Enables monitoring of running agent loops with token and monetary cost estimation, pruning of verbose thinking chains near limits, and routing sub-tasks between fast/cheap and deep reasoning models. It provides deterministic, MCP-compatible budget optimization for autonomous agents and copilot frameworks.
Reduces token consumption for AI coding agents by 50-70% through intelligent code context filtering, Git delta tracking, and local SQLite/Tree-sitter indexing.
MartinLoop is the independent governance and financial control layer for AI coding agents. Set hard spend limits, prevent runaway loops, enforce verification, trigger rollback on failure, and generate auditable receipts showing what changed, what it cost, and whether the work passed.