agent-topology-optimizer
Agent skill for topology-optimizer - invoke with $agent-topology-optimizer
40
Quality
11%
Does it follow best practices?
Impact
92%
1.58xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-topology-optimizer/SKILL.mdQuality
Discovery
7%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 description is severely deficient, providing only a name and invocation command without any explanation of capabilities, use cases, or trigger conditions. It fails to help Claude understand when to select this skill from a pool of options, as it contains no actionable information about what topology optimization means or what tasks it performs.
Suggestions
Add concrete actions describing what the skill does (e.g., 'Optimizes network topology layouts, reduces node connections, minimizes path lengths').
Include a 'Use when...' clause with natural trigger terms users might say (e.g., 'Use when optimizing network layouts, graph structures, or when user mentions topology, network optimization, or graph efficiency').
Specify the domain and file types or inputs the skill works with (e.g., 'Works with network graphs, mesh structures, or connectivity diagrams').
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description provides no concrete actions whatsoever. 'Agent skill for topology-optimizer' is completely abstract with no indication of what the skill actually does. | 1 / 3 |
Completeness | The description fails to answer both 'what does this do' and 'when should Claude use it'. It only provides an invocation command with no functional description or usage guidance. | 1 / 3 |
Trigger Term Quality | The only keyword is 'topology-optimizer' which is technical jargon. No natural user terms are provided - users wouldn't naturally say 'topology-optimizer' when seeking help. | 1 / 3 |
Distinctiveness Conflict Risk | The specific term 'topology-optimizer' is distinctive enough to avoid conflicts with most other skills, but without knowing what it does, it's unclear if it might overlap with related optimization or topology skills. | 2 / 3 |
Total | 5 / 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 reference document masquerading as an agent skill. It provides comprehensive code examples for topology optimization concepts but fails to give Claude actionable guidance on when and how to invoke this agent, what inputs are required, or what outputs to expect. The content would benefit from radical condensation into a focused overview with clear invocation patterns.
Suggestions
Reduce to a concise overview (under 100 lines) with clear invocation syntax: when to use this agent, required inputs, expected outputs
Add a clear workflow section: 1) Analyze current topology, 2) Generate recommendations, 3) Validate changes, 4) Apply optimization with rollback plan
Move detailed algorithm implementations and code examples to separate reference files (e.g., ALGORITHMS.md, MCP_INTEGRATION.md)
Include concrete input/output examples showing actual topology optimization scenarios with expected results
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at 700+ lines with extensive code that explains concepts Claude already knows (genetic algorithms, simulated annealing, graph partitioning). Much of this is reference material that could be in separate files or omitted entirely. | 1 / 3 |
Actionability | Contains concrete JavaScript code examples and CLI commands, but the code is largely illustrative/pseudocode-like (classes with undefined dependencies like 'new HierarchicalTopology()', 'new LatencyAnalyzer()'). Not copy-paste executable without significant additional context. | 2 / 3 |
Workflow Clarity | No clear step-by-step workflow for when or how to use this agent. The content describes capabilities and code patterns but lacks sequenced instructions, validation checkpoints, or decision points for the user/Claude to follow. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with no references to external files. All content is inline including detailed algorithm implementations, MCP integration code, and metrics definitions that should be split into separate reference documents. | 1 / 3 |
Total | 5 / 12 Passed |
Validation
90%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 10 / 11 Passed
Validation for skill structure
| Criteria | Description | Result |
|---|---|---|
skill_md_line_count | SKILL.md is long (813 lines); consider splitting into references/ and linking | Warning |
Total | 10 / 11 Passed | |
- Repository
- ruvnet/claude-flow
- Commit
b2618f9
- Reviewed
Table of Contents
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