按代理任务做模型基准并形成选型 Playbook

• You have representative OpenClaw task samples (tool calls, multi-step chains, failure retries).
• At least 2-3 candidate models are available for A/B comparison.

1. Define benchmark dimensions first: success rate, retry behavior, injection safety, and cost/latency.
2. Run each model on identical task set and log pass/fail with failure reasons.
3. Separate ‘basic tool-call pass’ from ‘edge-case robustness’ when ranking models.
4. Pick default model by weighted score, then schedule monthly re-runs to catch regressions.

• This Reddit benchmark references external methodology/results; validate with your own workload before adopting globally（需验证）。
• Do not optimize solely for score; include operational constraints such as quota, rate limits, and compliance.

This tip is aggregated from community/public sources and preserved with attribution.