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.
Collects Claude Code commands, agents, skills and engineering best practices with ready CLAUDE.md templates and orchestration examples. Focuses on reusable agent workflows, hooks, and MCP integrations for productionizing Claude-based coding/automation.
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.
Packages reusable GitHub Copilot building blocks — agents, prompts, instructions, and skills — to make AI-assisted coding repeatable and standards-aligned for a team. Built around an RPI (Research, Plan, Implement) workflow in VS Code.
Visual, example-driven guide for using Claude Code: structured learning path, copy‑paste templates, and diagrams that show how to combine slash commands, hooks, subagents and MCP into production workflows.
Packages Salesforce development workflows as on‑demand Agent Skills (SKILL.md, scripts, assets) that let AI assistants scaffold Apex/LWC, author Flows, run SOQL, and manage metadata and permission sets. Optimized for Agentforce Vibes and usable by any tool that supports the Agent Skills specification.
Unifies team email, chat, docs, tasks, CRM, calls and AI agents into a single workspace with bidirectional @-linking and a shared, exportable team memory.
Drives penetration testing from chat commands, orchestrating 100+ security tools through an MCP-native multi-agent engine on CloudWeGo Eino. Adds attack-chain graphs, risk scoring, and human-in-the-loop approval gates for authorized use.
Runs recurring workplace tasks across 100+ tools (Slack, GitHub, Gmail, Notion, Linear) as scheduled sub-agents that triage errors, draft outreach, and compile daily briefs. Each run executes in an isolated Firecracker microVM with scoped permissions.
Provides a frontend-design skill plus 20 steering commands and curated anti-patterns to steer LLMs toward clearer, accessible UI designs. Designed to plug into AI harnesses (Cursor, Claude/Gemini CLI, code agents) for auditing, critiquing, and polishing interfaces.
Combines a vector store, Cypher-style graph queries, and on-device LLM inference in one Rust engine, with a graph neural network that reranks results and adapts to query patterns in under a millisecond. Services ship as self-contained .rvf containers.
Provides an in‑IDE interface for IntelliJ IDEA to interact with Anthropic Claude Code and OpenAI Codex for AI-assisted coding. Supports dual-engine switching, file-aware context, session history, agent skills, MCP extensions, and security/permission controls.