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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

47

Quality

50%

Does it follow best practices?

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SecuritybySnyk

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tessl review fix ./skills/code-refactoring-tech-debt/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

50%

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

The body is a well-structured, concrete technical-debt framework, but it is verbose with illustrative placeholder code, lacks executable analysis tooling and inter-phase validation checkpoints, and is entirely monolithic with no progressive disclosure. Every dimension lands at 2.

Suggestions

Move the large template/example blocks (metrics dashboard yaml, trend dicts, facade implementation, stakeholder-report markdown) into reference files and link to them from a lean overview to improve both conciseness and progressive disclosure.

Replace placeholder code with concrete, runnable analysis commands/tools (e.g. specific linters/complexity scanners) so the guidance is copy-paste executable rather than illustrative.

Add explicit validation checkpoints between phases (e.g. 'Confirm the debt inventory is complete and metrics are gathered before building the prioritized roadmap') to lift workflow clarity.

DimensionReasoningScore

Conciseness

The ~380-line body avoids explaining basics Claude already knows and supplies specific thresholds, but it is padded with long illustrative template blocks (hardcoded debt_trends dates, full PaymentFacade/PaymentService code, yaml team/quality-gate configs, output-report markdown) that could be tightened, matching the 'mostly efficient but could be tightened' anchor rather than the lean 3.

2 / 3

Actionability

Concrete thresholds and ROI formulas are strong, but the code examples are illustrative placeholders (e.g. 'def process_payment(self, order): pass', example output dicts) rather than executable analysis tooling, and the core task ('Conduct a thorough scan') specifies no runnable commands, matching 'some concrete guidance but incomplete; pseudocode instead of executable code'.

2 / 3

Workflow Clarity

The eight numbered phases (Inventory -> Impact -> Metrics -> Plan -> Implementation -> Prevention -> Communication -> Success Metrics) give a clear sequence, but there are no explicit validation checkpoints or feedback loops between phases (e.g. verify inventory completeness before prioritizing), matching 'steps listed but validation gaps; checkpoints missing or implicit'.

2 / 3

Progressive Disclosure

The skill is a single monolithic file with no references/, scripts/, or assets/ bundles and no file references at all; sections are well-organized internally, but large template/example blocks that should be split into one-level-deep reference files are inlined, matching the score-2 anchor.

2 / 3

Total

8

/

12

Passed

Description

50%

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 conveys a clear domain and several concrete actions but is written in second person, lacks any 'Use when' trigger guidance, and is truncated mid-word, capping most dimensions at 2. It is adequate but not exemplary.

Suggestions

Add an explicit trigger clause, e.g. 'Use when the user asks about technical debt, code quality, refactoring priorities, or legacy/maintainability issues.'

Rewrite in third person ('Identifies, quantifies, and prioritizes technical debt...') to avoid the second-person specificity penalty and complete the truncated final phrase ('create actionable remediation plans').

Broaden natural trigger terms to include 'refactoring', 'code quality', 'legacy code', and 'maintainability' for better user-language coverage.

DimensionReasoningScore

Specificity

Lists multiple concrete actions ('identifying, quantifying, and prioritizing technical debt', 'Analyze the codebase to uncover debt, assess its impact, and create acti[onable remediation plans]') which would anchor at 3, but the second-person voice ('You are a technical debt expert') triggers the rubric's -1 specificity penalty.

2 / 3

Completeness

It clearly states what the skill does but provides no 'Use when...' clause or equivalent explicit trigger guidance, so per the rubric guideline completeness is capped at 2; the truncated tail ('create acti') further weakens the what-side without changing the cap.

2 / 3

Trigger Term Quality

'technical debt' and 'codebase' are relevant natural keywords, but common variations a user would actually say ('refactoring', 'code quality', 'legacy code', 'maintainability') are missing, matching the 'some relevant keywords but missing common variations' anchor.

2 / 3

Distinctiveness Conflict Risk

'Technical debt' is a recognizable niche, but without explicit triggers and given natural overlap with general refactoring, code-review, and code-quality skills, it matches 'somewhat specific but could still overlap with similar skills' rather than the clearly-distinct 3 anchor.

2 / 3

Total

8

/

12

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/antigravity-awesome-skills
Reviewed

Table of Contents

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