feat: DecisionAssure integration – runtime anomaly detection as TRACE claims

[a1k7]

Summary

This PR adds a behavioural anomaly detection layer to the agentrust‑io stack using DecisionAssure – an open‑source runtime governance engine for AI agents.

The adapter (da_to_trace.py) reads a DecisionAssure signed trace (JSON) and converts continuity failures (policy drift, identity mutation, stale evidence) and collusion suspicion signals into a TRACE‑compatible claim (EAT/JWT format). This directly addresses the documented gap in the agentrust‑io README:

“There is no dedicated behavioural anomaly detection or agent quarantine tooling in the current repos. … TRACE provides the audit foundation; detection is not included.”

Changes

• decisionassure-integration/da_to_trace.py – core adapter
• decisionassure-integration/README.md – usage documentation
• decisionassure-integration/requirements.txt – empty (no extra deps)

How to test

1. Place a DecisionAssure signed trace (e.g., trace_signed.json) in the folder.
2. Run:

   python da_to_trace.py trace_signed.json

3. Output is a URL‑safe base64 encoded TRACE claim.
   Next steps

The claim can be submitted to a trace-registry instance or used as attestation evidence.
Conformance tests are provided in a separate PR (agentrust-io/trace-tests).
Related

DecisionAssure repo: github.com/a1k7/DecisionAssure-Runtime-Governance
trace-spec: github.com/agentrust-io/trace-spec
/cc @imran-siddique

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