Show HN: AgentFacts – verifiable identity and audit logs for AI agents (github.com)

AgentFacts has launched an open-source SDK designed to establish verifiable identities for AI agents. This innovative tool enables developers to create signed, tamper-evident profiles for AI agents, capturing critical data such as identity, model, tools, and policies, all formatted in a secure JSON card. By utilizing Ed25519 signatures and decentralized identifiers (DIDs), AgentFacts allows for offline verification and seamless introspection of popular frameworks, thereby enhancing trust and transparency in AI applications without imposing significant development overhead. The significance of AgentFacts lies in its potential to address crucial aspects of accountability and compliance in AI systems. By ensuring that agents can present verifiable profiles, it mitigates risks associated with misuse and bias in AI deployment. The systematic approach to policy checks and audit trails through Merkle log proofs enhances operational integrity, making it easier for organizations to monitor and validate AI behavior under a zero-trust framework. With straightforward installation via pip, support for Python 3.10+, and integrations with well-known platforms like LangChain and Hugging Face, AgentFacts positions itself as a vital resource for fostering reliable AI interactions in today's tech landscape.