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

67%

Does it follow best practices?

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Securityby

Passed

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tessl review fix ./skills/antigravity-agent-orchestration-multi-agent-optimize/SKILL.md

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 skill body is organized into clear sections but is heavily padded with buzzword prose and skeleton/pseudocode examples rather than executable guidance, and it lacks any progressive disclosure to supporting files. Validation in the core workflow is mentioned only abstractly.

Suggestions

Strip the 'Role: AI-Powered...' Context section and abstract buzzword bullet lists; keep only concrete guidance Claude does not already know.

Replace skeleton code (semantic_truncate, `pass` bodies, undefined agent/tracker classes) with complete, runnable examples or remove the code blocks.

Add explicit validation checkpoints with concrete commands and an error-recovery feedback loop to the Instructions workflow, since orchestration changes are risky.

Dimension	Reasoning	Score
Conciseness	The body is padded with marketing fluff ('advanced AI-driven framework designed to holistically improve system performance', 'Leveraging cutting-edge AI orchestration techniques') and abstract buzzword bullets ('Intelligent result memoization', 'Machine learning-driven improvement') that explain concepts Claude already knows.	1 / 3
Actionability	Code blocks are present but not executable — compress_context calls an undefined semantic_truncate, select_optimal_model is just `pass`, and agents/trackers are referenced but never defined — matching the pseudocode-instead-of-executable-code anchor.	2 / 3
Workflow Clarity	The four-step Instructions list a sequence but validation is only abstract ('Validate improvements with repeatable tests and rollbacks') with no concrete checkpoint or error-recovery feedback loop, so it is capped at 2 for risky orchestration changes.	2 / 3
Progressive Disclosure	All content sits inline in a single ~240-line SKILL.md with no bundle files or external references, so while section structure exists, detailed code and workflows that should be split out are not progressively disclosed.	2 / 3
	Total	7 / 12 Passed

Description

100%

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

A well-crafted description that concisely names concrete capabilities and pairs them with an explicit, natural-language use trigger. It answers both 'what' and 'when' without fluff.

Dimension	Reasoning	Score
Specificity	Lists multiple concrete actions — 'coordinated profiling, workload distribution, and cost-aware orchestration' — rather than vague language, matching the multiple-specific-actions anchor.	3 / 3
Completeness	It explicitly states both what it does (optimize multi-agent systems via profiling/distribution/orchestration) and when to use it via an explicit 'Use when' trigger clause.	3 / 3
Trigger Term Quality	The 'Use when improving agent performance, throughput, or reliability' clause uses natural phrases a user would actually say, giving good coverage of trigger terms.	3 / 3
Distinctiveness Conflict Risk	The 'multi-agent' niche plus specific triggers (throughput, reliability, cost-aware orchestration) make it clearly distinguishable and unlikely to fire for unrelated skills.	3 / 3
	Total	12 / 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
Path: skills/antigravity-agent-orchestration-multi-agent-optimize/SKILL.md
Commit: c27161a

Reviewed: 3 days ago

Table of Contents

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