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agent-squad-python

Use when building or modifying a Python app that uses the agent-squad Python package — async multi-agent orchestration for Python 3.11+: orchestrator, agents (BedrockLLMAgent, AnthropicAgent, OpenAIAgent, SupervisorAgent, GroundedAgent, ChainAgent, and more), classifier routing (Bedrock, Anthropic, OpenAI), storage (in-memory, DynamoDB, SQL/Turso), retrievers (Amazon KB, Dakera), tools (AgentTools, MCPToolProvider), and custom implementations.

72

Quality

87%

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SecuritybySnyk

Low

Low-risk findings worth noting

SKILL.md
Quality
Evals
Security

Quality

Content

82%Weight 40%Scale 1-5

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

A high-quality, actionable guide with executable examples and clear navigation pointers to source and docs. The main improvement lever is progressive disclosure: the detailed agent/classifier/storage tables and the 'Go deeper' file listing could move into bundled reference files to shorten the SKILL.md overview.

Suggestions

Move the per-agent, classifier, storage, and retriever tables into a bundled reference file (e.g. references/COMPONENTS.md) and summarize only the selection guidance inline, so SKILL.md stays a lean overview.

Trim or externalize the 'Go deeper' file/class listing into a references/SOURCE_MAP.md, keeping just the top entry points (orchestrator.py, agents/agent.py) inline.

Add a one-line 'minimal viable example' near the top (orchestrator + one agent + route_request) so the core workflow is visible before the component catalog.

DimensionReasoningScore

Conciseness

The body is dense and deliberately framed as 'a guide and a map — not an API reference', avoiding basic-concept padding, but at ~400 lines it carries reference-heavy material (the full per-agent table and the 'Go deeper' file/class listing) that could be trimmed or moved. Falls at score 4 — efficient with minor trimmable parts — rather than 5 because not every token earns its place.

4 / 5

Actionability

Provides copy-paste-ready, executable examples covering the common cases: pip extras, `await orchestrator.route_request(...)` with streaming/non-streaming branching, `AgentSquad`/`BedrockLLMAgent` construction, `MCPToolProvider.create`, and a minimal custom `Agent` subclass. Matches the score-5 anchor for fully executable, copy-paste-ready guidance.

5 / 5

Workflow Clarity

'How a turn works' sequences the core flow clearly (construct orchestrator → add agent → await route_request → branch on response.streaming), and the Gotchas section reinforces pitfalls. It is a reference guide rather than a destructive/batch workflow, so no validation feedback loop is required; score 4 reflects a clear sequence without the explicit checkpoints that define a 5.

4 / 5

Progressive Disclosure

No bundle files exist (references/, scripts/, assets/ absent), so all content is inline, but the file is well-sectioned (## When to use what, ## The pieces, ## Gotchas, ## Go deeper) and points one level deep to repo source (`python/src/agent_squad/...`) and docs (`docs/src/content/docs/`) rather than nesting references. Good structure with minor organization gaps — score 4, not 5, because detailed per-component material stays inline instead of splitting into bundled reference files.

4 / 5

Total

17

/

20

Passed

Description

92%Weight 40%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.

A strong, specific description that explicitly pairs a 'Use when...' trigger with a comprehensive enumeration of the framework's capabilities. Its only soft spot is trigger-term breadth — it relies on the package name and 'multi-agent orchestration' without varied synonyms.

DimensionReasoningScore

Specificity

Enumerates concrete capabilities comprehensively — 'orchestrator, agents (BedrockLLMAgent, AnthropicAgent, OpenAIAgent, SupervisorAgent, GroundedAgent, ChainAgent, and more), classifier routing (Bedrock, Anthropic, OpenAI), storage (in-memory, DynamoDB, SQL/Turso), retrievers (Amazon KB, Dakera), tools (AgentTools, MCPToolProvider), and custom implementations'. This matches the score-5 anchor (multiple specific concrete items, comprehensive coverage) and exceeds the score-4 example in breadth.

5 / 5

Completeness

Explicitly answers both: 'what' ('async multi-agent orchestration for Python 3.11+: orchestrator, agents..., classifier routing..., storage..., retrievers..., tools..., and custom implementations') and 'when' ('Use when building or modifying a Python app that uses the agent-squad Python package'). Matches the score-5 anchor with concrete trigger phrases.

5 / 5

Trigger Term Quality

Natural phrases a user of this package would say are present — 'building or modifying a Python app that uses the agent-squad Python package', 'multi-agent orchestration'. Coverage is good but stops short of the synonyms/extensions that define a 5 (no alternate phrasings like 'agent swarm' or file/dependency markers).

4 / 5

Distinctiveness Conflict Risk

Tightly bound to a named package ('agent-squad Python package') with a clear niche (async multi-agent orchestration for Python 3.11+), giving minimal overlap with other skills. Matches the score-5 'clear niche with distinct triggers' anchor.

5 / 5

Total

19

/

20

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.

Validation16 / 16 Passed

Validation for skill structure

No warnings or errors.

Repository
2FastLabs/agent-squad
Reviewed

Table of Contents

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