llm-agents

Runtime safety net for LLM agents that detects runaway token growth, classifies failure patterns, and suggests fixes without extra LLM calls. The project includes a Rust core, Python SDK, examples, benchmarks, and benchmark claims across multiple models and runs.

A TypeScript library for deterministic context folding in long-running LLM agent sessions, designed to preserve prompts, avoid extra summarization calls, and keep provider caches hot.

Go-native framework for building, orchestrating, and observing AI agents with native OpenTelemetry, an embedded dashboard, replay, and first-party MCP/A2A support.

Go-based multi-source search CLI for LLM agents with session-based workflows, paginated result reading, and support for web, HN, Reddit, GitHub, YouTube, and multiple search APIs.

LLM Wiki is a plugin and instruction-file based system that turns LLM agents into a research and knowledge-base workflow with session memory, parallel research, source ingestion, and wiki compilation.

A self-hosted TypeScript harness for building provider-neutral LLM agent systems inside an application or platform, with typed agent and workflow runtime, tool support, state, tracing, and example workspaces.

A service-boundary-aware coordination layer for heterogeneous LLM code agents via MCP. It combines versioned Markdown documents, pub-sub notifications, diff-aware updates, and a web dashboard for browsing, search, and AI chat.

A technical guide that shows how to build a small CLI-based LLM agent for microservices using tool discovery, model calls, conversation history, and a REPL loop.

A reference implementation for intent-execution separation in LLM agents. The project uses a typed intent layer (SIF) over domain vocabularies, with a deterministic execution layer and demo domains for legal and veterinary workflows.

An arXiv paper on reducing LLM inference cost for web automation by compiling browser tasks into a deterministic JSON workflow and executing them without repeated model calls.