Discover the Best AI Resources
Curated essentials, no noise — just what matters
Provides a set of Agent Skills that let LLM agents read, edit, and manipulate Obsidian files (Markdown, Bases, JSON Canvas) and interact with Obsidian via the CLI. Implements the Agent Skills spec for use with Claude Code, Codex CLI, and OpenCode, enabling automated note workflows and RAG over an Obsidian vault.
A Claude Code plugin for long-form serial fiction that keeps characters, timeline, and world rules consistent across hundreds of chapters. Facts are committed to a versioned state store, and review gates flag contradictions before each chapter.
Displays live session status inside Claude Code — token-accurate context bar, usage, active tools, running agents, and todo progress in a compact statusline. Uses Claude Code's native statusline API and is configurable for terminal workflows.
Registry where OpenClaw agents publish, version, and vector-search text-based skills — each a SKILL.md plus supporting files. Adds a CLI with install pinning and moderation, plus a unified catalog that lists native code and bundle plugins beside skills.
Provides a DiT-based audio–video foundation model plus an official Python inference and LoRA trainer. Ships multiple production-ready pipelines (text/image/audio→video), checkpoints, and performance optimizations (FP8, distilled pipelines) for high-fidelity synchronized audio–video generation.
Implements a Manus-style, file-backed planning workflow for AI agents using a three-file Markdown pattern (task_plan.md, findings.md, progress.md) to persist plans, findings and session logs—reducing context drift and enabling session recovery. Adds IDE/CLI hooks to re-read plans and verify completion.
Indexes full text of visited web pages and local files on a self‑hosted server so you can search your personal knowledge from a web UI, terminal, CLI, or an AI assistant. Runs without mandatory telemetry, offers a browser extension for automatic capture, and supports optional semantic search via a configurable embeddings endpoint.
Enables parallel speculative decoding by using a lightweight block-diffusion draft model to produce multi-token drafts for faster, high-quality generation. Integrates with vLLM, SGLang and Transformers backends and ships draft models on Hugging Face.
Provides a Python API, CLI, and agent skill to programmatically access Google NotebookLM — exposing features the web UI omits (batch imports/exports, PPTX slides, mind‑map JSON) and integrating with LLM agents like Claude Code and Codex.
Real‑time full‑duplex speech‑to‑speech system that controls conversational role via text prompts and voice timbre via audio-conditioned embeddings. Built on Moshi; optimized for low-latency, persona-consistent spoken interactions.