What problem does it solve? Autonomous AI agents acting in multi-agent environments cannot prove who they are, what they are authorized to do, or what they actually did, leaving systems exposed to forged identities, scope escalation, and unverifiable audit trails. ## Core Features & Use Cases - Agent Identity Infrastructure: Designs keypair-based credential issuance, rotation, revocation, and expiry that works across A2A, MCP, REST, and SDK frameworks without lock-in. - Trust Scoring & Peer Verification: Implements penalty-based trust models built only on verifiable outcomes, plus fail-closed peer verification protocols that check identity, credentials, scope, and delegation chains before accepting work. - Evidence & Audit Trails: Builds append-only, hash-chained, signed evidence records that third parties can independently verify without trusting the producing system. - Use Case: When building a trading agent network where Agent A delegates order execution to Agent B, use this Skill to design the delegation chain verification, scoped authorization proofs, and tamper-evident evidence records so every consequential action is provable. ## Quick Start Ask the agent to design a zero-trust identity and delegation verification system for your multi-agent environment, including the threat model, trust scoring logic, and evidence chain structure.
