Your agents run 24/7.
Your token bill runs blind.

$847 last week. One agent. No explanation.

Your agent ships a code review. The API bill says $847. You open the dashboard. It shows tokens in, tokens out, total cost. That's it. No breakdown by agent. No breakdown by skill. No idea that your context.md was re-injected 40 times, that the debug skill retried 14x in a loop, or that half your tool definitions were never called. The money is gone. You don't know where. You don't know why. It'll happen again tomorrow.

Analyze. Compare. Cut.

An analysis engine built for agentic workloads. It tells you why your agents are expensive, compares performance across models, and gives you the levers to fix it.

• cost breakdown Spend per agent, per skill, per session, per tool call. Not just a monthly total.
• context mapping Which context files, system prompts, and memory injections cost the most tokens. Find the bloat.
• multi-model Compare cost and quality across Claude, GPT, Gemini, and open-source. Same task, different models. Know when Haiku does the job Opus is doing.
• loop detection Automatic alerts when agents enter retry storms or skill loops. Before $5 becomes $500.
• optimization Actionable recommendations: prune unused tools, compress context, set circuit breakers. One-click fixes.
• guardrails Per-agent and per-session spend limits. Auto-pause or downgrade models when budgets hit.

The difference.

Burning tokens? Tell us.

We're building this from real pain. If you've been hit by a surprise token bill, watched agents loop, or just want visibility into what's actually happening, we want to hear it. 15-min call, no pitch.