Total 50,615 skills, AI & Machine Learning has 8484 skills
Showing 12 of 8484 skills
Autonomous iterative research loop. Takes a topic, runs web searches, fetches sources, synthesizes findings, and files everything into the wiki as structured pages. Based on Karpathy's autoresearch pattern: program.md configures objectives and constraints, the loop runs until depth is reached, output goes directly into the knowledge base. Triggers on: "/autoresearch", "autoresearch", "research [topic]", "deep dive into [topic]", "investigate [topic]", "find everything about [topic]", "research and file", "go research", "build a wiki on".
Generate videos from text prompts (and optional reference or frame images) using OpenRouter's asynchronous video generation API. Use when the user asks to create, generate, or make a video or animation from a description, animate an existing image, or turn a prompt into a short video clip.
Assesses how ready a business is for AI adoption across six dimensions. Evaluates data maturity, tech stack, team skills, process documentation, budget, and culture. Generates a comprehensive ai-readiness-report.md with scores, gap analysis, and recommended starting points. Aligned with OneWave AI's audit methodology.
When the user wants to build or improve a sales bot's ability to manage sender reputation and ensure messages get delivered. Also use when the user mentions "deliverability," "spam prevention," "sender reputation," "email warmup," or "domain reputation."
When the user wants to build or improve a sales bot's ability to pull in firmographic or contact data mid-conversation. Also use when the user mentions "data enrichment," "lead enrichment," "pulling company data," "contact data lookup," or "real-time data."
RLM-style large-codebase comprehension — build a mental map of any codebase by dispatching sub-agents to explore regions without bloating main context
Diagnose a recurring failure (STUCK task, clustered CI error, frequent reverts) by dispatching sub-agents to digest CI logs without bloating main context. Returns one root-cause diagnosis.
Multi-source research synthesis — aggregate and compare 3+ sources or any source >5KB using sub-agent dispatch and SharedState
Use when the user wants Luma / 拾光 / 拾光智能体 / 拾光工具 to create a complete viral-remix short-video workflow: research, rewrite, TTS, digital human, PIP materials, subtitles, BGM, and cover.
Manage Luma / 拾光 cloud assets used by generation tools, including voices, avatars, fonts, media inputs, and named groups.
Install Zero and load version-matched workflows with zero skills.
BEVFusion for multi-sensor 3D object detection. Fuses LiDAR point clouds and camera images in bird's-eye-view (BEV) space, used in autonomous driving for robust 3D perception. Use when training, evaluating, or running inference for a TAO BEVFusion model. Trigger phrases include "train BEVFusion", "LiDAR + camera fusion", "BEV 3D detection", "multi-sensor 3D perception".