agent-swarm

Agent skill for swarm - invoke with $agent-swarm

2.27x

Quality

Does it follow best practices?

Impact

100%

2.27x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agents/skills/agent-swarm/SKILL.md

Quality

Discovery

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 is an extremely weak description that fails on every dimension. It provides no information about what the skill does, when it should be used, or what distinguishes it from other skills. It reads more like a label than a functional description that Claude could use for skill selection.

Suggestions

Add concrete actions describing what the swarm agent actually does (e.g., 'Coordinates multiple sub-agents to parallelize tasks such as X, Y, Z').

Add an explicit 'Use when...' clause with natural trigger terms that describe the situations or user requests that should activate this skill.

Replace the invocation instruction ('invoke with $agent-swarm') with a meaningful description of the skill's capabilities and domain, as invocation syntax is not useful for skill selection.

Dimension	Reasoning	Score
Specificity	The description contains no concrete actions whatsoever. 'Agent skill for swarm' is entirely vague and abstract, providing no information about what the skill actually does.	1 / 3
Completeness	The description fails to answer both 'what does this do' and 'when should Claude use it'. There is no explanation of capabilities and no 'Use when...' clause or equivalent trigger guidance.	1 / 3
Trigger Term Quality	The only keyword is 'swarm', which is technical jargon without context. There are no natural user-facing trigger terms that someone would use when needing this skill. The invocation command '$agent-swarm' is not a natural language trigger.	1 / 3
Distinctiveness Conflict Risk	The description is so vague that it provides no clear niche. 'Agent skill for swarm' could mean anything and provides no distinguishing characteristics to differentiate it from other skills.	1 / 3
	Total	4 / 12 Passed

Implementation

14%

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

This skill reads more like a persona description or marketing document than actionable instructions. It is heavily padded with explanatory content about concepts (topologies, agent types, quality standards) that don't help Claude execute tasks, while lacking the concrete workflow guidance, validation steps, and error handling that would make it operationally useful. The MCP tool examples are the strongest element but are undermined by the absence of real workflow integration.

Suggestions

Remove the descriptive lists of topologies, agent types, and quality standards—replace with a concise decision table or flowchart showing when to use each topology/agent type based on task characteristics.

Add a concrete end-to-end workflow example: receive a user request → analyze → init swarm → spawn agents → orchestrate → check status → handle errors → return results, with explicit validation checkpoints after each step.

Add error handling guidance: what to do when swarm_init fails, when agents don't respond, or when task_orchestrate returns errors—include specific retry/fallback patterns.

Split the MCP tool reference into a separate REFERENCE.md file and keep SKILL.md focused on the decision-making workflow and a quick-start example.

Dimension	Reasoning	Score
Conciseness	Extremely verbose with extensive explanations of concepts Claude already knows (what topologies are, what agent types do, generic quality standards). The bullet-point lists of agent types and topologies with descriptions are padding that doesn't add actionable value. The 'Your core responsibilities' and 'Quality standards' sections describe rather than instruct.	1 / 3
Actionability	The JavaScript code block provides concrete MCP tool calls with parameter examples, which is useful. However, the code is illustrative rather than executable in a real workflow—there's no guidance on how to chain these calls together, handle responses, or make decisions based on outputs. The orchestration approach is a generic numbered list without concrete decision criteria.	2 / 3
Workflow Clarity	The 6-step 'orchestration approach' is vague and lacks validation checkpoints. There's no guidance on what to do when agent spawning fails, how to verify swarm health before proceeding, or how to handle errors during orchestration. For a system involving multi-agent deployment and scaling (a complex, potentially destructive operation), the absence of any feedback loops or verification steps is a significant gap.	1 / 3
Progressive Disclosure	The content is a monolithic wall of text with no references to external files and no clear separation between quick-start and advanced content. Everything—topology descriptions, agent types, quality standards, tool reference—is dumped into a single file with no navigation structure.	1 / 3
	Total	5 / 12 Passed

Validation

100%

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 — 11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository: ruvnet/ruflo
Commit: 0f7c750

Reviewed: 3 days ago

Table of Contents

Discovery Implementation Validation

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