agent-resource-allocator

Agent skill for resource-allocator - invoke with $agent-resource-allocator

5.00x

Quality

—

Does it follow best practices?

Impact

80%

5.00x

Average score across 3 eval scenarios

Securityby

Passed

No known issues

Quality

Content

15%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

The body is a verbose, monolithic collection of illustrative JavaScript classes with undefined dependencies rather than executable, well-structured guidance. It lacks a clear sequenced workflow and any progressive disclosure via bundle files.

Suggestions

Cut the large class implementations that re-explain known concepts (circuit breakers, RL, genetic optimizers) and keep only the concrete, executable commands and MCP hooks Claude needs.

Replace undefined placeholder classes with real, runnable code or drop the code in favor of specific, actionable instructions.

Add a sequenced workflow with explicit validation checkpoints (e.g., analyze -> predict -> allocate -> verify) for resource allocation, and move lengthy reference material into separate bundle files linked from a concise overview.

Dimension	Reasoning	Score
Conciseness	The ~670-line body is dominated by large code blocks re-implementing concepts Claude already knows (circuit breakers, genetic algorithms, LSTM, reinforcement learning, profiling), padded with unnecessary context.	1 / 3
Actionability	It provides some concrete guidance (npx claude-flow commands, mcp.* calls) but the JavaScript relies on many undefined placeholder classes (CPUAllocator, MultiObjectiveGeneticSolver, DeepQNetworkAgent), so it is not copy-paste executable.	2 / 3
Workflow Clarity	The body enumerates capability classes rather than presenting a sequenced workflow, and there are no validation checkpoints or feedback loops for the batch/destructive allocation operations it describes.	1 / 3
Progressive Disclosure	All content sits in a single monolithic SKILL.md with no bundle files (references/, scripts/, assets/ are absent) and no signaled navigation to separate materials, matching the monolithic anchor.	1 / 3
	Total	5 / 12 Passed

Description

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

The description is generic boilerplate that names a domain and an invocation token but states no concrete capabilities or usage triggers. It fails to answer what the skill does or when to use it.

Suggestions

Rewrite the description in third person listing concrete actions (e.g., allocates CPU/memory/storage, predicts scaling needs, profiles performance).

Add an explicit "Use when..." clause with natural trigger terms a user would say (e.g., resource allocation, capacity planning, scaling, bottlenecks).

Drop the "invoke with $agent-resource-allocator" boilerplate and replace it with capability + trigger phrasing to improve distinctiveness.

Dimension	Reasoning	Score
Specificity	The description "Agent skill for resource-allocator - invoke with $agent-resource-allocator" names only a domain and offers no concrete actions, matching the vague/abstract anchor.	1 / 3
Completeness	It does not state what the skill concretely does ("agent skill" is generic) and has no "Use when..." clause, so both the what and when are missing or very weak.	1 / 3
Trigger Term Quality	The only "triggers" are the invocation token "$agent-resource-allocator" and "resource-allocator", which are technical invocation syntax rather than natural phrases a user would say.	1 / 3
Distinctiveness Conflict Risk	The boilerplate "Agent skill for resource-allocator" could describe nearly any agent skill and provides no distinct triggers, so it would conflict with many skills.	1 / 3
	Total	4 / 12 Passed

Validation

93%

Warnings & errors only

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation — 15 / 16 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	15 / 16 Passed

Repository: ruvnet/claude-flow
Commit: 03d4f84

Reviewed: 2 days ago

Table of Contents

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