Add Determs — verifiable LLM decision audit records (VDR spec + SDK)

Author: nullcb

README.md

@@ -196,6 +196,7 @@ An awesome & curated list of the best LLMOps tools for developers.
 | [Fiddler AI](https://github.com/fiddler-labs/fiddler-auditor)                  | Evaluate, monitor, analyze, and improve machine learning and generative models from pre-production to production. Ship more ML and LLMs into production, and monitor ML and LLM metrics like hallucination, PII, and toxicity. | ![GitHub Badge](https://img.shields.io/github/stars/fiddler-labs/fiddler-auditor.svg?style=flat-square)          |
 | [Giskard](https://github.com/Giskard-AI/giskard)                               | Testing framework dedicated to ML models, from tabular to LLMs. Detect risks of biases, performance issues and errors in 4 lines of code.                                                                                      | ![GitHub Badge](https://img.shields.io/github/stars/Giskard-AI/giskard.svg?style=flat-square)
 | [QWED](https://github.com/QWED-AI/qwed-verification) | Deterministic verification protocol for LLM outputs using 8 formal verification engines (SymPy, Z3, AST, SQLGlot). Prevents hallucinations through mathematical proofs rather than statistical methods. | ![GitHub Badge](https://img.shields.io/github/stars/QWED-AI/qwed-verification.svg?style=flat-square) |
+| [Determs](https://github.com/determs-com/determs) | Open standard (Verifiable Decision Record spec, CC-BY-4.0) and reference implementation for verifiable AI decision audit records. Wraps Anthropic/OpenAI clients (Python SDK) to capture each LLM call as a structured record with RFC 8785 canonical SHA-256 digests and optional public anchor (OpenTimestamps → public blockchain). Rust CLI for verify/replay. Evidence packs for EU AI Act Art. 12/19 compliance. | ![GitHub Badge](https://img.shields.io/github/stars/determs-com/determs.svg?style=flat-square) |
 | [Great Expectations](https://github.com/great-expectations/great_expectations) | Always know what to expect from your data.                                                                                                                                                                                     | ![GitHub Badge](https://img.shields.io/github/stars/great-expectations/great_expectations.svg?style=flat-square) |
 | [Helicone](https://github.com/Helicone/helicone)                              | Open source LLM observability platform. One line of code to monitor, evaluate, and experiment with features like prompt management, agent tracing, and evaluations.                                                            | ![GitHub Badge](https://img.shields.io/github/stars/Helicone/helicone.svg?style=flat-square)                     |
 | [Traceloop OpenLLMetry](https://github.com/traceloop/openllmetry)                              | OpenTelemetry-based observability and monitoring for LLM and agents workflows.                                                           | ![GitHub Badge](https://img.shields.io/github/stars/traceloop/openllmetry.svg?style=flat-square)