Discover the Best AI Resources

notebooklm-py

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.

jcode

Terminal-first coding agent harness for multi-session LLM workflows, offering session memory, provider integrations, browser automation, and swarm collaboration. Tuned for low RAM and very fast startup to support many concurrent sessions.

PersonaPlex

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.

Skills

Archive of all versions of agent 'skills' backed up from clawdhub.com — a historical snapshot that includes potentially suspicious or malicious skills; intended for analysis and research, not for running unvetted code.

UI Skills

Provides a set of versioned "skills" that codify UI design standards and automated checks for design engineers and AI agents. Includes a CLI to discover, install, and run skills like baseline UI rules, accessibility fixes, motion-performance tuning, and metadata corrections.

Destructive Command Guard (dcg)

Intercepts and blocks destructive git, filesystem and CLI commands before they execute when run by AI coding agents. Offers sub-millisecond hook latency, 50+ modular rule packs, heredoc/inline-script AST scanning, agent-specific integrations and configurable bypass/allow-once workflows.

Ralph

Runs an autonomous agent loop that uses AI coding tools (Amp or Claude Code) to implement PRD user stories iteratively, persisting context via git history, progress.txt and prd.json; designed for small, CI-backed tasks.

codex-lb

Pools multiple ChatGPT/Codex accounts behind a local OpenAI-compatible proxy and dashboard — provides request load balancing, per-account usage/cost tracking, API-key management, and configurable routing strategies.

Hyper-Extract

Transforms unstructured documents into strongly-typed Knowledge Abstracts with one CLI command, extracting entities and relations into graphs, hypergraphs, and spatio‑temporal structures. Includes 80+ templates, multiple RAG engines, local vLLM support, Obsidian export and an MCP server.

Headroom

Compresses any context sent to LLMs (tool outputs, DB reads, RAG results, files, logs) to cut tokens by ~70–95% while preserving reversible originals; runs as a proxy or Python/TypeScript SDK with integrations for common agent frameworks.

pi-subagents

Enables Pi to delegate tasks to focused child agents for code review, parallel audits, background jobs, and saved workflows. Supports foreground and background runs, session artifacts, worktree isolation, and built-in role agents to simplify orchestration.

Pocket TTS

Generates low-latency, streaming text-to-speech entirely on CPUs (no GPU or cloud API required), using an ~100M-parameter model with voice cloning and multilingual support. Optimized for low resource use (2 CPU cores, ~200ms to first audio chunk) — suited for local, privacy-sensitive, or embedded TTS.