hive

A command that asks several AI models for views on the same question and combines their responses into a considered answer. In code-related tasks, it can provide the relevant source code as context for that discussion.

In plain words
What is it for?
Use it for code reviews, bug investigation, audits, architecture questions, or other questions where multiple independent opinions may help.
Why use it?
It gives you more than one model's perspective and helps compare their reasoning before reaching a conclusion.

Command for Claude Code

Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

agentmods
npx agentmods add commands/quantulabs/hivemind/hive
Clone the repo
git clone --depth 1 https://github.com/QuantuLabs/Hivemind

Made for: Claude Code.

Per session 0 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 1,446 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5 $0.00000 $0.01446
Opus 5 $0.00000 $0.00723
Sonnet 5 $0.00000 $0.00289
Haiku 4.5 $0.00000 $0.00145

Measured yesterday against content hash 4b3f82d8217f, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

hive scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured yesterday.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

.claude/commands/hive.md · 209 lines

How it starts

The opening of the file, as written. The whole thing — 209 lines — stays where its author put it; the contents beside it link to each section on GitHub.

/hive - Hivemind Deliberation

Query multiple AI models and orchestrate consensus through deliberation.

You (Claude Code) are the orchestrator. GPT and Gemini provide their perspectives, and you analyze, investigate, and synthesize the final consensus.

Arguments

  • $ARGUMENTS - The question to ask the Hivemind

Phase 1: Context Building (if needed)

For questions about the codebase:

CRITICAL: Pass RAW, UNDIGESTED code - but be SMART about what you include.

  1. Use Glob to find relevant files by pattern
  2. Use Read to get file contents
  3. Be selective - include the relevant portions, not necessarily entire files
  4. DO NOT use Explore agents - they return analyzed summaries, not raw code
  5. DO NOT pre-analyze - keep your interpretation for AFTER hivemind results

Smart context selection:

  • For audits: Include the actual implementation code, not your analysis
  • For bugs: Include the buggy function + related code, line numbers
  • For architecture: Include key files/interfaces, skip boilerplate
  • Large files: Use Read with offset/limit to get relevant sections

Example workflow:

# Find files
Glob("src/auth/**/*.ts")

# Read targeted sections (smart selection)
Read("/path/to/auth.ts", offset=50, limit=100)  # Just the relevant function
Read("/path/to/types.ts")  # Full file if small and relevant

# Pass raw code to hivemind (next phase)

Key: Raw ≠ Everything. Raw = actual code, not your summary of it.

For general questions, skip to Phase 2.


Phase 2: Initial Query

Step 1: Formulate YOUR answer first

Before calling the hivemind tool, think through the question and formulate your own complete answer. Be thorough - this is your contribution to the deliberation.

Step 2: Query other models

hivemind({
  question: "The question here",
  context: `
## Source Code (RAW - not summaries)

### /path/to/auth.ts (lines 50-150)
\`\`\`typescript
[PASTE THE RELEVANT CODE SECTION - actual code, not your description]
\`\`\`

### /path/to/types.ts
\`\`\`typescript
[PASTE ACTUAL CODE - be selective if file is large]
\`\`\`
`
})

Read the full file on GitHub · 209 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. yesterday First seen · 209 lines · 0 tokens per session scan A 4b3f82d8217f

Subscribe to this mod's changes

hive is a command published in the GitHub repository QuantuLabs/Hivemind (1 stars, last pushed 7mo ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 1,446 tokens. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-31.