agent-resource-allocator
Agent skill for resource-allocator - invoke with $agent-resource-allocator
Install with Tessl CLI
npx tessl i github:ruvnet/claude-flow --skill agent-resource-allocator36
Does it follow best practices?
If you maintain this skill, you can automatically optimize it using the tessl CLI to improve its score:
npx tessl skill review --optimize ./path/to/skillEvaluation — 80%
↑ 5.00xAgent success when using this skill
Validation for skill structure
Discovery
0%Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
This description is critically deficient across all dimensions. It provides only a name and invocation command without explaining what resources are allocated, what actions the skill performs, or when Claude should select it. This would be nearly impossible to correctly match against user requests.
Suggestions
Define what 'resources' means in this context and list specific actions (e.g., 'Allocates CPU, memory, and storage resources for cloud deployments' or 'Assigns team members to project tasks').
Add a 'Use when...' clause with natural trigger terms users would actually say (e.g., 'Use when the user asks about distributing workload, assigning capacity, or balancing resources').
Remove the invocation syntax from the description - this is metadata, not selection criteria - and replace with capability-focused content.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description contains no concrete actions whatsoever. 'Agent skill for resource-allocator' is completely abstract with no indication of what the skill actually does. | 1 / 3 |
Completeness | Missing both 'what' and 'when'. The description only provides invocation syntax ('$agent-resource-allocator') but explains neither what the skill does nor when to use it. | 1 / 3 |
Trigger Term Quality | Contains only technical jargon ('agent skill', 'resource-allocator') with no natural keywords a user would say. 'Resource-allocator' is not a term users naturally use in requests. | 1 / 3 |
Distinctiveness Conflict Risk | Extremely generic - 'resource-allocator' could mean anything from memory management to project staffing to budget allocation. No clear niche or distinct triggers. | 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 an extensive code showcase rather than actionable guidance. It presents sophisticated concepts (ML-based scaling, circuit breakers, genetic algorithms) through illustrative but non-executable code, without clear workflows or validation steps. The content would benefit from dramatic reduction to essential commands and patterns, with detailed implementations moved to referenced files.
Suggestions
Reduce to a concise overview (50-100 lines) with essential CLI commands and one complete, executable example for the most common use case
Add a clear numbered workflow for resource allocation tasks with explicit validation checkpoints (e.g., 'verify allocation applied' before proceeding)
Move detailed code implementations to separate reference files (e.g., PREDICTIVE_SCALING.md, CIRCUIT_BREAKER.md) and link from a brief overview
Replace illustrative pseudocode with actual executable examples using real MCP tool calls that can be copy-pasted
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive code that explains concepts Claude already knows (circuit breakers, genetic algorithms, LSTM models). The 500+ lines could be reduced to ~50 lines of actionable guidance without losing essential information. | 1 / 3 |
Actionability | Contains concrete code examples and CLI commands, but the code is illustrative pseudocode with undefined dependencies (CPUAllocator, MemoryAllocator, etc.) rather than executable implementations. The MCP integration shows real tool calls but lacks complete working examples. | 2 / 3 |
Workflow Clarity | No clear step-by-step workflow for resource allocation tasks. The content presents disconnected code blocks and concepts without sequencing or validation checkpoints. Missing feedback loops for operations that could fail. | 1 / 3 |
Progressive Disclosure | Monolithic wall of code with no references to external files for detailed implementations. All content is inline regardless of complexity. No clear hierarchy between quick-start usage and advanced features. | 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 (679 lines); consider splitting into references/ and linking | Warning |
Total | 10 / 11 Passed | |
- Reviewed
Table of Contents
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