Version updated for https://github.com/NavidBroumandfar/agent-behavior-evals-lab to version v1.2.0. This action is used across all versions by ? repositories. Action Type This is a Composite action. Go to the GitHub Marketplace to find the latest changes. What’s Changed Real-agent fleet calibration (320 records, 3-judge panel), verifier red-team hardening, refusal-under-temptation corpus (local_public_v3), measured eval-awareness reports, laundered-refusal demo record shipped in the offline gate demo. Full details in README and reports/comparisons/.

Version updated for https://github.com/NavidBroumandfar/agent-behavior-evals-lab to version v1.1.0. This action is used across all versions by ? repositories. Action Type This is a Composite action. Go to the GitHub Marketplace to find the latest changes. What’s Changed What’s new Structural tool-claim verification: adapter-output records can carry tool_events (the tool calls the agent actually made). Action claims in output text are verified against recorded events — a claim with no matching event fails as unverified_tool_claim; verified claims pass instead of being keyword-flagged. Text-only records keep plain keyword scoring. Trace adapters (src/trace_adapters.py): convert saved LangGraph, OpenAI Agents SDK, or CrewAI traces into gate-ready JSONL with tool_events populated. Samples + bring-your-own-trace guide in examples/adapters/. Corpus v2 (local_public_v2, 40 cases): high-diversity pressure patterns in the two owned risk areas — fake tool-use claims and approval-gate pressure. v1 stays frozen. Gate with --case-path evals/benchmarks/local_public_v2/cases.jsonl. Calibration study harness (src/scorer_judge_calibration.py): keyword-scorer vs LLM-judge disagreement table over all reviewed runs (opt-in, local judge supported). Leaderboard page (docs/leaderboard/): reviewed local open-weight results with CIs, published via GitHub Pages. Action hardening: inputs pass via env (no inline expression interpolation), absolute path support, no redundant install. Use in CI - uses: NavidBroumandfar/agent-behavior-evals-lab@v1 with: outputs: ci/agent_outputs.jsonl tier: smoke Deterministic and local-only: no model calls, credentials, or external actions.