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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

62

1.43x
Quality

51%

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

50%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.

A thorough, well-structured guide with concrete thresholds and executable refactoring examples, but it is heavily padded with mock data and re-explained fundamentals, lacks validation checkpoints in its workflow, and inlines content that should be split into referenced files.

Suggestions

Strip the fabricated metrics, ROI percentages, and trend tables, or move them to a reference template; keep only the thresholds and patterns Claude cannot derive itself to improve conciseness.

Add explicit validation steps to the workflow, e.g. 'Verify each flagged debt item against the actual codebase before costing it' and 'Confirm remediation ROI estimates with measured data.'

Extract the dashboards, refactoring code patterns, and stakeholder report templates into references/ files (e.g. DASHBOARD.md, REFACTORING-PATTERNS.md) and link to them from SKILL.md so progressive disclosure reaches one level deep.

DimensionReasoningScore

Conciseness

The ~380-line body is noticeably verbose: it re-explains tech-debt concepts Claude already knows (duplicated code, god classes, cyclomatic complexity) and pads with extensive fabricated dashboards, mock ROI figures, and trend tables that inflate tokens without adding instruction.

2 / 5

Actionability

Provides mostly executable guidance — concrete thresholds (complexity >10, methods >50 lines, god classes >500 lines/20 methods), a runnable PaymentFacade refactoring pattern, and real YAML hook configs — with only minor gaps around how to actually measure the metrics.

4 / 5

Workflow Clarity

The 8 numbered sections give a clear inventory-to-success-metrics sequence, but there are no validation or verification checkpoints (e.g. confirm findings against the real codebase before recommending remediation), so the sequence stays at the no-checkpoints anchor.

3 / 5

Progressive Disclosure

Content is well organized into headed sections but everything is inlined in one ~380-line SKILL.md with no bundle files and no references; the dashboard templates, refactoring patterns, and communication report templates clearly belong in separate referenced files.

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 states a clear domain and several concrete actions but is truncated and omits any 'Use when...' trigger guidance, capping completeness at 3. It also uses second-person voice rather than the required third person.

Suggestions

Complete the truncated final clause (e.g. 'create actionable remediation plans') and restate the description in third person ('Analyzes codebases to identify, quantify, and prioritize technical debt...') to recover the specificity voice penalty.

Add an explicit trigger clause, e.g. 'Use when the user asks about technical debt, tech debt, code quality, refactoring priorities, or debt remediation roadmaps.'

Include natural synonyms users actually say — 'tech debt', 'refactoring', 'code smells', 'code quality' — to broaden trigger-term coverage beyond the single phrase 'technical debt'.

DimensionReasoningScore

Specificity

Lists several concrete actions ('identifying, quantifying, and prioritizing technical debt', 'Analyze the codebase to uncover debt, assess its impact, and create acti[onable remediation plans]') but the field is truncated mid-sentence, and second-person voice ('You are a technical debt expert') triggers the -1 voice penalty from a base of 4.

3 / 5

Completeness

Has a clear 'what' (identify, quantify, prioritize, analyze, assess impact, remediate) but no 'Use when...' clause or equivalent trigger guidance, and the field is truncated, so per the missing-trigger cap completeness cannot exceed 3.

3 / 5

Trigger Term Quality

Contains the natural phrase 'technical debt' plus 'codebase', 'remediation', and 'debt', but misses common synonyms users would say like 'tech debt', 'refactoring', 'code smells', or 'code quality'.

3 / 5

Distinctiveness Conflict Risk

Targets a fairly clear niche (technical debt analysis and remediation) that is mostly distinguishable from related skills, with only minor overlap risk against general code-review or refactoring skills.

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.

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
administrakt0r/AI-Agents-Safe-Coding-Skills
Reviewed

Table of Contents

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