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 problem it solves. It reads as a placeholder or auto-generated stub rather than a functional skill 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, or managing parallel workflows').
Replace the invocation instruction ('invoke with $agent-mesh-coordinator') with functional description content — invocation syntax belongs in the skill body, not the description field.
| 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 like a distributed systems textbook chapter rather than an actionable skill file. It explains well-known concepts (pBFT, Raft, gossip protocols, DHTs, work stealing) that Claude already understands, consuming enormous token budget without providing project-specific value. The few actionable MCP commands are buried in conceptual material, and there is no clear operational workflow for actually coordinating mesh network tasks.
Suggestions
Remove all textbook explanations of distributed systems concepts (pBFT, Raft, gossip, DHTs, Byzantine fault tolerance) and replace with a brief reference to which protocol to use when, trusting Claude's existing knowledge.
Add a clear step-by-step operational workflow: how to initialize a mesh task, distribute work, monitor progress, handle failures, and collect results—with explicit validation checkpoints at each stage.
Split content into a concise SKILL.md overview (~50 lines) with references to separate files like CONSENSUS.md, FAULT-TOLERANCE.md, and LOAD-BALANCING.md for detailed configurations.
Replace illustrative pseudocode Python classes with actual executable MCP tool command sequences that demonstrate real mesh coordination scenarios end-to-end.
| 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. The Python class examples are conceptual illustrations of well-known algorithms, not project-specific executable code. Most content is textbook material that wastes token budget. | 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 consists of pseudocode Python classes (WorkStealingProtocol, HeartbeatMonitor, etc.) that are illustrative rather than executable—they reference undefined functions and can't actually be run. The skill mixes actionable MCP commands with non-actionable conceptual code. | 2 / 3 |
Workflow Clarity | There is no clear step-by-step workflow for how to actually coordinate a mesh network task from start to finish. The content describes many concepts and protocols but never sequences them into a coherent operational workflow with validation checkpoints. The hooks in the frontmatter hint at a workflow but the body doesn't elaborate on when to use which strategy or how to handle failures in practice. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with no references to external files. All content—network architecture, consensus algorithms, failure detection, load balancing, performance metrics, best practices—is inlined in a single massive document. This would benefit enormously from splitting into separate reference files for consensus algorithms, task distribution strategies, and fault tolerance procedures. | 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/ruflo
- Commit
398f7c2
- Reviewed
Table of Contents
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