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Transforms enterprise architecture governance into a structured, AI-assisted workflow covering principles, requirements, risk, procurement and design reviews. Bundles templates, CLI/plugins and autonomous research agents (MCP integrations) to keep traceability and compliance.
Provides 22 scripts that let Claude Code build, test, and interact with iOS apps by wrapping xcodebuild and controlling the simulator via simctl/idb. Uses accessibility-driven UI navigation, progressive build summaries, and compressed screenshots to cut token cost and fragility for AI agents and developers.
Turns documentation sites, GitHub repos, PDFs, videos and other sources into ready-to-use skill packs for Claude, Gemini, OpenAI and RAG frameworks like LangChain. Detects conflicts across sources, transcribes video, and exports to 21 formats.
Provides 134 ready-to-use Agent Skills that let AI agents execute multi-step scientific workflows (bioinformatics, cheminformatics, imaging, clinical research). Each skill includes curated docs and examples plus unified access to 100+ scientific databases and common Python packages — for agents that support the Agent Skills standard.
A library of ~140 ready-to-use Agent Skills that turn a coding agent (Claude Code, Cursor, Codex) into a science assistant across biology, chemistry, medicine, and drug discovery, with connectors to 100+ scientific databases and Python analysis tools.
Desktop app that runs many CLI coding agents — Claude Code, Codex, Cursor, Gemini — in parallel, each in its own git worktree and branch. A built-in diff viewer, terminal, and PR tracking let you dispatch and review 10+ agents at once.
Lets AI agents (Claude Code, Codex, Cursor, and others) register through a guide and join a shared paper-trading arena, where they publish signals, debate ideas, and copy-trade each other across stocks, crypto, and Polymarket markets.
Automates multi-step web tasks by perceiving webpages as pixels and issuing low-level mouse, keyboard and scroll actions. A 7B-parameter multimodal agent trained on 145K synthetic trajectories (FaraGen), designed for on-device deployment and efficient task completion (~16 steps/task).
Agent memory that learns over time instead of just recalling past chats: retain/recall/reflect primitives turn interactions into facts, experiences, and mental models. Reports top LongMemEval scores; self-hostable with Python and Node SDKs.
Drives an LLM-powered agent to autonomously research, write, and ship ML code by accessing Hugging Face docs, datasets, repos, and cloud compute. Provides interactive CLI and headless modes, approval gates, tool routing, and integrations for HF, GitHub, and Anthropic models.
Visual workspace for managing multiple LLM-powered coding agent sessions and iterating on code, docs, and mockups. Combines WYSIWYG editors, session kanban, task tracking, and git tooling so developers can review, approve, and integrate agent-generated changes.
Builds knowledge-grounded AI agents by combining hybrid RAG retrieval with a visual, block-based workflow editor, keeping question-answering tied to your own data. Supports document import, reranking, MCP, and self-hosted deployment.