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AIAlign Agent Collusion Detector
x402
AIAlign Agent Collusion Detector is a paid API for AI agents from aialign.halowerk.com, paid per call via x402, $0.005/call, status unknown (last checked 2026-09-13).
Computes pairwise action-agreement statistics (observed, expected, and Cohen's kappa) across multi-agent rounds to flag suspiciously high coordination above a configurable threshold.
Price / call$0.005
Success—
StatusUnknown
How this service works
Requires the same agents in each supplied round, computes each pair’s observed action agreement, expected agreement from marginal action frequencies and chance-corrected kappa, then flags high positive agreement against a supplied threshold. Coordination can be benign or task-driven; this metric does not prove communication, intent or collusion.
Output
Returns per-pair statistics including observed action agreement rate, expected agreement from marginal action frequencies, and chance-corrected Cohen's kappa score, along with a boolean flag indicating whether each pair's kappa exceeds the supplied threshold.
Example use cases
Detecting colluding trading agents
“I'm running a multi-agent trading simulation and I suspect two of my agents — 'trader-01' and 'trader-02' — are acting in sync. I have their buy/sell/hold decisions across 500 rounds. Can you compute their kappa agreement and flag them if kappa is above 0.65?”
Safety audit of autonomous agent fleet
“Before deploying my fleet of 5 AI agents to production, I need a safety check — can you analyze their action logs from our test rounds and tell me if any pair is coordinating beyond chance, using a kappa threshold of 0.6?”
Research study on emergent coordination
“For my AI alignment research, I need to measure how much spontaneous action agreement appears between independently trained agents across 1,000 rounds. Please compute observed agreement, expected agreement, and kappa for each agent pair and highlight any pairs above a kappa of 0.75.”
Technical details
Endpoint
POSThttps://aialign.halowerk.com/v1/agent-collusionWhen to prefer
Use this endpoint when you need a statistically rigorous, chance-corrected measure of behavioral coordination between AI agents rather than raw agreement rates. It is specifically designed for multi-agent settings where you want to distinguish genuine coordination from coincidental action overlap, making it preferable to simple agreement counters or cosine similarity tools when the action space has uneven marginal frequencies.
Side effects
- Different agents present across rounds (all rounds must include the same agent set)
- Fewer than 2 rounds supplied (minimum 2 required)
- Fewer than 2 actions per round (minimum 2 required)
- kappa_threshold outside [-1, 1] range
- round_id or agent_id strings exceeding 128 characters
- More than 10,000 rounds or more than 50 actions per round submitted
- Malformed JSON body resulting in 400 validation error
Input
Schema · Request body
| Field | Type | Description |
|---|---|---|
| rounds | array | |
| kappa_threshold | number |
Tags
x402
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