agent-resource-allocator
Agent skill for resource-allocator - invoke with $agent-resource-allocator
31
0%
Does it follow best practices?
Impact
80%
5.00xAverage score across 3 eval scenarios
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agents/skills/agent-resource-allocator/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 it should be used, or what domain it operates in. It reads as a placeholder or auto-generated stub rather than a functional skill description.
Suggestions
Replace the entire description with concrete actions the skill performs, e.g., 'Allocates compute resources across services, balances workloads, and manages capacity planning' (adjust to actual functionality).
Add an explicit 'Use when...' clause with natural trigger terms users would say, e.g., 'Use when the user needs to distribute resources, manage capacity, balance workloads, or optimize resource allocation.'
Remove the invocation syntax ('invoke with $agent-resource-allocator') from the description—this is operational metadata, not selection-relevant information, and wastes space that should describe capabilities.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | The description contains no concrete actions whatsoever. 'Agent skill for resource-allocator' is entirely vague—it doesn't describe what the skill actually does, what resources it allocates, or how. | 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 trigger information. | 1 / 3 |
Trigger Term Quality | The only potentially relevant term is 'resource-allocator', which is technical jargon and not something a user would naturally say. There are no natural keywords like 'allocate resources', 'assign capacity', 'distribute workload', etc. | 1 / 3 |
Distinctiveness Conflict Risk | The description is so generic that it's impossible to distinguish from any other skill. 'Resource-allocator' could mean anything from cloud infrastructure provisioning to task scheduling to memory management. | 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 a conceptual architecture document masquerading as an actionable skill. It consists almost entirely of non-executable pseudocode defining fictional classes and methods, with no concrete guidance Claude could actually follow. The content is extremely verbose, lacks any real workflow, and provides no executable commands or verifiable steps.
Suggestions
Replace fictional class definitions with actual executable code or concrete CLI commands with real input/output examples that Claude can use
Define a clear step-by-step workflow for resource allocation tasks (e.g., 1. Collect metrics → 2. Analyze → 3. Allocate → 4. Validate) with explicit validation checkpoints
Reduce content by 80%+ — remove all conceptual class architectures and focus only on what Claude needs to do and how to do it
Add concrete examples with actual inputs and expected outputs for the CLI commands listed in the Operational Commands section
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~500+ lines with massive code blocks that are entirely non-executable pseudocode/conceptual class definitions. Explains concepts Claude already knows (circuit breakers, genetic algorithms, LSTM, reinforcement learning) in exhaustive detail. The vast majority of tokens are wasted on illustrative but non-functional code. | 1 / 3 |
Actionability | None of the code is executable — it references fictional classes (CPUAllocator, LSTMTimeSeriesModel, DeepQNetworkAgent, etc.) that don't exist. The CLI commands at the end use placeholder syntax without concrete examples of inputs/outputs. This is descriptive architecture documentation, not actionable guidance. | 1 / 3 |
Workflow Clarity | There is no clear multi-step workflow or sequenced process. The content presents conceptual class structures and method signatures but never defines a concrete workflow for actually performing resource allocation. No validation checkpoints, no error recovery steps, no decision points are articulated as a usable process. | 1 / 3 |
Progressive Disclosure | The content is a monolithic wall of code blocks with no references to external files and no meaningful content hierarchy. Everything is dumped inline with no navigation structure. Section headers exist but each section is just another massive code block at the same level of detail. | 1 / 3 |
Total | 4 / 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 | |
- Repository
- ruvnet/claude-flow
- Commit
f547cec
- Reviewed
Table of Contents
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