Hi — I'm working on OM World, a protocol for a decentralized intent economy. CloddsBot's framing — autonomous trading across 1000+ markets on Polymarket/Kalshi/Binance/Hyperliquid/Solana DEXs/5 EVM chains — is one of the highest-stakes real-world autonomy surfaces I've seen, which makes it useful for stress-testing the Agent Mandate primitive we're specifying.
1. Scope boundaries across venues. When the principal authorizes the agent to trade across 1000+ markets, is the scope expressed venue-by-venue (per-venue spending caps, per-venue position limits), or aggregated (one budget pool the agent allocates)? The aggregated model is more flexible but harder to dispute; the venue-bound model is rigid but auditable.
2. Venue-failover semantics. If the agent commits to a leg on venue A and then venue A goes down mid-trade, what's the policy — auto-failover to venue B with equivalent execution, hard-fail the trade, or buffer for principal approval? This is the cross-venue analogue of the budget-exhaustion problem.
3. Kill-switch hierarchy. Multi-venue autonomous agents need layered kill switches: principal can stop the agent entirely, principal can stop a venue, the agent can self-stop on detected anomaly. How are these layered in CloddsBot — explicit on-chain controls, off-chain signals, or both? And which level wins on conflict?
Happy to share OM World's Mandate spec — the multi-venue stress case is exactly the territory where most mandate designs break down.
Hi — I'm working on OM World, a protocol for a decentralized intent economy. CloddsBot's framing — autonomous trading across 1000+ markets on Polymarket/Kalshi/Binance/Hyperliquid/Solana DEXs/5 EVM chains — is one of the highest-stakes real-world autonomy surfaces I've seen, which makes it useful for stress-testing the Agent Mandate primitive we're specifying.
1. Scope boundaries across venues. When the principal authorizes the agent to trade across 1000+ markets, is the scope expressed venue-by-venue (per-venue spending caps, per-venue position limits), or aggregated (one budget pool the agent allocates)? The aggregated model is more flexible but harder to dispute; the venue-bound model is rigid but auditable.
2. Venue-failover semantics. If the agent commits to a leg on venue A and then venue A goes down mid-trade, what's the policy — auto-failover to venue B with equivalent execution, hard-fail the trade, or buffer for principal approval? This is the cross-venue analogue of the budget-exhaustion problem.
3. Kill-switch hierarchy. Multi-venue autonomous agents need layered kill switches: principal can stop the agent entirely, principal can stop a venue, the agent can self-stop on detected anomaly. How are these layered in CloddsBot — explicit on-chain controls, off-chain signals, or both? And which level wins on conflict?
Happy to share OM World's Mandate spec — the multi-venue stress case is exactly the territory where most mandate designs break down.