Open-source desktop app for local voice cloning, voice design, video dubbing, dictation, transcription, and audiobook creation across 646 languages.
Python CLI and agent plugin that audits whether an AI agent does the job it is supposed to do, using adversarial and operational tests.
Builds a queryable knowledge graph from a codebase and its docs, PDFs, and configs, driven by a /graphify skill for AI coding assistants.
A local proxy that lets Claude Code, Codex, OpenCode and other coding agents run on free or alternative model providers.
Compresses tool outputs, logs, files, RAG chunks and conversation history before they reach an LLM, as a library, proxy, or MCP server.
A high-throughput LLM inference and serving engine featuring PagedAttention, continuous batching, and an OpenAI-compatible API server.
Open-source plugins that specialize Claude for knowledge-work roles like sales, legal, finance, and support, for use in Claude Cowork.
CLI and setup toolkit that gives AI agents read and search access to Twitter, Reddit, YouTube, GitHub, Bilibili, and XiaoHongShu.
Local CLI, MCP server, and catalog for searching, selecting, validating, and previewing installs of 2,700+ reusable SKILL.md agent playbooks.
Agent memory system that lets AI agents learn from experience over time, not just recall conversation history.
A multi-harness collection of plugins, agents, skills, and commands for AI coding tools like Claude Code, Codex CLI, and Cursor.
Python library and SDK that builds a hierarchical tree index of documents so an LLM can reason through it for retrieval, without vector databases or chunking.
Claude Code plugin that runs parallel SEO audits covering technical SEO, E-E-A-T, schema, GEO, and agent readiness.
Python library that uses LLMs and graph-based pipelines to extract structured data from websites and local documents from a natural-language prompt.
CLI and template catalog for configuring Claude Code with agents, commands, settings, hooks, MCP integrations, and monitoring tools.
A library of model optimization techniques (quantization, pruning, distillation, NAS, speculative decoding, sparsity) that exports compressed checkpoints for inference frameworks.