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deslop

Remove AI-generated code slop and clean up code style

45

Quality

46%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./cursor-team-kit/skills/deslop/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

60%

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

The skill is admirably concise and well-structured for its scope, with clear focus areas and guardrails. However, it lacks a concrete workflow (e.g., how to check the diff, iterate on changes, verify behavior preservation) and would benefit from before/after examples of slop patterns to make the guidance more actionable.

Suggestions

Add a concrete workflow sequence: 1) Get diff against main, 2) Identify slop patterns, 3) Make edits, 4) Verify behavior unchanged (e.g., run tests), 5) Summarize changes.

Include at least one before/after code example showing a specific slop pattern (e.g., unnecessary try/catch) and its cleaned-up version to make guidance more actionable.

Add a verification step or feedback loop (e.g., 'Run tests after each file edit to confirm behavior is unchanged') to ensure safe editing of code.

DimensionReasoningScore

Conciseness

Every line earns its place. No unnecessary explanations of what slop is or how code style works—assumes Claude's competence. The bullet points are tight and specific.

3 / 3

Actionability

Provides clear focus areas and guardrails, but lacks concrete examples of what slop looks like vs. clean code, and no specific commands or workflow for checking the diff against main. The guidance is directional rather than fully executable.

2 / 3

Workflow Clarity

The skill involves a multi-step process (check diff, identify slop, remove it, summarize) but provides no sequenced steps, no validation checkpoints, and no feedback loop for verifying behavior is unchanged after edits.

1 / 3

Progressive Disclosure

This is a simple, short skill under 50 lines with no need for external references. The content is well-organized into clear sections (Focus Areas, Guardrails) making it easy to scan.

3 / 3

Total

9

/

12

Passed

Description

32%

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 is too terse and lacks explicit trigger guidance ('Use when...'), which is critical for skill selection. While 'AI-generated code slop' is a somewhat distinctive concept, the description doesn't enumerate specific actions or provide natural keywords users would use when requesting this kind of cleanup.

Suggestions

Add a 'Use when...' clause with trigger terms like 'clean up AI code', 'remove slop', 'refactor generated code', 'simplify boilerplate', 'code quality'.

List specific concrete actions such as 'removes unnecessary comments, simplifies over-engineered patterns, fixes inconsistent naming, eliminates redundant code blocks'.

Include natural keyword variations users might say, such as 'refactor', 'code smell', 'AI-generated', 'ChatGPT code', 'copilot output', 'code review'.

DimensionReasoningScore

Specificity

It names a domain ('AI-generated code slop') and two actions ('remove' and 'clean up code style'), but doesn't list specific concrete actions like what cleaning up entails (e.g., removing unnecessary comments, simplifying logic, fixing naming conventions).

2 / 3

Completeness

It partially answers 'what' (remove slop, clean up style) but has no explicit 'when' clause or trigger guidance. Per the rubric, a missing 'Use when...' clause caps completeness at 2, and the 'what' is also weak, so this scores a 1.

1 / 3

Trigger Term Quality

Includes some relevant terms like 'code slop', 'clean up', and 'code style', but misses common natural variations users might say such as 'refactor', 'code quality', 'lint', 'code smell', 'boilerplate', or 'AI-generated code'.

2 / 3

Distinctiveness Conflict Risk

The term 'AI-generated code slop' is somewhat distinctive, but 'clean up code style' is broad enough to overlap with linting, formatting, or general refactoring skills.

2 / 3

Total

7

/

12

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
cursor/plugins
Reviewed

Table of Contents

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