cost-control

An open-source Python tool that controls AI agent loops using real-time convergence signals instead of a fixed max-iterations cap, with rollback and adapters for popular agent frameworks.

LLMCap is a proxy for LLM API calls that hard-stops requests when a dollar cap is reached, with support for major providers and companion tools for VS Code, CLI, and Windows.

tokentoll is a GitHub Action and CLI that scans Python and JavaScript/TypeScript code for LLM API calls, estimates spend, and blocks pull requests when cost or model-policy thresholds are exceeded.

Self-hosted LLM gateway for cost-aware model routing, spend tracking, and policy-based traffic control across multiple providers.

A long-form technical article on building ship-ready AI agents in Rails with the Anthropic Ruby SDK, covering tool design, agent loops, MCP servers, human approval, testing, and cost control.