Spending tokens blind drains your whole budget Tokdash v2.7.0 shipped Oct 24. 8 open-source GitHub repos for tracking token spend and capping agent budgets: 22.8k stars as of Oct 24. MIT and Apache-2.0. Pushed Oct 19–24. MEASURE THE BURN 01. codeburn ★11.6k ▸ → spend by model, project, task 02. tokscale ★5.7k ▸ → token and cost CLI across agents 03. Tokdash ★87 ▸ → local dashboard with quota resets PRICE EACH CALL 04. genai-prices ★401 ▸ → price table for LLM calls CAP THE SPEND 05. floe-guard ★347 ▸ → hard stop before budget ceiling 06. cycles-server ★5 ▸ → reserve budget before agent acts 07. ai-gateway ★2.3k ▸ → quotas and attribution at gateway 08. openmeter ★2.4k ▸ → usage metering and enforcement pip install floe-guard from floe_guard import BudgetGuard guard = BudgetGuard(limit_usd=5.00) the stack: logs → count → price → guard → reserve → quota → meter Wrong ceiling stops a live agent. Not the model. The blind spend around it. Full cost stack in the terminal ↓