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review-local-changes

Comprehensive review of local uncommitted changes using specialized agents with code improvement suggestions

43

Quality

43%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Risky

Do not use without reviewing

Fix and improve this skill with Tessl

tessl review fix ./plugins/review/skills/review-local-changes/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

55%

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

This skill provides an exceptionally detailed and actionable code review workflow with clear phases, concrete commands, and well-defined output formats. However, it is severely over-engineered for a SKILL.md file — the content is far too verbose, repeats key concepts multiple times (especially the filtering logic), and inlines everything into a single monolithic document rather than using progressive disclosure. The actionability and workflow clarity are excellent, but the token cost is very high.

Suggestions

Extract the JSON and markdown output templates into separate reference files (e.g., TEMPLATES.md) and link to them from the main skill, reducing the SKILL.md by ~40%.

Remove redundant explanations of the filtering logic — the min-impact filter and progressive confidence threshold are each explained 2-3 times with examples. State the rules once with the concrete example, then reference that section.

Move the false-positive examples, confidence/impact scoring rubrics, and evaluation guidelines into a separate REVIEW-GUIDELINES.md file, keeping only a brief summary in the main skill.

Eliminate unnecessary prose like 'The goal is to catch bugs and security issues...' and 'This review happens before commit...' — Claude already understands the purpose from the workflow itself.

DimensionReasoningScore

Conciseness

The skill is extremely verbose at ~300+ lines. It over-explains concepts like argument parsing, filtering logic, and scoring rubrics that Claude can handle with far less detail. The concrete example walkthrough for filter application, the extensive false-positive examples, and repeated restatements of the same filtering rules (min-impact is explained at least 3 times) waste significant tokens.

1 / 3

Actionability

The skill provides highly concrete, executable guidance: specific git commands, exact agent prompts to use, detailed scoring rubrics with numeric thresholds, complete output templates in both markdown and JSON formats, and concrete examples of usage. Everything is copy-paste ready and unambiguous.

3 / 3

Workflow Clarity

The multi-phase workflow (Preparation → Issue Search → Scoring/Filtering → Report) is clearly sequenced with explicit steps, validation checkpoints (filtering with dual thresholds), and feedback loops (agents verify issues, confidence scoring acts as validation). The parallel agent orchestration is well-specified with clear inputs and outputs for each phase.

3 / 3

Progressive Disclosure

The entire skill is a monolithic wall of text with no references to external files. The JSON/markdown output templates, scoring rubrics, false-positive examples, and argument parsing details could all be split into separate reference files. Everything is inlined into a single massive document, making it hard to navigate and consuming excessive context window space.

1 / 3

Total

8

/

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 conveys the general domain (reviewing uncommitted code changes) but lacks concrete action verbs, explicit trigger guidance ('Use when...'), and natural user-facing keywords. It reads more like a feature summary than a discriminating skill description that Claude could reliably select from a large pool of skills.

Suggestions

Add an explicit 'Use when...' clause with natural trigger terms like 'review my changes', 'code review', 'uncommitted code', 'git diff', 'staged changes', 'check my code before committing'.

List specific concrete actions the skill performs, e.g., 'Analyzes git diffs, identifies bugs and style issues, suggests refactors, and summarizes changes across modified files'.

Clarify what 'specialized agents' means or remove the jargon—users won't search for 'specialized agents' and it adds ambiguity rather than distinctiveness.

DimensionReasoningScore

Specificity

It names the domain (code review of uncommitted changes) and mentions 'code improvement suggestions' and 'specialized agents', but doesn't list specific concrete actions like 'analyze diffs, check style, suggest refactors'.

2 / 3

Completeness

It describes what the skill does (review uncommitted changes with suggestions) but has no explicit 'Use when...' clause or equivalent trigger guidance, which per the rubric should cap completeness at 2, and the 'what' is also somewhat vague, placing this at 1.

1 / 3

Trigger Term Quality

Includes some relevant terms like 'uncommitted changes', 'code improvement', and 'review', but misses common natural variations users would say such as 'code review', 'diff', 'staged changes', 'git status', or 'check my code'.

2 / 3

Distinctiveness Conflict Risk

The mention of 'local uncommitted changes' and 'specialized agents' provides some distinctiveness, but 'code improvement suggestions' is broad enough to overlap with general code review or linting skills.

2 / 3

Total

7

/

12

Passed

Validation

90%

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

Validation10 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

10

/

11

Passed

Repository
NeoLabHQ/context-engineering-kit
Reviewed

Table of Contents

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