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swarm-advanced

Advanced swarm orchestration patterns for research, development, testing, and complex distributed workflows

50

3.84x
Quality

24%

Does it follow best practices?

Impact

100%

3.84x

Average score across 3 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./.claude/skills/swarm-advanced/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 excessively verbose, repeating similar agent-spawning and parallel-execution patterns across four nearly identical swarm types without meaningful differentiation. The code examples use undefined variables and inconsistent syntax, making them illustrative rather than executable. The content would benefit enormously from condensing the core patterns into a concise overview with detailed patterns split into separate referenced files.

Suggestions

Reduce the document to ~150 lines: provide one complete pattern example inline and move the other three patterns (Development, Testing, Analysis) to separate referenced files (e.g., RESEARCH_SWARM.md, DEV_SWARM.md).

Make code examples executable by removing undefined variables (e.g., `findings`, `researchData`) and showing complete, self-contained MCP tool calls with literal values.

Add explicit validation checkpoints between workflow phases, e.g., 'Check swarm_status before proceeding to Phase 2; if any agent failed, re-spawn before continuing.'

Remove explanatory content Claude already knows (e.g., what mesh/star/ring topologies are conceptually) and replace with only the tool-specific configuration differences.

DimensionReasoningScore

Conciseness

Extremely verbose at 600+ lines with massive repetitive code blocks. The four swarm patterns (Research, Development, Testing, Analysis) follow nearly identical structures with redundant agent spawning boilerplate. Topology descriptions, best practices, and troubleshooting sections explain concepts Claude already knows. Much of this could be condensed to 1/4 the size.

1 / 3

Actionability

Provides concrete MCP tool calls and CLI commands, which is good. However, the code is JavaScript-style pseudocode with undefined variables (e.g., `findings`, `researchData`, `testSuites`, `workflowMetrics`) making it non-executable. The `await` syntax mixed with `mcp__` function call notation is inconsistent and unclear whether these are actual API calls or illustrative patterns.

2 / 3

Workflow Clarity

Each pattern has clear phased workflows (Phase 1-4) with logical sequencing. However, validation checkpoints are largely absent — there's no explicit 'verify this succeeded before proceeding' step between phases. The error handling section exists but is generic and not integrated into the workflow phases. For complex distributed operations, missing feedback loops between phases is a significant gap.

2 / 3

Progressive Disclosure

Monolithic wall of text with no bundle files to offload detail into. All four patterns with full code examples are inline, making this extremely long. The 'Related Skills' and 'References' sections reference external resources but the core content that should be split (e.g., each pattern could be its own file) is all crammed into one document with no actual supporting files provided.

1 / 3

Total

6

/

12

Passed

Description

22%

Based on the skill's description, can an agent find and select it at the right time? Clear, specific descriptions lead to better discovery.

This description reads like a high-level category label rather than a functional skill description. It lacks concrete actions, explicit trigger guidance, and relies on buzzwords like 'advanced' and 'complex' without specifying what the skill actually does. It would be difficult for Claude to reliably select this skill over others in a large skill library.

Suggestions

Add a 'Use when...' clause with specific trigger scenarios, e.g., 'Use when the user asks to coordinate multiple parallel agents, distribute tasks across workers, or orchestrate multi-step research pipelines.'

Replace vague language with concrete actions, e.g., 'Spawns and coordinates multiple agent swarms, distributes subtasks across parallel workers, aggregates results, and manages inter-agent communication for research and testing workflows.'

Remove filler adjectives like 'advanced' and 'complex' and instead describe the specific patterns supported (e.g., fan-out/fan-in, pipeline, map-reduce).

DimensionReasoningScore

Specificity

The description uses vague, abstract language like 'advanced swarm orchestration patterns' and 'complex distributed workflows' without listing any concrete actions. No specific operations (e.g., 'spawn agents', 'coordinate tasks', 'aggregate results') are mentioned.

1 / 3

Completeness

The description partially addresses 'what' (swarm orchestration patterns) but in very vague terms, and completely lacks any 'when' clause or explicit trigger guidance. The absence of a 'Use when...' clause caps this at 2 per the rubric, but the 'what' is also too weak, resulting in a score of 1.

1 / 3

Trigger Term Quality

It includes some relevant domain keywords like 'swarm', 'orchestration', 'research', 'development', 'testing', and 'distributed workflows', but these are broad and mixed with buzzwords. A user might say 'swarm' or 'orchestration' but terms like 'advanced patterns' are not natural trigger phrases.

2 / 3

Distinctiveness Conflict Risk

The term 'swarm orchestration' provides some distinctiveness, but the broad scope covering 'research, development, testing, and complex distributed workflows' could easily overlap with general development, testing, or workflow automation skills.

2 / 3

Total

6

/

12

Passed

Validation

81%

Checks the skill against the spec for correct structure and formatting. All validation checks must pass before discovery and implementation can be scored.

Validation9 / 11 Passed

Validation for skill structure

CriteriaDescriptionResult

skill_md_line_count

SKILL.md is long (974 lines); consider splitting into references/ and linking

Warning

frontmatter_unknown_keys

Unknown frontmatter key(s) found; consider removing or moving to metadata

Warning

Total

9

/

11

Passed

Repository
ruvnet/ruvector
Reviewed

Table of Contents

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