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 is essentially a placeholder rather than a functional description.

Suggestions

Add concrete actions describing what mesh-coordinator actually does (e.g., 'Orchestrates multi-agent workflows, routes tasks between agents, manages agent communication and dependencies').

Add an explicit 'Use when...' clause with natural trigger terms that describe scenarios where this skill should be selected (e.g., 'Use when coordinating multiple agents, distributing tasks across services, or managing parallel workflows').

Replace the invocation instruction ('invoke with $agent-mesh-coordinator') with functional description content — invocation details belong 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, 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 avoid conflicts with 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 is an extensive theoretical reference on distributed systems concepts rather than an actionable coordination guide. It explains well-known algorithms (pBFT, Raft, gossip protocols, DHTs) that Claude already understands, while failing to provide a clear operational workflow for actually using the mesh coordinator tools. The content would benefit enormously from being reduced to ~50 lines of concrete tool usage with a clear step-by-step workflow.

Suggestions

Remove all textbook distributed systems explanations (Byzantine fault tolerance theory, Raft consensus details, gossip protocol descriptions) that Claude already knows, and focus only on tool-specific commands and configurations.

Add a clear sequential workflow: 1) Initialize mesh → 2) Distribute tasks → 3) Monitor consensus → 4) Validate results → 5) Handle failures, with explicit validation checkpoints at each step.

Replace pseudocode Python classes with actual executable MCP tool commands showing expected inputs and outputs for each operation.

Extract detailed algorithm references and performance metrics into separate bundle files, keeping SKILL.md as a concise operational guide with links to deeper material.

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 pseudocode classes for work stealing, heartbeat monitoring, partition handling, and load balancing are textbook implementations that add no novel, actionable value specific to this tool ecosystem.	1 / 3
Actionability	The MCP tool integration section provides concrete bash commands that are somewhat actionable, but the bulk of the content is pseudocode Python classes and YAML descriptions of theoretical algorithms that aren't directly executable. The actual tool commands (mcp__claude-flow__*) are the only actionable parts, but they lack context on expected outputs or error handling.	2 / 3
Workflow Clarity	There is no clear sequential workflow for how to actually coordinate a mesh network task from start to finish. The content presents isolated concepts (consensus algorithms, load balancing, failure detection) without sequencing them into a coherent operational workflow. No validation checkpoints or feedback loops are defined for the coordination process despite this being a complex multi-step distributed operation.	1 / 3
Progressive Disclosure	Monolithic wall of text with no references to external files and no bundle files to support it. All content—from network architecture theory to consensus algorithms to load balancing strategies—is inlined in a single massive document with no progressive structure or navigation aids.	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: 619b263

Reviewed: about 9 hours ago

Table of Contents

Discovery Implementation Validation

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