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.
46
33%
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 ./skills/antigravity-agent-orchestration-multi-agent-optimize/SKILL.mdQuality
Discovery
67%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 has good structural completeness with an explicit 'Use when...' clause, but suffers from somewhat abstract, buzzword-heavy language in its capability listing. The terms 'coordinated profiling', 'workload distribution', and 'cost-aware orchestration' sound impressive but don't convey concrete actions. The trigger terms could be broader to capture more natural user phrasings.
Suggestions
Replace abstract phrases like 'coordinated profiling' and 'cost-aware orchestration' with concrete actions such as 'profile agent execution times, distribute tasks across agents, optimize API call costs, and manage agent coordination patterns'.
Expand trigger terms in the 'Use when...' clause to include natural variations like 'agent coordination', 'scaling agents', 'agent latency', 'multi-agent architecture', or 'agent pipeline optimization'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain (multi-agent systems) and lists some actions (coordinated profiling, workload distribution, cost-aware orchestration), but these are somewhat abstract and buzzword-heavy rather than concrete, actionable tasks like 'extract text' or 'fill forms'. | 2 / 3 |
Completeness | Explicitly answers both 'what' (optimize multi-agent systems with profiling, workload distribution, orchestration) and 'when' ('Use when improving agent performance, throughput, or reliability'), with a clear 'Use when...' clause. | 3 / 3 |
Trigger Term Quality | Includes some relevant terms like 'multi-agent systems', 'agent performance', 'throughput', and 'reliability', but these are fairly technical. Missing common natural variations users might say such as 'agent coordination', 'load balancing', 'scaling agents', 'agent latency', or 'multi-agent architecture'. | 2 / 3 |
Distinctiveness Conflict Risk | The multi-agent focus provides some distinctiveness, but terms like 'performance', 'throughput', and 'reliability' are generic enough to overlap with general performance optimization or system monitoring skills. 'Orchestration' could also conflict with container/workflow orchestration skills. | 2 / 3 |
Total | 9 / 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 verbose, abstract document that reads more like a marketing whitepaper than actionable guidance. It explains concepts Claude already understands, provides non-executable pseudocode with undefined functions, and lacks concrete workflows with validation steps. The content would need to be fundamentally restructured to be useful—replacing abstract descriptions with specific, executable instructions and clear decision frameworks.
Suggestions
Replace all pseudocode with executable, copy-paste-ready examples using real libraries (e.g., actual profiling with cProfile, actual async orchestration with asyncio), or remove code blocks entirely if the skill is instruction-only.
Remove the 'Role' section, 'Core Capabilities' bullets, and all marketing language ('cutting-edge', 'holistic', 'advanced AI-driven framework')—these waste tokens and tell Claude nothing actionable.
Convert the 8 numbered sections into a concrete workflow with explicit validation checkpoints, e.g., 'Run baseline benchmark → Profile with [specific tool] → If latency > threshold, apply [specific change] → Re-run benchmark → Compare results'.
Either split detailed sections (profiling agents, cost optimization, coordination patterns) into separate referenced files, or dramatically condense the document to under 100 lines focusing only on decision logic and concrete steps.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive padding. Explains concepts Claude already knows (what profiling is, what context windows are, basic concurrency patterns). The 'Role' section with 'AI-Powered Multi-Agent Performance Engineering Specialist' and 'Core Capabilities' bullet list is pure filler. Much of the content describes rather than instructs, and marketing-style language ('cutting-edge AI orchestration techniques', 'holistic') wastes tokens. | 1 / 3 |
Actionability | Code examples are pseudocode with undefined functions (semantic_truncate, aggregate_performance_metrics, DatabasePerformanceAgent) and incomplete implementations (select_optimal_model with just 'pass'). None of the code is executable or copy-paste ready. The reference workflows are vague bullet lists ('Agent-based optimization', 'Iterative performance refinement') with no concrete commands or steps. | 1 / 3 |
Workflow Clarity | The top-level instructions (steps 1-4) are extremely vague ('Profile agent workloads and identify coordination bottlenecks'). The reference workflows are abstract lists without specific commands, validation checkpoints, or error recovery steps. No feedback loops are defined despite the skill involving potentially destructive orchestration changes. The numbered sections (1-8) read as a taxonomy rather than a workflow. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with 8 major sections all inline, no references to external files, and no bundle files to support progressive disclosure. Content that could be split (profiling details, cost optimization, coordination patterns) is all dumped into one long document with poor navigability. | 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 |
|---|---|---|
frontmatter_unknown_keys | Unknown frontmatter key(s) found; consider removing or moving to metadata | Warning |
Total | 10 / 11 Passed | |
- Repository
- boisenoise/skills-collections
- Commit
431bfad
- Reviewed
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