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multi-agent-patterns

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.

45

Quality

47%

Does it follow best practices?

Impact

No eval scenarios have been run

SecuritybySnyk

Passed

No known issues

Fix and improve this skill with Tessl

tessl review fix ./plugins/sadd/skills/multi-agent-patterns/SKILL.md
SKILL.md
Quality
Evals
Security

Quality

Content

27%

Reviews the quality of instructions and guidance provided to agents. Good implementation is clear, handles edge cases, and produces reliable results.

This skill is significantly over-scoped, combining multi-agent architecture patterns with an extensive memory system design guide in a single monolithic file. It spends excessive tokens explaining concepts Claude already understands (context windows, vector stores, knowledge graphs, parallelization benefits) while providing insufficient actionable, executable guidance for actually implementing these patterns in Claude Code. The content would benefit greatly from aggressive trimming, splitting into focused files, and replacing conceptual explanations with concrete implementation examples.

Suggestions

Split the Memory System Design section into a separate MEMORY.md file and reference it from the main skill, reducing the monolithic structure and improving progressive disclosure.

Remove explanatory content Claude already knows (what context windows are, why parallelization helps, how vector stores work, benchmark comparison tables) to reduce token usage by an estimated 50-60%.

Replace pseudocode and markdown diagrams with executable Claude Code examples showing actual Task tool invocations, concrete command definitions, and real file-based coordination patterns.

Add explicit validation checkpoints to multi-agent workflows, such as verifying subagent output format before aggregation and checking for divergence between agent results before synthesis.

DimensionReasoningScore

Conciseness

Extremely verbose at ~300+ lines. Extensively explains concepts Claude already knows (what context windows are, why parallelization helps, what vector stores do, what knowledge graphs are). The 'Memory System Design' section is essentially a second skill embedded within the first, with lengthy explanations of memory architecture fundamentals, benchmark tables, and five memory layers that Claude doesn't need explained. Much content describes rather than instructs.

1 / 3

Actionability

Provides some structural guidance (e.g., the code review multi-agent example, command-as-supervisor pattern) but lacks executable code. Examples are pseudocode or markdown diagrams rather than copy-paste ready implementations. The Claude Code-specific guidance is vague ('use Task tool to spawn subagent') without showing actual invocation syntax or concrete command definitions.

2 / 3

Workflow Clarity

Steps are listed for the supervisor pattern (analyze, dispatch, collect, synthesize) and some failure modes have mitigations, but there are no explicit validation checkpoints or feedback loops. For an architecture involving multi-agent coordination—where error propagation is a named failure mode—the lack of concrete validation steps between agent handoffs caps this at 2.

2 / 3

Progressive Disclosure

Monolithic wall of text with no references to external files despite the content clearly warranting separation. The entire 'Memory System Design' section (which is roughly half the document) should be a separate file. No bundle files exist to support progressive disclosure. The document tries to cover too much in a single file with no navigation aids or cross-references.

1 / 3

Total

6

/

12

Passed

Description

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 a solid structure with an explicit 'Use when...' clause covering multiple trigger conditions, which is its strongest aspect. However, it lacks specificity in the concrete actions it performs beyond 'design' and could benefit from more natural trigger terms that users would actually say. The domain is moderately distinctive but could overlap with general architecture or system design skills.

Suggestions

Add specific concrete actions such as 'define agent roles, create communication protocols, implement orchestration patterns, design handoff strategies'.

Include additional natural trigger terms users might say, such as 'orchestration', 'agent swarm', 'delegation', 'agentic workflow', or 'multi-step pipeline'.

DimensionReasoningScore

Specificity

Names the domain ('multi-agent architectures') and mentions some concepts like 'context limits', 'subtasks', and 'specializing agents', but doesn't list concrete actions beyond the vague 'design'. Lacks specifics like 'define agent roles, create communication protocols, implement orchestration patterns'.

2 / 3

Completeness

Clearly answers both 'what' (design multi-agent architectures for complex tasks) and 'when' with an explicit 'Use when...' clause listing three specific trigger conditions: context limits exceeded, natural task decomposition, and quality improvement through specialization.

3 / 3

Trigger Term Quality

Includes some 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 term 'multi-agent architectures' provides some distinctiveness, but 'complex tasks' and 'subtasks' are generic enough to potentially overlap with general architecture, system design, or task planning skills. The niche is somewhat clear but not sharply delineated.

2 / 3

Total

9

/

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.

Validation11 / 11 Passed

Validation for skill structure

No warnings or errors.

Repository
NeoLabHQ/context-engineering-kit
Reviewed

Table of Contents

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