Cross-Agent Model Compatibility Verifier 20260820 v1.0

What it does

Cross-Agent Model Compatibility Verifier helps agent teams confirm whether a model route is ready to work across multiple agent runtimes. It checks redacted evidence for provider identity, model identity, authentication, context limits, tool calls, structured outputs, rate limits, cost ceilings, fallback, failure evidence, and rollback.

The result gives teams a simple readiness verdict before a model is added to shared workflows. It is local-only, deterministic, advisory, and read-only.

Use cases

• AI platform teams onboarding a new model across several agents.
• Governance reviewers checking compatibility, limits, fallback, and rollback evidence.
• Operators comparing model readiness before routing production work.

Requirements

• Python 3 with standard-library modules only.
• Redacted inline text or one explicit local notes file.
• No API keys required.
• Compatible with the standard OpenClaw skill layout and local script execution.

Example usage

python3 scripts/cross_agent_model_compatibility_verifier.py --text "agent platform documented; provider identifier documented; model identifier documented; authentication reference documented; context limit documented; tool call test documented; structured output test documented; rate limit documented; cost ceiling documented; fallback route documented; failure evidence documented; rollback plan documented" --json

Expected output: JSON with result: "PASS", signal coverage, and mutated_files: []. Missing evidence returns REVIEW; multiple risk signals or very low coverage returns BLOCKED.

Price

$4.99