AI Agent2025
Declares and installs agent dependencies from an apm.yml manifest—skills, prompts, agents, plugins and MCP servers—with transitive resolution, security auditing, plugin packaging, and cross-host registries so agents are reproducible across repos.
AI Agent2025
Audits source code for security flaws using LLM agents, then auto-generates and runs proof-of-concept exploits in Docker sandboxes to confirm which findings are real. Retrieves CWE/CVE knowledge via RAG; runs on hosted or local Ollama models.
AI Agent2025
Lets AI agents describe interactive UIs as declarative JSON instead of executable code; client apps render the components with native widgets from a pre-approved catalog, keeping agent-generated UI safe across trust boundaries.
AI Agent2025
A library of 232 ready-made AI agent personas across 16 divisions — engineering, design, marketing, sales, security, finance, and more. Each defines a role, workflow, and concrete deliverables rather than just a prompt template.
AI Infra2025
Generates production-grade synthetic datasets from scratch or from seed data using dependency-aware samplers, LLM-backed text columns, built-in validators, previewing, and LLM-as-judge scoring.
AI Coding2025
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.
Embodied AI2025
Detects motion from Wi‑Fi channel state information (CSI) on cheap ESP32 boards and integrates natively with Home Assistant; offers an optional on‑device ML detector that requires no calibration.
AI Dataset2025
Provides mined hard negatives and relevance scores for 1.88M queries across seven retrieval datasets, enabling contrastive fine-tuning and nv-retrieve filtering; includes full 2048 mined negatives per query, paired query/document splits, and parquet-formatted files for large-scale training.
AI Agent2025
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.
AI Dataset2025
Aggregates SEC EDGAR filings into raw files, parsed plaintext, and rich filing metadata for LLM training and retrieval. Includes ~8.05M filings (~590 GB, ~43B tokens), per-filing token counts, and parsed outputs; Apache-2.0.
AI Infra2025
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.
AI Image2025
Turn plain-English requests into editable draw.io diagrams: the model writes the underlying draw.io XML, which renders live in an embedded canvas. Upload images, PDFs, or text to replicate, refine through chat, and roll back via version history.