agent-orchestration-multi-agent-optimize

Optimize multi-agent systems with coordinated profiling, workload distribution, and cost-aware orchestration. Use when improving agent performance, throughput, or reliability.

Quality

—

Does it follow best practices?

Impact

—

No eval scenarios have been run

Securityby

Passed

No known issues

Quality

Content

35%

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

The body is over-long and padded with marketing-style framing and generic concept restatements, while its code examples are incomplete rather than executable. Workflow sequencing exists but lacks concrete validation checkpoints, and nothing is offloaded to reference files.

Suggestions

Remove the 'Role: AI-Powered...' marketing context and trim generic bullet-only sections (4, 6, 7, 8) to their actionable essentials to cut padding.

Make code examples executable: implement select_optimal_model and define or document the helper functions (semantic_truncate, aggregate_performance_metrics, DatabasePerformanceAgent) instead of leaving undefined calls.

Add explicit validation checkpoints to the workflow (e.g., baseline-measure -> change -> regression-test -> rollback-if-regressed) rather than the vague 'repeatable tests' instruction.

Dimension	Reasoning	Score
Conciseness	Padding throughout — the 'AI-Powered Multi-Agent Performance Engineering Specialist' role and 'advanced AI-driven framework... cutting-edge AI orchestration techniques' context is marketing fluff, and several sections restate generic concepts Claude already knows ('Asynchronous agent processing', 'Predictive caching').	1 / 3
Actionability	Concrete Python is present (profiler, orchestrator, cost optimizer classes) but it is incomplete: select_optimal_model is a bare pass, and core helpers like semantic_truncate, aggregate_performance_metrics, and DatabasePerformanceAgent are undefined.	2 / 3
Workflow Clarity	The Instructions section sequences four steps and the Safety section calls for regression testing, but validation is vague ('repeatable tests') with no explicit checkpoints or error-recovery feedback loop for risky orchestration changes.	2 / 3
Progressive Disclosure	No bundle files exist and the 240+ line body is a monolithic single file with generic API/catalog content kept inline that could be split out; organization is present but content is not appropriately separated or navigable.	2 / 3
	Total	7 / 12 Passed

Description

77%

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 well-formed with explicit what-and-when guidance and several concrete capabilities. It is held back only by trigger terms that are more technical than naturally user-spoken and modest overlap risk with generic optimization skills.

Dimension	Reasoning	Score
Specificity	Names the multi-agent domain and multiple concrete actions — 'coordinated profiling, workload distribution, and cost-aware orchestration' — matching the multiple-specific-actions anchor.	3 / 3
Completeness	Explicitly states both what it does ('Optimize multi-agent systems with...') and when to use it ('Use when improving agent performance, throughput, or reliability'), satisfying the what-and-when anchor.	3 / 3
Trigger Term Quality	Triggers exist ('improving agent performance, throughput, or reliability') but lean technical and miss natural user phrasings like making agents faster or reducing costs, so not full coverage.	2 / 3
Distinctiveness Conflict Risk	Multi-agent orchestration is a niche, but 'performance, throughput, or reliability' could overlap with general optimization skills, so it is somewhat specific yet not clearly distinct.	2 / 3
	Total	10 / 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
frontmatter_unknown_keys	Unknown frontmatter key(s) found; consider removing or moving to metadata	Warning

	Total	15 / 16 Passed

Repository: boisenoise/skills-collections
Commit: f36337d

Reviewed: 2 days ago

Table of Contents

Discovery Implementation Validation

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