phone-call
Place outbound AI phone calls via Bland AI: book reservations, make appointments, ask businesses questions, then report back the transcript and summary.
Browse reusable Agent Skills, each with a clear purpose and practical guidance.
Place outbound AI phone calls via Bland AI: book reservations, make appointments, ask businesses questions, then report back the transcript and summary.
Operator's guide to the YC CLI (`yc`) for the Gini batch demo — scoped to the yc commands the demo actually uses: the validated browser-forward login flow (tmux + browser_connect) and investor research against Bookface. Assumes yc is installed but NOT logged in yet. Load before staging or running the demo.
Inspect and interact with running Windows app UIs from the command line using UI Automation (UIA). Use when an AI agent or developer needs to inspect a UI element tree, find controls, take screenshots, click buttons, read or set text, or verify UI state in a running Windows app. Works with any framework WinUI 3, WPF, WinForms, Win32, Electron.
Download the Simulation Challenge LeRobot v2.1 training datasets from ModelScope using ./scripts/download_dataset.sh. Pulls task-suite data (instruction / manipulation / sim2real) from the agibot_world/GenieSim3.0-Dataset repo into a local dir. Trigger: When the user asks to "下载训练数据", "下载数据集", "拉取 lerobot 数据", "download training data", "download the dataset", "get the lerobot v2.1 data", "download task suite", mentions download_dataset.sh, ModelScope GenieSim3.0-Dataset, or needs training data to train a challenge model.
Entry point for the Simulation Challenge skill set. Use when the user mentions the challenge, leaderboard, submitting a model, or any of the /api/challenge/* endpoints — this skill picks the right downstream skill for them.
Use when the contestant needs to obtain or refresh their Simulation Challenge JWT (CHALLENGE_TOKEN), or wants to inspect the current logged-in user. Trigger words include "log in", "token", "401", "current user", "name", "refresh".
Use to track a Simulation Challenge job's progress — list jobs, fetch a job's per-task scores, or pull execution logs when a job ended in Failed. Read-only; safe to run without confirmation.
Use when the contestant wants to submit a model evaluation job to the Simulation Challenge — POST /api/challenge/job. This is a quota-consuming, side-effecting action; always confirm with the user first. Captures JOB_UUID, PARALLELISM, TUNNEL_ENDPOINT for the rest of the pipeline.
Turn a natural-language scene request into a Genie Sim scene — an LLM writes a Scene-Language DSL program (`LLM_RESULT.py`), and `geniesim_generator.app` compiles it into `scene.usda` + a layout graph under benchmark/config/llm_task/. Works either through the Open WebUI agent, OR by having Claude write the DSL program directly and run the compiler (no WebUI / no MCP server needed). Trigger: When the user asks to "生成一个场景", "按需求生成场景", "generate a scene", "make a scene with <objects>", "build a tabletop layout", "create scene.usda from a description", "直接写脚本生成场景", "绕过 webui 生成场景", or wants the generator to produce a scene from a prompt.
Drive `geniesim_world` to produce a photorealistic, explorable 3D world from a single equirectangular panorama — uses the `geniesim_world create` CLI (Click subcommand), pairs SHARP + DA360 to fuse panorama RGB with metric depth, and optionally upscales with Real-ESRGAN. Trigger: When the user asks to "generate a world", "生成 3D 世界", "pano to 3D", "PanoRecon", "make a scene from a photo", "create a world from a panorama", or references `geniesim_world` / a `.png` panorama input.