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 findings from the security scan

Fix and improve this skill with Tessl

tessl review fix ./.agents/skills/agent-mesh-coordinator/SKILL.md

Quality

Content

0%Scale 1-3

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 actionable instructions for Claude. It spends hundreds of tokens explaining well-known CS concepts (BFT, Raft, gossip protocols, DHTs, work stealing) that Claude already understands, while providing almost no concrete guidance on what to actually do when invoked as a mesh coordinator. The Python code examples are illustrative pseudocode, not executable implementations tied to the actual MCP tooling.

Suggestions

Remove all textbook-level distributed systems explanations (BFT, Raft, gossip theory, etc.) and replace with a concise summary of which protocol to use when, focused on the specific MCP tools available.

Replace illustrative Python pseudocode classes with concrete, executable MCP tool command sequences showing the actual workflow: receive task → distribute to peers → monitor → handle failures → collect results.

Add a clear step-by-step operational workflow with numbered steps and validation checkpoints (e.g., verify peer connectivity before distributing tasks, confirm consensus before proceeding).

Extract detailed reference material (consensus algorithm details, load balancing strategies, performance metrics) into separate bundle files and reference them from a concise SKILL.md overview.

Dimension	Reasoning	Score
Conciseness	Extremely verbose at ~350+ lines. Includes extensive theoretical explanations of well-known distributed systems concepts (Byzantine fault tolerance, Raft consensus, gossip protocols, DHTs) that Claude already knows. The Python class examples are illustrative pseudocode explaining general CS concepts rather than project-specific instructions. Most content is textbook-level distributed systems knowledge that wastes token budget.	1 / 3
Actionability	Despite containing code blocks, nearly all code is pseudocode/illustrative Python classes (WorkStealingProtocol, TaskAuction, HeartbeatMonitor, etc.) that are not executable or copy-paste ready. The MCP tool commands in bash blocks appear to be the only actionable content, but they lack context on when/how to use them in practice. The skill describes distributed systems concepts rather than instructing Claude on specific actions to take.	1 / 3
Workflow Clarity	There is no clear step-by-step workflow for how to actually coordinate a mesh network task. The content presents concepts (gossip algorithms, consensus protocols, failure detection) as isolated topics without sequencing them into an operational workflow. No validation checkpoints exist, and there's no guidance on what to do when receiving a task — just theoretical descriptions of how mesh networks work in general.	1 / 3
Progressive Disclosure	Monolithic wall of text with no references to external files and no bundle files provided. All content — from network architecture theory to consensus algorithms to load balancing strategies — is dumped inline. Content that could be separated (e.g., consensus algorithm details, Python class examples, performance metrics) bloats the main file unnecessarily.	1 / 3
	Total	4 / 12 Passed

Description

0%Scale 1-3

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 triggers should activate it. It reads more like a stub or placeholder than a functional skill description.

Suggestions

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

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

Replace the invocation instruction ('invoke with $agent-mesh-coordinator') with functional description content — invocation syntax belongs in the skill body, not the description field used for skill selection.

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, providing 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.	1 / 3
Distinctiveness Conflict Risk	The description is so vague that it's impossible to distinguish it from any other agent skill. 'Mesh-coordinator' gives a slight hint of domain but without any explanation of what mesh coordination entails, it could conflict with anything.	1 / 3
	Total	4 / 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
Path: .agents/skills/agent-mesh-coordinator/SKILL.md
Commit: 913f9ea

Reviewed: 3 days ago

Table of Contents

Discovery Implementation Validation

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