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.
47
Quality
35%
Does it follow best practices?
Impact
Pending
No eval scenarios have been run
Passed
No known issues
Optimize this skill with Tessl
npx tessl skill review --optimize ./.agent/skills/agent-orchestration-multi-agent-optimize/SKILL.mdQuality
Discovery
N/ABased on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.
Something went wrong
Implementation
35%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill functions primarily as a table of contents rather than actionable guidance. While it correctly defers detailed content to sub-skills, the main file lacks any concrete examples, executable code, or specific commands. The 16 sub-skill references would benefit from logical grouping, and the core instructions need concrete implementation details.
Suggestions
Add at least one concrete, executable code example in the main file (e.g., a basic profiling snippet or metric collection command) to demonstrate the workflow
Replace the abstract 4-step instructions with specific commands or tool invocations that Claude can actually execute
Group the 16 sub-skills into logical categories (e.g., 'Profiling', 'Optimization', 'Cost Management', 'Workflows') with brief descriptions of when to use each
Remove the unnecessary 'Role:' header and emoji decorations to improve token efficiency
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | The content is reasonably efficient with clear sections, but includes unnecessary role labeling ('Role: AI-Powered Multi-Agent Performance Engineering Specialist') and emoji decorations that add no value. The numbered knowledge modules list is verbose when a simpler grouped reference would suffice. | 2 / 3 |
Actionability | The instructions are vague and abstract ('Establish baseline metrics', 'Profile agent workloads') without any concrete code, commands, or specific examples. Everything actionable is deferred to sub-skills with no executable guidance in the main file. | 1 / 3 |
Workflow Clarity | The 4-step instruction sequence provides a logical flow with validation mentioned ('Validate improvements with repeatable tests'), but lacks explicit checkpoints, specific validation commands, or error recovery steps. The workflow is too abstract to guide actual implementation. | 2 / 3 |
Progressive Disclosure | References to 16 sub-skills are present and one-level deep, but the organization is poor - a flat numbered list of 16 items without grouping or clear signaling of what each contains. The main file provides almost no actionable overview content, making it overly dependent on sub-files. | 2 / 3 |
Total | 7 / 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 |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- Dokhacgiakhoa/antigravity-ide
- Commit
3395991
- Reviewed
Table of Contents
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