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.
56
33%
Does it follow best practices?
Impact
96%
3.00xAverage score across 3 eval scenarios
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 more natural and varied to better match how users would phrase their needs.
Suggestions
Replace abstract phrases like 'coordinated profiling' and 'cost-aware orchestration' with concrete actions such as 'profile agent execution times, balance task distribution across agents, minimize API costs'.
Expand trigger terms in the 'Use when...' clause with more natural user language like 'agent bottlenecks', 'scaling agents', 'agent latency', 'multi-agent costs', or 'agent coordination issues'.
| 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, cost-aware 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 like 'agents are slow', 'scaling agents', 'agent bottleneck', 'load balancing', or 'agent costs'. | 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 workflow or pipeline 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 overview or architecture whitepaper than actionable guidance for Claude. It explains concepts Claude already understands, provides non-executable pseudocode with undefined dependencies, and lacks concrete workflows with validation steps. The content would need a complete rewrite to be useful as a skill file.
Suggestions
Replace all pseudocode with either executable code examples using real libraries or remove code entirely and provide specific, concrete step-by-step instructions with actual commands/tools to use.
Cut the content by at least 70% - remove all conceptual explanations (Core Capabilities, Coordination Principles, Key Strategies bullet lists) and keep only actionable guidance that Claude doesn't already know.
Add concrete validation checkpoints to workflows, e.g., 'Run benchmark X, compare against baseline Y, only proceed if metric Z improves by at least N%' with actual commands.
Split detailed content (profiling agents, cost optimization, latency techniques) into separate referenced files and keep SKILL.md as a concise overview with clear navigation to each topic.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose with extensive conceptual explanations Claude already knows (what profiling is, what coordination principles are, what cost optimization means). Filled with marketing-style language ('cutting-edge AI orchestration techniques', 'holistically improve system performance') and bullet-point lists of abstract concepts that add no actionable value. The content could be reduced by 70%+ without losing useful information. | 1 / 3 |
Actionability | Code examples are pseudocode with undefined functions (semantic_truncate, aggregate_performance_metrics, PriorityQueue, PerformanceTracker) and placeholder implementations (pass statements). No concrete, executable commands or real tool usage. The reference workflows are just abstract 4-step lists with no specifics. The 'Arguments Handling' section uses undefined variables with no explanation of how they're actually used. | 1 / 3 |
Workflow Clarity | The initial 4-step instruction workflow is extremely vague ('Profile agent workloads and identify coordination bottlenecks'). Reference workflows are abstract outlines with no validation checkpoints, no error recovery, and no concrete steps. For a skill involving orchestration changes that could cause system-wide regressions, there are no feedback loops or verification steps despite the safety section acknowledging the risk. | 1 / 3 |
Progressive Disclosure | Monolithic wall of text with 8 numbered sections all inline, many of which contain only bullet-point lists of abstract concepts. No references to external files for detailed content. The document tries to cover profiling, context optimization, coordination, parallelism, cost optimization, latency, quality tradeoffs, and monitoring all in one file with insufficient depth in any of them. | 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
636b862
- Reviewed
Table of Contents
Is this your skill?
If you maintain this skill, you can claim it as your own. Once claimed, you can manage eval scenarios, bundle related skills, attach documentation or rules, and ensure cross-agent compatibility.