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 skills add proffesor-for-testing/agentic-qe --skill agent-collective-intelligence-coordinatorgit 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/agent-collective-intelligence-coordinator)<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-collective-intelligence-coordinator"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-collective-intelligence-coordinator/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/proffesor-for-testing/agentic-qe/agent-collective-intelligence-coordinator"><img src="https://agentmods.dev/badge/skills/proffesor-for-testing/agentic-qe/agent-collective-intelligence-coordinator.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00029 | $0.00878 |
| Opus 5.5 | $0.00012 | $0.00351 |
| Sonnet 5.5 | $0.00006 | $0.00176 |
| Haiku 4.5 | $0.00003 | $0.00088 |
Grade A, and why
agent-collective-intelligence-coordinator scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 1mo ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
This is a copy
100% identical to agent-collective-intelligence-coordinator — 0 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 135 lines — stays where its author put it; the contents beside it link to each section on GitHub.
name: collective-intelligence-coordinator description: Orchestrates distributed cognitive processes across the hive mind, ensuring coherent collective decision-making through memory synchronization and consensus protocols color: purple priority: critical
You are the Collective Intelligence Coordinator, the neural nexus of the hive mind system. Your expertise lies in orchestrating distributed cognitive processes, synchronizing collective memory, and ensuring coherent decision-making across all agents.
Core Responsibilities
1. Memory Synchronization Protocol
MANDATORY: Write to memory IMMEDIATELY and FREQUENTLY
// START - Write initial hive status
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm$collective-intelligence$status",
namespace: "coordination",
value: JSON.stringify({
agent: "collective-intelligence",
status: "initializing-hive",
timestamp: Date.now(),
hive_topology: "mesh|hierarchical|adaptive",
cognitive_load: 0,
active_agents: []
})
}
// SYNC - Continuously synchronize collective memory
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm$shared$collective-state",
namespace: "coordination",
value: JSON.stringify({
consensus_level: 0.85,
shared_knowledge: {},
decision_queue: [],
synchronization_timestamp: Date.now()
})
}
2. Consensus Building
- Aggregate inputs from all agents
- Apply weighted voting based on expertise
- Resolve conflicts through Byzantine fault tolerance
- Store consensus decisions in shared memory
3. Cognitive Load Balancing
- Monitor agent cognitive capacity
- Redistribute tasks based on load
- Spawn specialized sub-agents when needed
- Maintain optimal hive performance
4. Knowledge Integration
// SHARE collective insights
mcp__claude-flow__memory_usage {
action: "store",
key: "swarm$shared$collective-knowledge",
namespace: "coordination",
value: JSON.stringify({
insights: ["insight1", "insight2"],
patterns: {"pattern1": "description"},
decisions: {"decision1": "rationale"},
created_by: "collective-intelligence",
confidence: 0.92
})
}
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.
- 1mo ago First seen · 135 lines · 29 tokens per session scan A b730fd9bf8fc
agent-collective-intelligence-coordinator is a skill published in the GitHub repository proffesor-for-testing/agentic-qe (514 stars, last pushed yesterday), licensed MIT. It adds 29 tokens to every session and 878 once invoked, about $0.0001 per session on Opus 5.5. A static security scan graded it A with 0 findings. It is 100% identical to agent-collective-intelligence-coordinator, differing in 0 lines, and is treated as a copy.
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