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code-review-ai-ai-review

You are an expert AI-powered code review specialist combining automated static analysis, intelligent pattern recognition, and modern DevOps practices. Leverage AI tools (GitHub Copilot, Qodo, GPT-5, C

41

Quality

41%

Does it follow best practices?

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SecuritybySnyk

Low

Low-risk findings worth noting

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tessl review fix ./skills/code-review-ai-ai-review/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

46%Scale 1-5

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

This skill is a comprehensive but excessively verbose reference document that reads more like a knowledge base article than a focused skill instruction. It contains good code examples and covers many aspects of AI-powered code review, but fails to respect token budget by inlining extensive reference material (OWASP Top 10, SOLID principles, scalability red flags) that Claude already knows. The lack of bundle files means all content is crammed into one file with no progressive disclosure.

Suggestions

Extract reference material (OWASP Top 10, SOLID principles, scalability red flags, architecture anti-patterns) into separate bundle files and reference them from the main skill

Remove explanations of concepts Claude already knows (what SQL injection is, what N+1 queries are, what SOLID stands for) and focus only on the specific workflow and tool integration patterns

Add explicit error handling and validation steps to the orchestrator workflow (e.g., what to do when static analysis tools fail, how to handle API rate limits, retry logic)

Complete the incomplete code examples (define `get_pr_diff()`, `to_github_comment()`, `detect_n_plus_1_queries` helper functions) or remove them to avoid misleading copy-paste attempts

DimensionReasoningScore

Conciseness

Extremely verbose at ~350+ lines. Extensively explains concepts Claude already knows (OWASP Top 10 list, SOLID principles, what N+1 queries are). Much of this is reference material that adds token cost without teaching Claude anything new. The 'Use this skill when' and 'Do not use this skill when' sections are tautological filler.

2 / 5

Actionability

Contains concrete, mostly executable code examples across Python, TypeScript, Go, YAML, and bash. The GitHub Actions workflow and orchestrator class are largely copy-paste ready. However, some code is illustrative rather than truly executable (e.g., `detect_n_plus_1_queries` references undefined functions, `ReviewIssue.to_github_comment()` and `get_pr_diff()` are never defined).

4 / 5

Workflow Clarity

The 'Automated Code Review Workflow' section provides a clear sequence (triage → static analysis → AI review → routing), and the CI/CD integration shows a quality gate. However, there are no explicit validation/feedback loops for error recovery in the workflow steps themselves. The orchestrator lacks error handling or retry logic for when static analysis or AI review fails.

3 / 5

Progressive Disclosure

This is a monolithic wall of content (~350+ lines) with no bundle files to support it. References `resources/implementation-playbook.md` but no bundle exists. The OWASP list, architecture analysis, performance review, and security sections should clearly be in separate referenced files rather than inlined. The single reference to an external file is unverifiable.

2 / 5

Total

11

/

20

Passed

Description

36%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.

This description is truncated mid-sentence, which severely undermines its utility. Even the visible portion relies heavily on buzzwords ('AI-powered,' 'intelligent pattern recognition,' 'modern DevOps practices') rather than concrete actions. It also uses second-person voice ('You are') which is inappropriate for a skill description, and lacks any 'Use when...' guidance.

Suggestions

Complete the truncated description and add an explicit 'Use when...' clause with natural trigger phrases like 'review my code,' 'pull request review,' 'check for bugs,' or 'code quality.'

Replace abstract buzzwords ('intelligent pattern recognition,' 'modern DevOps practices') with concrete actions such as 'identifies security vulnerabilities, flags code smells, checks style consistency, reviews pull requests.'

Switch from second-person voice ('You are an expert') to third-person voice ('Performs automated code review, analyzes diffs for...').

DimensionReasoningScore

Specificity

The description names the domain ('code review') and mentions some broad categories like 'static analysis' and 'pattern recognition,' but these are abstract concepts rather than concrete actions. No specific operations like 'flag unused variables' or 'check for security vulnerabilities' are listed.

2 / 5

Completeness

The description is truncated mid-sentence, so it cannot fully answer 'what' or 'when.' There is a vague sense of 'what' (code review with AI tools) but no 'when' clause or trigger guidance whatsoever. The truncation alone severely limits completeness.

2 / 5

Trigger Term Quality

Contains some relevant keywords like 'code review,' 'static analysis,' 'GitHub Copilot,' and 'DevOps,' but the description appears truncated and lacks natural user phrases like 'review my PR,' 'pull request,' 'lint,' or 'code quality.' The tool names (GPT-5, Qodo) are not typical user trigger terms.

3 / 5

Distinctiveness Conflict Risk

While 'code review' is somewhat specific, the broad mention of 'static analysis,' 'pattern recognition,' and 'DevOps practices' could overlap with linting skills, CI/CD skills, security scanning skills, or general coding assistance skills. The truncation prevents any narrowing of scope.

3 / 5

Total

10

/

20

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

Table of Contents

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