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.
npx agentmods add commands/lancejames221b/agent-hivemind/hv-querygit clone --depth 1 https://github.com/lancejames221b/agent-hivemindWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/commands/lancejames221b/agent-hivemind/hv-query)<a href="https://agentmods.dev/commands/lancejames221b/agent-hivemind/hv-query"><img src="https://agentmods.dev/badge/commands/lancejames221b/agent-hivemind/hv-query.svg" alt="Measured on agentmods" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00011 | $0.02411 |
| Opus 5 | $0.00005 | $0.01205 |
| Sonnet 5 | $0.00002 | $0.00482 |
| Haiku 4.5 | $0.00001 | $0.00241 |
Grade A, and why
hv-query 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 5d ago.
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.
How it starts
The opening of the file, as written. The whole thing — 290 lines — stays where its author put it; the contents beside it link to each section on GitHub.
hv-query - Collective Knowledge Search
Purpose
Search the hAIveMind collective memory and query specialized agents for comprehensive answers combining stored knowledge with real-time expertise.
When to Use
- Troubleshooting Issues: Find solutions to problems encountered before
- Best Practices: Learn how other agents handle similar situations
- Configuration Guidance: Get infrastructure setup recommendations
- Incident Research: Find related incidents and their resolutions
- Technical Questions: Tap into specialized agent knowledge
- Historical Context: Understand past decisions and their outcomes
Syntax
hv-query "question or topic" [category] [options]
Parameters
- question (required): Clear, specific question or topic to search
- category (optional): Narrow search to specific memory types
infrastructure: Server configs, network topology, hardwareincidents: Outage reports, resolutions, post-mortemsdeployments: Release procedures, rollbacks, configurationssecurity: Vulnerabilities, patches, compliance, auditsmonitoring: Alerts, metrics, dashboards, thresholdsrunbooks: Procedures, scripts, operational guides
- options (optional):
--agent=name: Query specific agent directly (e.g., --agent=elastic1-specialist)--recent=hours: Limit to memories from last N hours (e.g., --recent=24)--semantic: Use semantic search only (default: hybrid)--exact: Use exact text matching only
Query Intelligence Features
Hybrid Search Strategy
- Semantic Search: Finds conceptually related information
- Full-Text Search: Locates exact phrases and technical terms
- Agent Expertise: Routes questions to specialists
- Context Correlation: Links related memories automatically
Agent Expertise Routing
- Database Issues → mysql-specialist, mongodb-specialist
- Elasticsearch Problems → elastic1-specialist, cluster-manager
- Security Questions → security-analyst, auth-specialist
- Network Issues → infrastructure-manager, network-specialist
- Code Questions → development-team, code-reviewer
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.
- 5d ago First seen · 290 lines · 0 tokens per session scan A ebe01fb52505
hv-query is a command published in the GitHub repository lancejames221b/agent-hivemind (7 stars, last pushed 1mo ago), licensed MIT. It adds 11 tokens to every session and 2,411 once invoked, about $0.0001 per session on Opus 5. 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.
Other commands, from other repositories
minutes-ideas
Surface recent voice memos and ideas captured from any device. Use when the user asks "what ideas did I have?", "what were my recent memos?", "what did I record while walking?", or wants to recall a captured thought.
learn
Force claude-smart to extract learnings from this session now.
session-end
I'll summarize this coding session and update the memory system with our accomplishments.
memory-store
Store an insight, decision, or pattern to memory.
cc-memory
Configure persistent memory that survives across sessions using a layered approach: split rule files for always-loaded context, auto-memory for organic learning, and optional MCP-backed long-term memory for large codebases.
analyze-context
USE WHEN you want to analyze project context before starting work on a task. Calls context + recall, then synthesizes goals, decisions, gotchas, and relevant memories into a pre-task brief.