crewai-multi-agent

Multi-agent orchestration framework for autonomous AI collaboration. Use when building teams of specialized agents working together on complex tasks, when you need role-based agent collaboration with memory, or for production workflows requiring sequential/hierarchical execution. Built without LangChain dependencies for lean, fast execution.

Quality

86%

Does it follow best practices?

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Securityby

Low

Low-risk findings worth noting

Quality

Content

72%

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

The content is highly actionable with executable code and well-structured progressive disclosure to real reference files. It is let down by some cross-section duplication and the absence of explicit validation checkpoints in its setup workflow.

Suggestions

Consolidate the repeated Agent/Task/Crew construction examples into one canonical block and reference it from Quick start, Core concepts, and Process types to remove duplication.

Drop or trim the 'CrewAI vs alternatives' table since the 'Use alternatives instead' list already covers the same distinctions.

Add an explicit validation step to the Quick start workflow (e.g., verify the crew ran without errors and inspect result.tasks_output) to create a feedback checkpoint before treating the run as complete.

Dimension	Reasoning	Score
Conciseness	The body is mostly lean reference material but duplicates Agent/Task/Crew construction across Quick start, Core concepts, and Process types, and the 'CrewAI vs alternatives' table restates the earlier 'Use alternatives' section; it is efficient but could be tightened, matching the mostly-efficient-but-could-tighten anchor rather than the every-token-earns-its-place anchor at 3.	2 / 3
Actionability	Throughout it provides executable, copy-paste-ready pip and CLI commands plus complete annotated Python and YAML examples, matching the fully-executable-and-copy-paste-ready anchor.	3 / 3
Workflow Clarity	Quick start gives an install-create-install-run sequence and best-practice guardrails (max_iter, max_rpm), but there are no explicit validation checkpoints or feedback loops on the setup/run path, matching the steps-listed-but-checkpoints-missing anchor rather than the explicit-validation anchor at 3.	2 / 3
Progressive Disclosure	The body is a well-organized overview with one-level-deep, clearly signaled references to flows.md, tools.md, and troubleshooting.md — all confirmed present in references/ — matching the clear-overview-with-one-level-deep-references anchor.	3 / 3
	Total	10 / 12 Passed

Description

100%

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 specific, well-triggered, complete, and clearly distinguished from adjacent frameworks. It names concrete capabilities and provides explicit 'Use when' guidance with natural trigger phrasing.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete capabilities — 'building teams of specialized agents', 'role-based agent collaboration with memory', 'sequential/hierarchical execution', 'production workflows' — matching the multiple-specific-actions anchor rather than the domain-plus-some-actions anchor at 2.	3 / 3
Completeness	Explicitly answers both what ('Multi-agent orchestration framework for autonomous AI collaboration') and when via an explicit 'Use when...' clause, matching the clearly-answers-both anchor.	3 / 3
Trigger Term Quality	'Use when building teams of specialized agents', 'when you need role-based agent collaboration', 'production workflows requiring sequential/hierarchical execution' are natural phrases a user would say, giving good coverage; not a 2 because it goes beyond a single keyword with missing variations.	3 / 3
Distinctiveness Conflict Risk	'Built without LangChain dependencies' plus the role-based multi-agent / Crews+Flows niche gives a clear, distinct trigger space unlikely to fire for the wrong skill.	3 / 3
	Total	12 / 12 Passed

Validation

93%

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 — 15 / 16 Passed

Validation for skill structure

Criteria	Description	Result
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: Orchestra-Research/AI-Research-SKILLs
Path: 14-agents/crewai/SKILL.md
Commit: 773a529

Reviewed: about 13 hours ago

Table of Contents

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