agent-mesh-coordinator
Agent skill for mesh-coordinator - invoke with $agent-mesh-coordinator
40
7%
Does it follow best practices?
Impact
99%
2.60xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-mesh-coordinator/SKILL.mdQuality
Discovery
0%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 to use it, or what user needs it addresses. It reads as a placeholder rather than a functional description for skill selection.
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 — 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, 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 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 more like a distributed systems textbook chapter than an actionable skill for Claude. It extensively explains well-known CS concepts (pBFT, Raft, gossip protocols, DHTs, work stealing) that Claude already understands, while failing to provide a clear, sequenced workflow for actually coordinating mesh network tasks. The MCP tool commands are the only genuinely useful content, but they're buried in hundreds of lines of theoretical pseudocode.
Suggestions
Remove all general distributed systems theory (consensus algorithms, gossip protocols, DHTs, fault tolerance patterns) that Claude already knows, and focus exclusively on the specific MCP tool commands and project-specific configuration needed to operate this mesh coordinator.
Add a clear step-by-step workflow with numbered phases (e.g., 1. Initialize network → 2. Distribute tasks → 3. Monitor consensus → 4. Handle failures → 5. Collect results) with explicit validation checkpoints at each stage.
Extract detailed reference material (consensus configuration options, load balancing parameters, performance metrics) into separate bundle files and reference them from a concise overview in SKILL.md.
Replace pseudocode Python classes with actual executable MCP tool command sequences that demonstrate real task coordination scenarios end-to-end.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~350+ lines. Contains 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 explain general CS concepts rather than providing project-specific configuration or tool usage. | 1 / 3 |
Actionability | The MCP tool integration section provides concrete bash commands that are copy-paste ready, which is valuable. However, the bulk of the content is pseudocode Python classes (WorkStealingProtocol, HeartbeatMonitor, PartitionHandler, etc.) that are illustrative rather than executable, and the YAML blocks for consensus algorithms are descriptive rather than actionable instructions. | 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 many concepts and strategies in parallel without a coherent step-by-step process. There are no validation checkpoints or feedback loops for error recovery despite the complexity and potential for failures in distributed coordination. | 1 / 3 |
Progressive Disclosure | The entire skill is a 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 clear navigation hierarchy or separation of overview from detailed reference material. | 1 / 3 |
Total | 5 / 12 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.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
- Repository
- ruvnet/claude-flow
- Commit
d29d87f
- Reviewed
Table of Contents
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