Provides a Claude Code plugin marketplace that supplies modular skills for security research, vulnerability detection, and audit workflows. Includes scanners, analysis skills, and developer tooling to embed LLM-assisted security checks into existing pipelines.
Provides an operator-grade system and reusable toolkit for building, running, and securing agentic workflows across multiple LLM harnesses — skills, hooks, memory, MCP integrations, and security scanning for production agent deployments.
Desktop + CLI agent-native client for managing multi-session conversations, connecting to multiple LLM providers and external data sources, and creating shareable agent skills and automations without editing code.
A collection of role-specific plugins for Claude Cowork and Claude Code that encode skills, slash commands, and connectors so teams can turn process, tools, and company context into reusable, file-based components for knowledge-work workflows.
Researches the last 30 days of public discussion across Reddit, X, Bluesky, YouTube, TikTok, Instagram, HN and Polymarket, then synthesizes a citation-rich briefing and copy-paste prompts. Multi-source scoring, comparative mode, and optional watchlist; requires API/auth for some sources.
Provides a catalog of NVIDIA-verified, portable “skills” — instruction sets that teach AI agents how to use NVIDIA libraries, models and platform tools. Each skill is published with detached signatures and evaluation artifacts for verifiable reuse in agent workflows.
Generates protocol-bound GEP prompts that guide iterative evolution of AI agent behavior from runtime logs, producing auditable EvolutionEvents and reusable Genes/Capsules. Node.js-based and works offline; optional EvoMap network integration enables skill sharing, worker pools and leaderboards while git provides rollback and validation.
Provides a workflow layer for OpenAI Codex CLI to bootstrap stronger Codex sessions, add reusable agent roles/skills, and manage durable project state under .omx. Includes team runtime, canonical skills, and monitoring surfaces.
Creates human-directed teams of AI agents (via GitHub Copilot) that live in your repo, persist knowledge, and coordinate development work. Key features: repo-first persistence, watch/triage automation, and an extensible CLI/SDK — alpha software, Copilot-dependent.
Turns a single Claude Code session into a coordinated game-development studio by providing 49 specialized AI agents, 72 slash-command skills, automated hooks and path-scoped rules. Includes tiered roles, engine-specific agent sets (Godot/Unity/Unreal) and templates to keep design, QA and release in sync.
Runs durable, checkpointed SQL workflows inside PostgreSQL so long-running data and AI pipelines can resume after crashes without external orchestrators. Provides a SQL DSL, in-process background worker, and Postgres-backed state—useful for embeddings, ETL, scheduling, and fan-out jobs when you can install extensions.
Provides a reliability layer for self-hosted LLM tool-calling and multi-step agent workflows. Adds guardrails — rescue parsing, response validation, retry nudges, and a synthetic respond tool — and ships a Drop-in OpenAI-compatible proxy plus a WorkflowRunner for structured loops.