Design multi-agent architectures for complex tasks. Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality.
55
43%
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 ./plugins/sadd/skills/multi-agent-patterns/SKILL.mdQuality
Discovery
75%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-structured with a clear 'Use when' clause that provides three distinct trigger conditions, making it strong on completeness and distinctiveness. However, the 'what' portion is somewhat high-level—it could benefit from listing more concrete actions beyond 'design multi-agent architectures'. Trigger term coverage could also be expanded to include more natural user language variations.
Suggestions
Add more specific concrete actions, e.g., 'Design multi-agent architectures, define agent roles and responsibilities, configure inter-agent communication, and set up orchestration patterns for complex tasks.'
Expand trigger terms to include natural variations users might say, such as 'orchestration', 'agent pipeline', 'delegation', 'agentic workflow', or 'multiple agents'.
| Dimension | Reasoning | Score |
|---|---|---|
Specificity | Names the domain ('multi-agent architectures') and mentions some actions ('design', 'decompose into subtasks', 'specializing agents'), but doesn't list multiple concrete specific actions like 'define agent roles, configure communication protocols, set up orchestration patterns'. | 2 / 3 |
Completeness | Clearly answers both 'what' (design multi-agent architectures for complex tasks) and 'when' with explicit triggers ('Use when single-agent context limits are exceeded, when tasks decompose naturally into subtasks, or when specializing agents improves quality'). | 3 / 3 |
Trigger Term Quality | Includes relevant terms like 'multi-agent', 'subtasks', 'context limits', and 'specializing agents', but misses common natural variations users might say such as 'orchestration', 'agent swarm', 'delegation', 'pipeline', 'workflow', or 'agentic system'. | 2 / 3 |
Distinctiveness Conflict Risk | The focus on multi-agent architectures, context limits, and agent specialization creates a clear niche that is unlikely to conflict with other skills. The triggers are specific enough to distinguish this from general task planning or single-agent skills. | 3 / 3 |
Total | 10 / 12 Passed |
Implementation
12%Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.
This skill reads more like an academic survey of multi-agent architectures and memory systems than an actionable guide for Claude Code. It is extremely verbose, explaining many concepts Claude already understands (context windows, vector stores, knowledge graphs) while providing almost no executable code or concrete implementation examples. The Memory System Design section essentially doubles the skill's length with a second topic that should be a separate file.
Suggestions
Cut the content by at least 60%: remove explanations of concepts Claude already knows (what context windows are, why parallelization helps, what vector stores do) and focus only on Claude Code-specific implementation patterns.
Add concrete, executable examples: show actual Task tool invocations, real command structures, and copy-paste-ready code for spawning subagents and coordinating via files.
Extract the Memory System Design section into a separate MEMORY.md file and reference it from the main skill, along with other detailed sections like failure modes and consensus patterns.
Add explicit validation checkpoints to workflows: e.g., 'verify subagent output contains required fields before aggregation' with concrete validation code or checks.
| Dimension | Reasoning | Score |
|---|---|---|
Conciseness | Extremely verbose at ~300+ lines. Extensively explains concepts Claude already knows (what context windows are, why parallelization helps, what vector stores do, the context-memory spectrum). The Memory System Design section is essentially a second skill embedded within the first, with lengthy explanations of knowledge graphs, benchmarks, and memory layers that are largely conceptual rather than actionable. Much content reads like a textbook rather than operational instructions. | 1 / 3 |
Actionability | Despite the length, there is almost no executable code or concrete commands. The 'code examples' are pseudocode in markdown comments or ASCII diagrams. There are no actual Task tool invocations, no real command structures, no copy-paste-ready implementations. The guidance remains at the level of 'create a main command that orchestrates' without showing how. | 1 / 3 |
Workflow Clarity | The supervisor pattern includes a numbered sequence (analyze, dispatch, collect, synthesize) and the guidelines mention validation and iteration limits. However, there are no explicit validation checkpoints, no error recovery feedback loops, and no concrete verification steps. The failure modes section lists mitigations but doesn't integrate them into actionable workflows. | 2 / 3 |
Progressive Disclosure | The content is a monolithic wall of text with no references to external files despite being extremely long. The Memory System Design section alone could be its own separate file. There's no bundle structure to offload detailed content like benchmarks, memory layer details, or pattern implementations. Everything is inlined, making the skill overwhelming and poorly organized for consumption. | 1 / 3 |
Total | 5 / 12 Passed |
Validation
100%Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.
Validation — 11 / 11 Passed
Validation for skill structure
No warnings or errors.
dedca19
Table of Contents
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