OptimoClaw
An open-source optimization panel for OpenClaw AI agent fleets. Gives you actual controls over token spend, model routing, and agent performance instead of just read-only dashboards.
The Spark
I’ve been running multi-agent systems with OpenClaw and kept hitting the same problem: the cost black box. When you’re running a fleet of agents, every heartbeat, every model call, every context window is burning tokens. But there’s no intuitive way to see where the spend is going or do anything about it without digging through config files.
You shouldn’t need to be a config expert to understand what your agents are costing you.
Why I Built This
Most observability tools for agents are read-only dashboards. They show you charts and metrics but give you no way to actually change anything. I wanted something different: a control surface with actual levers. Model routing controls, tuning sliders, optimization presets, and a recommendation engine that tells you what to change and why.
The design philosophy is simple: use token counts and published pricing rates instead of billing API integration. That eliminates credential requirements and lets you start optimizing immediately.
What It Does
Token Optimizer lets you see model routing with token usage and pricing, then adjust default models, heartbeat frequency, compaction thresholds, session context, memory scope, and subagent concurrency.
Session Insights shows context utilization and cache efficiency with actionable optimization recommendations.
Agent Analyzer gives per-agent detail views showing active models, heartbeat config, active sessions, and cache efficiency.
Where It’s Going
Right now we have no good way to know whether an agent is actually performing well. Token counts and cache ratios tell you about infrastructure. They don’t tell you whether an agent handled a task effectively.
The next step is task-level telemetry and outcome signals. Not just a tuning dashboard, but a performance layer for agents that treats effectiveness as a first-class metric alongside cost.
Current Status
OptimoClaw is open source (MIT license) and free. It’s built with Next.js and React, runs on the same machine as your OpenClaw gateway, and connects via WebSocket for live agent data plus CLI integration for config changes.
There’s also an OptimoClaw Skill that brings optimization directly into OpenClaw agents, analyzing live configs and calculating costs across Anthropic, OpenAI, and Ollama models.