Looplane uses a static model-role catalog and retries or falls back only after retryable provider errors. Cache data is a provider hint plus trace, while cost is a static-table estimate; neither is live routing intelligence or a bill.
Claude Code's prompt caching works by exact prefix matching: a cache read bills at roughly 10% of the standard input rate, but switching models, changing effort, enabling fast mode, toggling MCP servers, or denying an entire tool forces the next turn to reprocess everything. The TTL defaults to five minutes; the main conversation and a few helper requests on a subscription get one hour.
Hermes supports 40+ providers, and the consumer-subscription OAuth paths are where billing surprises live: Anthropic OAuth only spends Claude Max extra-usage credits, and Claude Pro can't use it at all. Auxiliary tasks default to `provider: auto`, meaning your expensive main model does compression and vision grunt work. The fallback chain is a one-shot switch per session, not continuous retry.
A detailed look at OpenAI's Codex agent loop design: how prompts are constructed, how multi-turn conversations are managed, how prompt caching prevents cost explosions, and how context window auto-compaction works.
OpenClaw's failover runs in two stages: rotate auth profiles within the provider, then fall back to another model. But what really governs behavior is who chose the model — a model you picked yourself with /model is strict, and its failure is reported rather than answered by some other model.