let it loop (LIL): Deterministic AI engineer for complex coding. Hybrid LLM+Python with CONTRACT SYSTEM parsing intent, decomposing goals, enforcing checks, deterministic Python orchestration. Durable
let it loop (LIL) is an autonomous macro-task orchestration and verification control loop for AI coding agents. It provides a durable, production-grade execution backbone featuring automated DAG contract planning, crash-resilient supervisor execution (Write-Ahead Logging), deterministic multi-phase verification, multi-lens quality reviews, and universal Model Context Protocol (MCP) support.
- Autonomous DAG Planning: Decomposes natural language objectives into cryptographically scoped, strongly-typed JSON contract dependency graphs with cycle detection. - Fault-Tolerant Supervisor Loop: State journal with WAL (Write-Ahead Logging), crash recovery, Win32/POSIX atomic file-locking, and bounded 3-strike retries with strategy mutation. - Zero-Trust Verification Engine: 8 distinct deterministic acceptance check kinds (AST syntax parsers, command exit-code assertions, regex matchers, file validators, size bounds, and undeclared output detectors). - Multi-Lens Quality Plane: Multi-perspective evaluation with 5 specialized lenses (Code Correctness, Security Hardening, Documentation Fidelity, Test Completeness, Adversarial Architecture Audit) and formal arbitration. - Native Model Context Protocol (MCP) Server: 8 stdio JSON-RPC tools connecting directly with Claude Code, OpenAI Codex, Cursor, Google Antigravity, Hermes Agent, OpenCode, Cline, and Windsurf. - 10 Pluggable Worker Adapters: Native execution interfaces for Claude Code, OpenAI Codex, Google Antigravity (agy), OpenCode, Hermes Agent, Cline, Aider, Omniroute gateways, local scripts, and direct LLMs. - Zero-Subscription In
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Terminal discovery hub and package manager for AI coding tools, MCP servers, and agent skills. Built with Python & Textual
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