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 skills/proffesor-for-testing/agentic-qe/hive-mindnpx skills add proffesor-for-testing/agentic-qe --skill hive-mindgit clone --depth 1 https://github.com/proffesor-for-testing/agentic-qeWrote 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/skills/proffesor-for-testing/agentic-qe/hive-mind)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/hive-mind"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/hive-mind.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 | $0.00061 | $0.00433 |
| Opus 5 | $0.00030 | $0.00217 |
| Sonnet 5 | $0.00012 | $0.00087 |
| Haiku 4.5 | $0.00006 | $0.00043 |
Grade A, and why
hive-mind 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 2d 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.
This is a copy
100% identical to hive-mind — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
What it actually says
Hive-Mind Skill
Purpose
Byzantine fault-tolerant consensus and distributed swarm coordination.
When to Trigger
- Multi-agent distributed tasks
- Fault-tolerant operations needed
- Collective decision making
- Complex coordination patterns
Topologies
| Topology | Description | Use Case |
|---|---|---|
hierarchical |
Queen controls workers | Default, anti-drift |
mesh |
Fully connected peers | Research, exploration |
hierarchical-mesh |
Hybrid | Recommended for complex |
adaptive |
Dynamic based on load | Auto-scaling |
Consensus Strategies
| Strategy | Tolerance | Use Case |
|---|---|---|
byzantine |
f < n/3 faulty | Untrusted environment |
raft |
f < n/2 faulty | Leader-based, consistent |
gossip |
Eventual | Large scale, availability |
crdt |
Conflict-free | Concurrent updates |
quorum |
Configurable | Tunable consistency |
Commands
Initialize Hive-Mind
npx claude-flow hive-mind init --topology hierarchical-mesh --consensus raft
Spawn Queen
npx claude-flow hive-mind spawn --role queen --name coordinator
Check Consensus Status
npx claude-flow hive-mind consensus --status
View Sessions
npx claude-flow hive-mind sessions --active
Best Practices
- Use hierarchical for coding tasks (anti-drift)
- Use raft consensus for consistency
- Keep agent count under 8 for coordination
- Run frequent checkpoints
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.
- 2d ago First seen · 66 lines · 61 tokens per session scan A 4edb7cca7df5
hive-mind is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (474 stars, last pushed 3d ago), licensed MIT. It adds 61 tokens to every session and 433 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 0 findings. It is 100% identical to hive-mind, differing in 0 lines, and is treated as a copy.
Other skills, from other repositories
foundry-config-setup
Resolve missing setup caused by a hardcoded Foundry project endpoint or model in a sample. Use when a sample fails because it uses a placeholder/hardcoded projectendpoint (for example "https://your-project.services.ai.azure.com") or a hardcoded model instead of reading them from the environment.
dogfood
Systematically explore and test a mobile app on iOS/Android with agent-device to find bugs, UX issues, and other problems. Use when asked to dogfood, QA, exploratory test, find issues, bug hunt, or test this app on mobile.
tooluniverse-drug-research
Comprehensive drug profiling — mechanism, primary/secondary targets, drug interactions, clinical-trial status, adverse events (FAERS), pharmacogenomics, and approval history. Use for full drug investigation reports, 'tell me about drug X' queries, and assembling drug profiles for clinicians, researchers, or regulatory…
monorepo-management
Master monorepo management with Turborepo, Nx, and pnpm workspaces to build efficient, scalable multi-package repositories with optimized builds and dependency management. Use when setting up monorepos, optimizing builds, or managing shared dependencies.
gh-bulk-issues
Orchestrate parallel Mastra Code headless instances to debug and fix multiple GitHub issues simultaneously.
qa-investigation
Investigate a specific test failure to its root cause and document the why. Detects whether a failing test is flaky (intermittent) or a deterministic bug during reproduction. Use when a test fails and you need the real cause, not just to make it green. Execution layer, not strategy review. Keywords: flaky test…