General
40,579 installs
ControlNet & Pose
by agentspace-so/runcomfy-agent-skills
Pose-conditioned generation on RunComfy via the `runcomfy` CLI. Routes across Kling 2-6 Motion Control Pro / Standard (transfer the motion / blocking of a…
Skill content
Pose-conditioned image and video generation routed across Kling Motion Control, Wan 2-2 Animate, and Z-Image ControlNet LoRA. - Routes video pose-transfer requests to Kling 2-6 Motion Control (Pro or Standard) to apply reference video motion onto a target character, or to Wan 2-2 Animate for audio-driven stylized animation with pose conditioning - Routes still-image pose-conditioned generation to Z-Image Turbo ControlNet LoRA, accepting OpenPose, DWPose, canny, or depth control images paired with a text prompt - Triggered by keywords including "controlnet," "pose control," "openpose," "motion control," "depth control," and related pose-driven or skeleton-based generation requests - Invoked via runcomfy run CLI with reference video/character URLs or control image URLs and prompts; supports multi-condition ControlNet stacks via dedicated ComfyUI workflows for complex conditioning needs ControlNet & Pose Condition image or video generation on a pose, skeleton, or motion reference. This skill routes across the pose-driven Model API endpoints reachable today and points the agent at ComfyUI workflows for richer ControlNet rigs. runcomfy.com · Kling motion control · CLI docs Powered by the RunComfy CLI # 1. Install (see runcomfy-cli skill for details) npm i -g @runcomfy/cli # or: npx -y @runcomfy/cli --version # 2. Sign in runcomfy login # or in CI: export RUNCOMFY_TOKEN=<token>