agent-adaptive-coordinator
Agent skill for adaptive-coordinator - invoke with $agent-adaptive-coordinator
36
0%
Does it follow best practices?
Impact
100%
1.51xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-adaptive-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 domain it operates in. It reads as a placeholder rather than a functional description, making it impossible for Claude to correctly select this skill from a pool of available options.
Suggestions
Add concrete actions describing what the adaptive-coordinator actually does (e.g., 'Coordinates multi-step workflows by dynamically routing tasks to specialized agents').
Add an explicit 'Use when...' clause with natural trigger terms that describe the situations where this skill should be selected (e.g., 'Use when the user needs to orchestrate complex tasks across multiple agents or coordinate parallel workstreams').
Remove the invocation syntax ('invoke with $agent-adaptive-coordinator') from the description and replace it with domain-specific keywords that help distinguish this skill from others.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description contains no concrete actions whatsoever. 'Agent skill for adaptive-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 how to invoke it, not what it does or when to use it. | 1 / 3 |
Trigger Term Quality | The only keyword is 'adaptive-coordinator', which is technical jargon and not something a user would naturally say. There are no natural trigger terms present. | 1 / 3 |
Distinctiveness Conflict Risk | The description is so vague that it provides no distinguishing characteristics. 'Adaptive-coordinator' could overlap with any coordination, orchestration, or management skill. | 1 / 3 |
Total | 4 / 12 Passed |
Implementation
0%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 aspirational design document rather than an actionable skill file. It is extremely verbose, filled with non-executable pseudocode Python classes and speculative MCP commands, and lacks any concrete, step-by-step workflow that Claude could actually follow. The content reads more like a software architecture proposal than operational instructions, explaining concepts Claude already understands while failing to provide the specific, executable guidance needed.
Suggestions
Replace all pseudocode Python classes with actual executable MCP commands or concrete step-by-step instructions that Claude can follow directly when coordinating a swarm.
Reduce the content to under 100 lines by removing the KPI lists, best practices, ML optimization advice, and conceptual architecture descriptions—focus only on the decision logic and concrete commands for topology switching.
Add a clear, numbered workflow with explicit validation checkpoints (e.g., 'After switching topology, run X command and verify Y metric is above Z threshold before proceeding').
Extract detailed reference material (topology decision matrix, rollback mechanisms, performance metrics) into separate linked files and keep SKILL.md as a concise overview with navigation.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~350+ lines. Contains extensive Python class definitions that are conceptual pseudocode (not executable in the MCP context), lengthy YAML descriptions of topology switching conditions, and detailed explanations of ML concepts Claude already understands. The ASCII architecture diagram, KPI lists, and best practices sections add significant bulk without actionable value. | 1 / 3 |
Actionability | Despite containing code blocks, almost none of it is executable. The Python classes (WorkloadAnalyzer, TopologyOptimizer, AdaptiveAgentAllocator, PredictiveLoadManager, TopologyRollback) are all pseudocode with undefined methods like self.collect_performance_metrics() and self.initialize_ml_model(). The MCP commands in bash blocks reference tools that may not exist (bottleneck_analyze, topology_optimize, load_balance, trend_analysis, swarm_scale) without any verification. No concrete, copy-paste-ready workflow exists. | 1 / 3 |
Workflow Clarity | While there is a 4-phase 'Seamless Migration Process' in YAML, it contains only abstract bullet points with no concrete commands or validation checkpoints. The overall skill lacks a clear step-by-step workflow for how the coordinator should actually operate. There are no explicit validation steps or feedback loops with concrete commands—just conceptual descriptions of what should happen. | 1 / 3 |
Progressive Disclosure | The entire skill is a monolithic wall of text with no references to external files. All content—from architecture diagrams to Python classes to KPI definitions to best practices—is inlined in a single massive document. There is no separation of overview from detailed reference material, and no navigation aids or links to supplementary files. | 1 / 3 |
Total | 4 / 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
01070ed
- Reviewed
Table of Contents
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