hive-mind-advanced

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

0.99x

Quality

50%

Does it follow best practices?

Impact

99%

0.99x

Average score across 3 eval scenarios

Securityby

Low

Low-risk findings worth noting

Fix and improve this skill with Tessl

tessl review fix ./.claude/skills/hive-mind-advanced/SKILL.md

Quality

Content

50%

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

The body is rich with executable commands and a complete API reference, but it is over-long with redundant sections, lacks validation feedback loops in its workflows, and keeps all detail inline rather than splitting it into referenced bundle files.

Suggestions

Collapse the repeated consensus/queen-type explanations into one section and remove the Skill Progression and benchmark marketing content to tighten conciseness.

Add explicit validation checkpoints to multi-step workflows (e.g. after `hive-mind init`, verify status before spawning; on consensus failure, fall back per the troubleshooting steps already present).

Move the API Reference, Configuration, and Advanced Topics into separate referenced files (e.g. API.md, CONFIG.md) and keep SKILL.md as a concise overview, or fix the broken/non-executable code blocks so all guidance is copy-paste ready.

Dimension	Reasoning	Score
Conciseness	The body is mostly concrete reference material, but at ~700 lines it carries significant redundancy (consensus and queen types are explained three times) and marketing padding ("pinnacle of multi-agent coordination", benchmark stats, the Skill Progression section) that could be cut.	2 / 3
Actionability	Abundant copy-paste-ready `npx claude-flow hive-mind` commands anchor the content, but several JavaScript blocks are not executable as written (e.g. `priority: 8` inside a call argument) and the Neural Pattern Training block is comment-only, so guidance is not uniformly copy-paste ready.	2 / 3
Workflow Clarity	Getting Started and Skill Progression give clear numbered sequences, but there are no explicit validation checkpoints or validate->fix->retry feedback loops for batch spawning and consensus operations, which the rubric caps at 2.	2 / 3
Progressive Disclosure	Section headers organize the file, but everything (API reference, configuration, troubleshooting, advanced topics) is inline in one ~700-line monolith with only external URL references and no bundle files, so content that should be split out remains inline.	2 / 3
	Total	8 / 12 Passed

Description

50%

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 identifies a clear domain and several specific concepts but is noun-heavy with no explicit use-when trigger, leaving every dimension at the midpoint. Adding a trigger clause and concrete verbs would lift specificity and completeness.

Suggestions

Append an explicit trigger clause, e.g. "Use when coordinating multiple agents on a complex objective, spawning queen-led swarms, or building consensus across workers."

Lead with concrete actions ("Spawn queen-led swarms, orchestrate specialized workers, run majority/weighted/Byzantine consensus, persist collective memory") instead of a system description.

Add natural user-facing variations ("swarm", "multi-agent", "collective decision-making") to broaden trigger coverage.

Dimension	Reasoning	Score
Specificity	Names a concrete domain ("Hive Mind collective intelligence system", "queen-led multi-agent coordination", "consensus mechanisms", "persistent memory") but describes what the system IS rather than listing concrete actions a user performs, so it stops short of the multi-action anchor.	2 / 3
Completeness	It states what the skill is, but there is no "Use when..." clause or equivalent trigger, so per the rubric guideline completeness is capped at 2.	2 / 3
Trigger Term Quality	Recognizable terms like "Hive Mind", "multi-agent coordination", and "consensus" appear, but phrasing is jargon-heavy ("queen-led", "persistent memory") with no common variations or explicit trigger guidance.	2 / 3
Distinctiveness Conflict Risk	The "Hive Mind / queen-led" framing is a recognizable niche, but it overlaps with sibling skills the document itself lists (swarm-orchestration, consensus-mechanisms, memory-systems), so conflict risk remains.	2 / 3
	Total	8 / 12 Passed

Validation

87%

Warnings & errors only

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

Validation — 14 / 16 Passed

Validation for skill structure

Criteria	Description	Result
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	14 / 16 Passed

Repository: ruvnet/ruvector
Path: .claude/skills/hive-mind-advanced/SKILL.md
Commit: 6a6c39e

Reviewed: about 14 hours ago

Table of Contents

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