agent-mesh-coordinator

Agent skill for mesh-coordinator - invoke with $agent-mesh-coordinator

2.60x

Quality

Does it follow best practices?

Impact

99%

2.60x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Optimize this skill with Tessl

npx tessl skill review --optimize ./.agents/skills/agent-mesh-coordinator/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 provides virtually no useful information for skill selection. It only names the skill and its invocation command without describing any capabilities, use cases, or trigger conditions. It fails on every dimension of the rubric.

Suggestions

Add concrete actions describing what mesh-coordinator actually does (e.g., 'Coordinates distributed agent tasks, routes messages between agents, manages agent lifecycle').

Add an explicit 'Use when...' clause with natural trigger terms that describe scenarios where this skill should be selected (e.g., 'Use when orchestrating multiple agents, distributing tasks, or managing inter-agent communication').

Replace the invocation instruction ('invoke with $agent-mesh-coordinator') with functional description content — invocation syntax is not useful for skill selection and wastes description space.

Dimension	Reasoning	Score
Specificity	The description provides no concrete actions whatsoever. 'Agent skill for mesh-coordinator' is entirely abstract with no indication of what the skill actually does.	1 / 3
Completeness	Neither 'what does this do' nor 'when should Claude use it' is answered. The description only states it's an agent skill and how to invoke it, with no functional or contextual information.	1 / 3
Trigger Term Quality	The only keyword is 'mesh-coordinator', which is technical jargon unlikely to be naturally used by users. There are no natural language trigger terms that a user would say when needing this skill.	1 / 3
Distinctiveness Conflict Risk	The description is so vague that it's impossible to distinguish it from any other agent skill. Without knowing what it does, there's no way to determine when it should or shouldn't be selected.	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 like a distributed systems textbook chapter rather than an actionable skill for Claude. It is extremely verbose, explaining well-known concepts (pBFT, Raft, gossip protocols, DHTs) that Claude already understands, while failing to provide a clear, sequenced workflow for actually coordinating mesh network tasks. The few actionable MCP commands are buried among hundreds of lines of illustrative pseudocode and conceptual descriptions.

Suggestions

Reduce content by 70-80%: Remove textbook explanations of distributed systems concepts (pBFT, Raft, gossip, DHTs, Byzantine fault tolerance) and focus only on the specific MCP tool commands and coordination patterns unique to this system.

Add a clear step-by-step workflow: Define the actual sequence for receiving a task, distributing it across the mesh, monitoring progress, handling failures, and collecting results - with explicit validation checkpoints at each stage.

Replace illustrative pseudocode with executable examples: The Python classes are not runnable and serve no practical purpose. Replace them with concrete MCP tool command sequences showing real coordination scenarios.

Split content into overview + referenced files: Move detailed consensus algorithm descriptions, load balancing strategies, and performance metrics into separate referenced documents, keeping SKILL.md as a concise operational guide.

Dimension	Reasoning	Score
Conciseness	Extremely verbose at ~350+ lines. Explains distributed systems concepts (gossip protocols, pBFT, Raft, DHTs, Byzantine fault tolerance) that Claude already knows. Includes extensive pseudocode classes for work stealing, heartbeat monitoring, partition handling, load balancing, and auction-based assignment that are illustrative rather than executable. Most content is textbook distributed systems theory rather than skill-specific guidance.	1 / 3
Actionability	The MCP tool integration section provides some concrete bash commands that could be executed, but the bulk of the content is pseudocode Python classes and YAML descriptions of algorithms. The Python code is illustrative (not executable - missing imports, incomplete class definitions) and the YAML blocks describe concepts rather than provide actionable instructions.	2 / 3
Workflow Clarity	There is no clear step-by-step workflow for how to actually coordinate a mesh network task. The content describes many concepts (consensus algorithms, failure detection, load balancing) but never sequences them into a coherent workflow with validation checkpoints. For a coordinator skill involving distributed operations, the absence of explicit validation steps and error recovery workflows is a significant gap.	1 / 3
Progressive Disclosure	Monolithic wall of text with no references to external files. All content - from network architecture to consensus algorithms to load balancing to performance metrics - is inlined in a single massive document. Content like detailed consensus algorithm descriptions, Python class implementations, and performance metrics could easily be split into referenced files.	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/claude-flow
Commit: 01070ed

Reviewed: 3 days ago

Table of Contents

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