anthropic

Anthropic’s Claude API platform for building AI products, apps, and agent workflows with Claude models, built-in tools, pricing tiers, and developer docs.

WakaWiki is a Rust CLI that generates and keeps agent-facing documentation up to date for a codebase. It supports multiple model providers, a zero-LLM scan mode, incremental updates, and AGENTS.md integration, with CI-friendly GitHub Actions usage documented in the README.

OpenWiki is a CLI for generating and keeping agent-oriented documentation up to date for a codebase. The repo shows installation, init and update commands, interactive and one-shot usage, and support for multiple model providers.

Wizard is a self-extending autonomous agent shipped as a single Rust binary. It supports local and hosted models, live provider switching, MCP tools, self-modification, a messaging gateway, and built-in benchmarking.

A vocabulary-driven graph memory library for AI agents, with storage backends, indexing pipelines, and MCP servers for building persistent structured memory into agent workflows.

Intencion is a product analytics and observability platform for AI agents. It tracks user intent, tool calls, run outcomes, and resolution trends, then turns failures or unmet requests into Linear or GitHub issues.

An open-source CLI for testing LLM prompts across consistency, latency, cost, and behavior, with HTML reports and support for OpenAI and Anthropic.

A Windows system-tray app that shows Claude Code session and weekly rate-limit usage at a glance, with hover and click views for more detail.

Python package for recording real LLM API responses and replaying them in tests so LLM-driven code can run deterministically without live API calls.

A desktop browser that hallucinates web pages on the fly with an LLM, including interactive apps and customizable “lenses” for different styles of generated sites.

Anthropic research article on Claude interpretability, presenting evidence for a J-space and a global-workspace-like mechanism in language models.

AI-powered code review tool that analyzes git diffs and produces structured review reports, with support for GitHub Action workflows and multiple model providers.

Traicer is a developer tool that captures selected AI coding conversations, redacts secrets, encrypts traces, and stores them in seller-controlled S3-compatible storage for later marketplace use.

Yogen is a self-hosted AI swarm that uses 500 agents to debate an idea and produce a verdict and written report. It targets decision support for startup ideas, product changes, and other uncertain choices, with both a hosted demo and local setup using an Anthropic API key.

AI agent that runs plain-text manual test cases in a real browser. It pastes step-by-step tests into Chrome, executes them live, and reports pass, fail, or warn per step with support for captcha and OTP pauses.

TypeScript middleware that trims or compresses LLM chat history to fit a token budget, with support for OpenAI, Anthropic, and AI SDK integrations.

Self-hosted AI observability for tracking LLM requests, costs, latency, prompt traces, reasoning tokens, and PII masking across many model providers.

Python library for managing LLM conversation history with cache-friendly message ordering, dynamic context, and compaction.

FastAPI backend for the Brush Up tutor app. It retrieves from a markdown note corpus, expands context through graph neighbors, and calls Anthropic to generate grounded programming help for Python, Ruby, and JavaScript.

Minimal Erlang library for calling OpenAI and Anthropic models, with tool-use support and a built-in JSON encoder/decoder.

A GitHub repository of system-prompt overrides for Claude Code, aimed at shrinking the always-on prompt and adjusting behavior for Opus 4.7. It includes a detailed rationale, measured prompt-size reductions, and install steps using tweakcc-fixed.

A curated learning roadmap for building production AI agents, covering OpenAI, Anthropic, MCP, harnesses, evals, memory, and safety. The README organizes the material into phases with exercises and a prioritized reading table.

Anthropic research report on how people use Claude Code in practice, based on a large privacy-preserving analysis of session data. It covers task types, division of labor between user and model, and how domain expertise affects outcomes.