving some gaps.

3 / 5

Workflow Clarity

Eight numbered sections give a clear sequence (Inventory -> Impact -> Metrics -> Plan -> Implementation -> Prevention -> Communication -> Success Metrics), but there are no explicit validation or verification checkpoints (e.g., confirm inventory against the actual codebase).

3 / 5

Progressive Disclosure

Section headers provide reasonable structure, but the 380-line body is monolithic with no bundle files or external references; detailed templates and example outputs that belong in separate reference files are all inlined.

3 / 5

Total

11

/

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 clearly conveys the skill's purpose and domain with several concrete actions, but it is written in second-person voice and omits any explicit 'Use when' trigger guidance, which caps completeness. It is also truncated mid-sentence ('create acti').

Suggestions

Rewrite in third person (e.g., 'Identifies, quantifies, and prioritizes technical debt...') to avoid the second-person voice penalty.

Add an explicit trigger clause such as 'Use when analyzing technical debt, planning refactoring, or prioritizing code cleanup.'

Repair the truncated frontmatter so the description is not cut off at 'create acti'.

DimensionReasoningScore

Specificity

Names the domain and several concrete actions ('identifying, quantifying, and prioritizing technical debt', 'Analyze the codebase to uncover debt, assess its impact'), but uses second-person voice ('You are a technical debt expert', 'Analyze the codebase'), which reduces the score by one from a base of 4.

3 / 5

Completeness

The 'what' is clearly stated (identify, quantify, prioritize, assess, remediate technical debt) but there is no 'Use when...' clause or equivalent trigger guidance, capping completeness at 3 per the rubric guidelines.

3 / 5

Trigger Term Quality

'technical debt' and 'codebase' are natural terms a user might say, but coverage lacks synonyms or common variations like 'refactoring', 'code smell', or 'legacy code'.

3 / 5

Distinctiveness Conflict Risk

'Technical debt analysis and remediation' is a fairly distinct niche with limited overlap risk, though it could mildly overlap with general code-review or refactoring skills.

4 / 5

Total

13

/

20

Passed

Validation

100%

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

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
rmyndharis/antigravity-skills
Reviewed

Table of Contents

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