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

53%

Does it follow best practices?

Impact

73%

1.43x

Average score across 3 eval scenarios

Securityby

Passed

No findings from the security scan

Fix and improve this skill with Tessl

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

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 is a thorough, well-sequenced technical-debt playbook, but it is token-heavy with placeholder/time-sensitive examples and keeps everything inline rather than splitting detailed templates into referenced files. Code examples are illustrative rather than executable.

Suggestions

Trim the illustrative cost-calculation and dashboard blocks to compact templates, and move hard time-sensitive values (e.g. '2024_Q1', 'React 16 → 18') out of the main flow.

Make the refactoring code examples executable or explicitly mark them as illustrative patterns, replacing `pass` and undefined helper references.

Move the metrics-dashboard, communication-plan, and trend-analysis detail into separate reference files (e.g. DASHBOARD.md, COMMUNICATION.md) referenced one level deep from the overview.

Dimension	Reasoning	Score
Conciseness	The ~380-line body is noticeably verbose, padding with illustrative cost calculations, placeholder dashboards, and time-sensitive hardcodes ('2024_Q1', 'React 16 → 18') that are not placed in an 'old patterns' section and inflate token usage without adding guidance Claude lacks.	2 / 5
Actionability	Concrete thresholds (complexity >10, methods >50 lines, god classes >500 lines) and example quality-gate YAML are actionable, but the code examples are template/placeholder (`pass`, undefined `LegacyPaymentProcessor`/`feature_flag`) rather than copy-paste executable.	3 / 5
Workflow Clarity	An explicit 8-step sequence (Inventory → Impact → Metrics → Plan → Implementation → Prevention → Communication → Success Metrics) with substructure gives a clear path, though explicit validation/verification checkpoints against real measurements are only implied.	4 / 5
Progressive Disclosure	The skill is well-sectioned but monolithic at ~380 lines with no bundle files and no one-level-deep references; the example dashboards, communication-plan templates, and trend-analysis blocks read as content that could live in separate reference files.	3 / 5
	Total	12 / 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 concrete capabilities clearly but omits any explicit 'when to use' trigger clause and lacks common synonyms, so it is strongest on specificity and weakest on completeness/trigger coverage. The truncation at 'acti' also signals a malformed description field.

Suggestions

Add an explicit 'Use when...' clause naming concrete triggers, e.g. 'Use when analyzing technical debt, code smells, or legacy code, or when planning refactoring roadmaps.'

Include natural synonyms users say — 'code smells', 'refactoring', 'legacy code', 'maintenance burden' — alongside 'technical debt'.

Repair the truncated description so it does not end mid-word at 'acti'.

Dimension	Reasoning	Score
Specificity	Names the domain and several concrete actions — 'identifying, quantifying, and prioritizing technical debt', 'Analyze the codebase to uncover debt, assess its impact, and create actionable remediation plans' — but the description is truncated mid-word ('acti') and could be more granular.	4 / 5
Completeness	The 'what' is clear (identify, quantify, prioritize, analyze, remediate), but there is no 'Use when...' or equivalent explicit trigger guidance, which caps completeness at 3 per the judging guidelines.	3 / 5
Trigger Term Quality	'technical debt', 'codebase', and 'remediation' are relevant, but it omits common synonyms users would say like 'code smells', 'refactoring', 'legacy code', and has no natural trigger phrasing.	3 / 5
Distinctiveness Conflict Risk	'Technical debt' is a fairly distinct niche with minimal overlap, though it brushes against general code-review and refactoring skills.	4 / 5
	Total	14 / 20 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
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/skills/code-refactoring-tech-debt/SKILL.md
Commit: 57c135b

Reviewed: 2 days ago

Table of Contents

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