AI Developer Tool AI Tools

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.

OpenWorkers is a thesis-focused research assistant that searches literature, verifies citations, critiques ideas, and produces structured research support without writing the prose for the student.

Raidho is an open-source coding agent that separates planning and execution across different model providers and adds durable VSA-based memory across runs. The repo includes install steps, provider options, CLI usage, and benchmark evidence.

Klent is an AI agent guardrails product that sits between agents and their tools, letting teams allow, deny, pause, rewrite, or redirect tool calls with policies, human approval flows, and audit trails.

Local encrypted vault that captures supported AI assistant sessions from Claude, Codex, Cursor, OpenClaw, and similar tools, then normalizes and stores them for search and review.

Runtime authorization platform for AI agents with open-source SDKs in Python, TypeScript, Go, Java, and Rust. The page says the hosted service is in production, supports per-action checks, scoped delegation, revocable tokens, and a shared authorization model across MCP tools, agent-to-agent calls, and direct API integr

A Rust reimplementation of the 1982 ZX Spectrum BASIC runtime, compiled to native binaries and WebAssembly, with a live browser demo. The page frames it as an AI software-engineering experiment and describes the interpreter, editor, screen, keyboard, and runtime behavior it recreates.

A Commodore 64 chat client for Claude that streams Anthropic responses over a serial-style connection, with a Python proxy and C64-side UI.

A blog post describing ptc_runner’s MCP server and code-mode approach, where agents run short-lived untrusted programs inside a small Lisp REPL instead of Python or JavaScript.

An open-source experiment that adds a small zero-initialized overlay layer to a frozen GPT-2 so its behavior can be adjusted at inference time without retraining the base model.