Setup & Installation
Or with the ClawHub CLI, for registry-managed skill folders outside a full OpenClaw workspace:
Version History
Remove slack target, default all CLI commands to dry-run, add file modification docs
What This Skill Does
Reduces OpenClaw AI API costs by routing most requests to Claude Haiku, offloading heartbeats to local or alternative providers, enabling prompt caching, and trimming loaded context size. All changes preview before writing, and backups are created automatically before any modification.
Combines model routing, multi-provider heartbeat offloading, prompt caching, and config rollback into a single CLI with dry-run preview, rather than requiring manual edits across multiple config files.
When to use it
- Switching routine coding tasks from Sonnet to Haiku to cut token spend
- Routing OpenClaw heartbeats to a local Ollama instance instead of paid API
- Previewing config diffs before applying changes in a CI pipeline
- Setting daily and monthly spend caps to prevent runaway API bills
- Rolling back to a previous config after an optimization produces unexpected behavior
Example Workflow
Here's how your AI assistant might use this skill in practice.
User asks: reduce my OpenClaw API costs
- 1Run `python cli.py analyze` to inspect current model routing and heartbeat configuration
- 2Run `python cli.py optimize` to generate a diff preview of proposed changes
- 3Review the diff showing Haiku as default model, caching enabled, and budget limits added
- 4Run `python cli.py optimize --apply` to write changes to ~/.openclaw/
- 5Run `python cli.py verify` to confirm the new configuration is active
OpenClaw configured with Haiku as default model, prompt caching enabled, and daily/monthly budget limits set, with a timestamped backup of the previous config saved to ~/.openclaw/backups/