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hive-mind-advanced

Advanced Hive Mind collective intelligence system for queen-led multi-agent coordination with consensus mechanisms and persistent memory

45

0.99x
Quality

17%

Does it follow best practices?

Impact

99%

0.99x

Average score across 3 eval scenarios

SecuritybySnyk

Advisory

Suggest reviewing before use

Optimize this skill with Tessl

npx tessl skill review --optimize ./.claude/skills/hive-mind-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, attempting to be a comprehensive reference document rather than a focused, actionable skill. It explains many concepts Claude already understands, repeats information across sections, and packs everything into a single monolithic file. While it does provide concrete CLI commands and API examples, the sheer volume of content dilutes the actionable guidance, and the lack of validation checkpoints in workflows is a notable gap for a system involving multi-agent coordination.

Suggestions

Reduce content by 60-70%: remove concept explanations Claude already knows (Byzantine consensus theory, what LRU caches are, what WAL mode does), the 'Skill Progression' section, marketing benchmarks, and the verbose overview paragraph.

Split into multiple files: move API Reference to API.md, Configuration to CONFIG.md, Troubleshooting to TROUBLESHOOTING.md, and Examples to EXAMPLES.md, keeping SKILL.md as a concise overview with links.

Add explicit validation checkpoints to workflows: after 'hive-mind init', verify initialization succeeded; after 'spawn', verify queen and workers are running; include error recovery steps inline rather than in a disconnected troubleshooting section.

Fix incomplete code examples: add proper imports, fix the createTask syntax error, and ensure JavaScript examples show complete executable snippets with necessary setup context.

DimensionReasoningScore

Conciseness

Extremely verbose at ~500+ lines. Explains concepts Claude already knows (what Byzantine fault tolerance is, what LRU caches are, what WAL mode is). Includes extensive sections like 'Skill Progression' beginner/intermediate/advanced lists, marketing-style benchmarks, and redundant explanations. The overview paragraph is pure fluff ('represents the pinnacle of multi-agent coordination'). Much content is repeated across sections (consensus algorithms explained multiple times).

1 / 3

Actionability

Provides concrete CLI commands that appear executable and JavaScript API examples with clear method signatures. However, many code examples are incomplete (e.g., the createTask example has a syntax error with misplaced 'priority: 8'), some are pseudocode-like comments rather than executable code (neural pattern training section), and the JavaScript examples lack import statements or setup context. The mix of CLI and programmatic examples without clear context on when to use which reduces actionability.

2 / 3

Workflow Clarity

The Getting Started section provides a reasonable 3-step sequence (init, spawn, monitor), but lacks validation checkpoints. There are no explicit verification steps after spawning swarms, no error recovery workflows for failed initializations, and no feedback loops for the multi-step processes described. The troubleshooting section helps but is disconnected from the main workflows rather than integrated as validation checkpoints.

2 / 3

Progressive Disclosure

This is a monolithic wall of text with no bundle files to support it. Everything is inlined in a single massive document — API references, configuration details, troubleshooting, examples, and best practices that should be in separate files. The 'References' section links to external docs but the skill itself doesn't split content across files. The 'Related Skills' section references other skills but doesn't help organize this skill's own content.

1 / 3

Total

6

/

12

Passed

Description

7%

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 marketing tagline full of buzzwords rather than a functional skill description. It fails to specify concrete actions, lacks natural trigger terms users would use, and provides no guidance on when Claude should select this skill. The only slight positive is that its unusual terminology reduces conflict risk somewhat.

Suggestions

Replace abstract buzzwords with concrete actions the skill performs, e.g., 'Coordinates multiple agents to collaboratively solve tasks, aggregates responses, and resolves conflicts through voting mechanisms.'

Add an explicit 'Use when...' clause with natural trigger terms, e.g., 'Use when the user asks to coordinate multiple agents, run parallel tasks, or aggregate results from multiple sources.'

Remove jargon like 'queen-led' and 'Hive Mind' unless these are specific product names, and instead describe the functionality in plain language that a user would recognize.

DimensionReasoningScore

Specificity

The description uses abstract, buzzword-heavy language ('collective intelligence system', 'consensus mechanisms', 'persistent memory') without listing any concrete actions the skill performs. There are no specific verbs describing what it actually does.

1 / 3

Completeness

There is no 'Use when...' clause or equivalent trigger guidance, and the 'what' is extremely vague — it describes a system concept rather than concrete capabilities. Both what and when are very weak.

1 / 3

Trigger Term Quality

The terms used ('Hive Mind', 'queen-led', 'consensus mechanisms') are highly technical jargon that users would almost never naturally say. No common user-facing keywords are included.

1 / 3

Distinctiveness Conflict Risk

The niche terminology ('Hive Mind', 'queen-led multi-agent coordination') is unusual enough that it's unlikely to conflict with most other skills, but the lack of concrete triggers means it could still be confused with other multi-agent or orchestration skills.

2 / 3

Total

5

/

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 (730 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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