code-review

Automated code review for pull requests using multiple specialized agents

1.50x

Quality

55%

Does it follow best practices?

Impact

99%

1.50x

Average score across 3 eval scenarios

Securityby

Advisory

Suggest reviewing before use

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Quality

Content

77%

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

This is a well-structured, highly actionable multi-agent code review workflow with clear sequencing, validation steps, and explicit criteria for issue flagging. Its main weakness is moderate verbosity—some content is repeated (false positive criteria appear twice) and the entire workflow lives in one file when parts could be extracted. The specificity of agent types, CLI commands, and link formatting makes this immediately executable.

Suggestions

Extract the false-positive list into a single clearly-labeled section referenced from both steps 4 and 5, rather than duplicating the criteria

Consider extracting agent prompt templates or the detailed inline comment formatting rules into separate referenced files to improve progressive disclosure

Dimension	Reasoning	Score
Conciseness	The skill is fairly detailed and necessarily so given the complexity of the multi-agent workflow, but there is some redundancy (e.g., the false positive list is mentioned twice in steps 4/5 and again at the bottom, and some instructions are repeated across agent descriptions). Some tightening is possible without losing clarity.	2 / 3
Actionability	The skill provides highly specific, concrete instructions: exact agent types to use (haiku/sonnet/opus), specific CLI commands (gh pr view, gh pr comment, gh pr review), precise formatting for GitHub links, explicit criteria for what to flag and what not to flag, and clear examples of validation scenarios. This is copy-paste-ready orchestration guidance.	3 / 3
Workflow Clarity	The 9-step workflow is clearly sequenced with explicit validation checkpoints (step 5 validates step 4's findings, step 6 filters, step 1 gates the entire process). There are clear feedback loops for error recovery (validation agents confirm issues before posting), parallelism is explicitly specified, and conditional branching (step 7) is well-defined.	3 / 3
Progressive Disclosure	The content is a single monolithic file with no references to supporting documents. While the skill is complex enough that separating agent prompt templates or the false-positive list into referenced files would improve organization, the linear step-by-step structure is reasonably navigable. No bundle files are provided to offload content to.	2 / 3
	Total	10 / 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 identifies the domain (code review for PRs) but is too brief and lacks critical detail. It omits a 'Use when...' clause entirely, provides no specific actions beyond the generic 'automated code review,' and misses common trigger term variations like 'PR' or 'review my code.'

Suggestions

Add an explicit 'Use when...' clause with trigger terms like 'review my PR', 'pull request feedback', 'PR review', 'code review', 'merge request'.

List specific concrete actions the skill performs, e.g., 'Checks for bugs, style violations, security issues, and suggests improvements in pull request diffs.'

Include common keyword variations users might say: 'PR', 'pull request', 'code review', 'review changes', 'diff review'.

Dimension	Reasoning	Score
Specificity	Names the domain (code review, pull requests) and mentions 'multiple specialized agents' as a mechanism, but doesn't list specific concrete actions like checking style, finding bugs, suggesting improvements, etc.	2 / 3
Completeness	Describes what it does at a high level but completely lacks a 'Use when...' clause or any explicit trigger guidance for when Claude should select this skill. Per rubric guidelines, missing 'Use when' should cap completeness at 2, and the 'what' is also weak, so this scores a 1.	1 / 3
Trigger Term Quality	Includes relevant terms like 'code review' and 'pull requests' that users would naturally say, but misses common variations like 'PR', 'review my code', 'PR feedback', 'merge request', or file type triggers.	2 / 3
Distinctiveness Conflict Risk	The combination of 'pull requests' and 'multiple specialized agents' provides some distinctiveness, but 'code review' is broad enough to overlap with general code analysis or linting skills.	2 / 3
	Total	7 / 12 Passed

Validation

81%

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 — 9 / 11 Passed

Validation for skill structure

Criteria	Description	Result
allowed_tools_field	'allowed-tools' contains unusual tool name(s)	Warning
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	9 / 11 Passed

Repository: pipecat-ai/pipecat
Commit: 8fe21bf

Reviewed: 5 days ago

Table of Contents

Discovery Implementation Validation

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