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.

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.

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.

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.