agent-matrix-optimizer
Agent skill for matrix-optimizer - invoke with $agent-matrix-optimizer
38
7%
Does it follow best practices?
Impact
87%
1.40xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-matrix-optimizer/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 description is critically deficient across all dimensions. It functions only as an invocation instruction ('invoke with $agent-matrix-optimizer') rather than a meaningful description of capabilities or usage context. Claude would have virtually no information to determine when to select this skill.
Suggestions
Add concrete actions describing what the skill does, e.g., 'Optimizes matrix computations, performs eigenvalue decomposition, solves linear systems, and benchmarks matrix operations.'
Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user asks about matrix optimization, linear algebra performance, sparse matrix operations, or numerical computation efficiency.'
Remove the invocation instruction from the description (it belongs elsewhere) and replace it with functional content that helps Claude distinguish this skill from others.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description provides no concrete actions whatsoever. 'Agent skill for matrix-optimizer' is entirely vague—it doesn't describe what the skill actually does, only names itself. | 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 'matrix-optimizer', which is a tool name rather than a natural term a user would say. There are no natural language trigger terms like 'optimize', 'matrix operations', 'linear algebra', etc. | 1 / 3 |
Distinctiveness Conflict Risk | The description is so vague that Claude would have no basis to distinguish this skill from others. The term 'matrix-optimizer' is opaque without further explanation of its domain or purpose. | 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 excessively verbose, mixing vague aspirational descriptions (swarm coordination, neural network integration) with partially concrete MCP tool examples. Most sections describe capabilities at a high level without providing actionable, executable guidance. The skill would benefit enormously from being trimmed to its core purpose (matrix analysis via specific MCP tools) with concrete validation workflows and proper progressive disclosure.
Suggestions
Remove or drastically reduce sections that don't provide actionable guidance (Swarm Coordination, Neural Network Integration, Performance Monitoring, Error Analysis, Integration with Other Agents) — these are vague and waste tokens.
Make code examples fully executable by providing complete, self-contained examples with actual matrix data (e.g., small test matrices) rather than referencing undefined variables like 'matrixData' and 'sparseValues'.
Add explicit validation checkpoints to the workflow: after analyzeMatrix, check specific properties and branch with concrete fix-and-retry steps before proceeding to solve.
Extract detailed usage scenarios and integration examples into separate referenced files, keeping SKILL.md as a concise overview with clear pointers to deeper content.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with many sections that describe capabilities Claude already knows or could infer. Sections like 'Swarm Coordination', 'Neural Network Integration', 'Performance Monitoring', and 'Error Analysis' are vague bullet-point lists that add no actionable value. The 'Integration with Flow Nexus' and 'Integration with Claude Flow' sections pad the content significantly without providing executable guidance. | 1 / 3 |
Actionability | The MCP tool call examples in 'Usage Scenarios' are somewhat concrete and show actual tool invocations with parameters, but they use undefined variables (matrixData, sparseValues, rhsVector, systemMatrix) making them not truly executable. Many sections like 'Advanced Features', 'Best Practices', and 'Integration Guidelines' are abstract bullet points with no concrete code or commands. | 2 / 3 |
Workflow Clarity | The 'Complete Matrix Optimization Pipeline' is a vague 5-step list with no concrete commands, validation checkpoints, or error recovery steps. The 'Best Practices' section says 'always analyze matrix properties before solving' but doesn't provide a concrete workflow with validation gates. For a skill involving numerical computation where validation is critical, the lack of explicit validation/feedback loops is a significant gap. | 1 / 3 |
Progressive Disclosure | The content is a monolithic wall of text with no references to external files and no bundle files to support it. All content is inline regardless of depth or relevance, mixing overview-level guidance with detailed examples and aspirational integration descriptions. There is no clear hierarchy or navigation structure. | 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
9d4a9ea
- Reviewed
Table of Contents
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