dvcrn OpenClaw Model Router Skill
Deterministic model routing with a closed-loop production switch pipeline.
Why use this skill
- Explicit user intent routing (
@codex,@mini) - Time-window model policy (
router.schedule.json) - Safe switch flow with verification and rollback
- Concurrency lock to prevent race conditions
- Structured audit logs for operations and incident review
Core capabilities
- Prefix routing
@codex→openai-codex/gpt-5.3-codex@mini→minimax/MiniMax-M2.5- Aliases:
@c,@m
- Scheduler routing
- Rule-based windows by day/time/priority
- Timezone-aware resolution (
router.schedule.json.timezone) - Supports overnight windows (e.g. 18:00 → 09:00)
- Production switch loop
schedule apply/schedule end- Auth gate (
auth.requiredEnv[]) - Switch + readback verify
- Failure classification (
auth_expired,rate_limit,provider_drift,unknown) - Optional rollback (
safety.rollbackOnFailure) - Lock file (
safety.lockPath) to avoid concurrent switching - Audit logs (
router.log.jsonl+ rotation)
Quick commands
# Validate config
node src/cli.js validate
# Route inspection
node src/cli.js route "@codex implement this" --json
# Scheduler
node src/cli.js schedule validate
node src/cli.js schedule resolve --at "2026-03-02T10:00:00+01:00" --json
node src/cli.js schedule apply --json
node src/cli.js schedule end --id workday_codex --json
Key config files
router.config.json(prefix map, retry, auth, safety, logging, controller)router.schedule.json(timezone + rules)
Reliability checklist
- Deterministic mapping
- Idempotent switching behavior
- Execute only after switch verification
- Observable success/failure events
- Recoverability on failure paths
Tests
node --test