developer tools

Aerial is a local-first Rust tool for agent-to-agent messaging and orchestration, with durable mailboxes, a supervisor, and an MCP adapter. The page shows what it does, how it works, and basic install commands.

An AI skill that plans and optimizes vehicle delivery routes from natural language using Routing24’s WebMCP tools. It supports multi-stop route planning, shareable outputs, and installation for compatible agents like Claude or Cowork.

A monthly poll that asks developers which AI coding agents they use and publishes the results.

A CLI tool that deterministically routes prompts between local and hosted LLMs without making a model call to decide. It emphasizes offline operation, configurable calibration, and demo modes for seeing routing decisions and savings.

A side-by-side comparison of 15 AI agent frameworks, including LangGraph, CrewAI, AutoGen, Pydantic AI, OpenAI Agents SDK, Mastra, Vercel AI SDK, LangChain, LlamaIndex, Haystack, Dify, Flowise, n8n, Semantic Kernel, and smolagents. The page highlights use-case fit, control style, language support, GitHub stars, and fra

AdvertBench is a web app for ranking AI-generated image ad sets with Elo voting. The page shows head-to-head ad comparisons, a leaderboard, and a sample prompt for generating ads, making the product purpose easy to understand.

Read-only Kubernetes context engine that turns cluster state into structured context for SREs, scripts, and AI agents. It offers CLI commands for explain, graph, trace, health, dump, and a read-only HTTP API.

Autolang is a scripting language and compiler for AI agent code, designed to run untrusted AI-written scripts in a controlled environment with restricted access to registered functions.

A post about TMA1 v2, a local observability and context-sharing tool for coding agents. It adds an MCP server, hook-based context injection, and cross-agent sharing between Claude Code and Codex.

A docs index page for Claude Code that maps the documentation structure and links to major sections like getting started, core concepts, tools, automation, and deployment.

A technical blog post about using devcontainer + Nix + Docker, plus small helper tools, to keep one reproducible dev environment working for humans, CI, and AI agents.

AIllowpages is an AI tools search engine with 2,500+ curated tools, category filters, instant search, and an AI helper that suggests tools from a user’s goal.

Open-source collection of AI agent skills for Kotlin projects, with skill naming guidance, installation options, and examples for Claude Code and Codex.

An open-source desktop client for editing LLM context with a separate AI model, context maps, compression tools, and revision rollback.

A security-focused article about a Git configuration attack path affecting multiple AI coding agents, with concrete reproduction details and vendor response notes. It also introduces grith, described as an OS-level security proxy for AI coding agents.

A lightweight Markdown variant designed to reduce token usage for LLM consumption using single-character markers and context-aware parsing.

A practical article explaining how to run AI models directly in the browser with Transformers.js, including setup, how it works, browser support, and example use cases like translation and grammar checking.

A governance framework for multi-agent AI systems, with agent lifecycle controls, memory, runtime hooks, and quick-start scaffolding for governed projects.

OpenAI’s model documentation page for the API, with navigation into model selection, pricing, reasoning, text and code, embeddings, moderation, and related developer docs.

Stripe’s llms.txt entry surfaces core docs, API reference, SDKs, webhooks, Checkout, Connect, and a note to always check the latest package version before installing.

A safety-evaluation harness for AI agents operating physical equipment. It validates proposed robot intent against declared hardware and deployment limits, records machine-readable refusal reasons, and includes a sample corpus plus a runnable evaluation script.

HyperSAE is a Python package for mechanistic interpretability that trains hyperbolic sparse autoencoders on LLM activations. The page includes installation steps, a quickstart example, benchmark tables, and a short software architecture overview.

Aakit is a developer tool for measuring and tracking assumptions made by coding agents, linking each assumption to supporting code and flagging which ones fail. The repo includes a clear explanation of the idea, prior art, and early experiment results.

A standalone CLI coding agent from Warp that runs in any terminal and supports multi-model routing, persistent sessions, full-screen terminal apps, and cloud-agent handoff.