image-to-video

Q: How do I install image-to-video?

Run npx skills add https://github.com/prime-skills/runcomfy-agent-skills --skill image-to-video in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/image-to-video/ (personal) or .claude/skills/image-to-video/ (project).

by prime-skillsMedia & Creative

Animate any still image on RunComfy — this skill is a smart router that matches the user's intent to the right i2v model in the RunComfy catalog. Picks HappyHorse 1.0 I2V (Arena 1, native audio, identity preservation) for general animations, Wan 2.7 with audiourl for custom-voiceover lip-sync, or Seedance 2.0 Pro for multi-modal animation from image + reference video + reference audio. Bundles each model's documented prompting patterns so the caller gets sharper output without burning iterations on the wrong model. Calls runcomfy run / /image-to-video (or endpoint variant) through the local RunComfy CLI. Triggers on "image to video", "image-to-video", "i2v", "animate image", "make this move", or any explicit ask to turn a still into video.

Installs: 438.6K
Last 24h: +528
Trending rank: #642
Security: Pass

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/prime-skills/runcomfy-agent-skills --skill image-to-video

01
Install
Run the command in your project. The CLI asks which agents to install for.
02
Describe the task
Ask your agent for something this skill covers. It loads image-to-video automatically when relevant.
03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.

Security audits

Independent scans of the skill's instructions and bundled files.

Gen Agent Trust Hub PassSAFE ·The 'image-to-video' skill is a router for AI video generation models on the RunComfy platform. It facilitates image-to-video tasks by invoking the RunComfy CLI. The skill follows security best practices, including safe token storage and JSON-based command input to prevent shell injection. It primarily interacts with official RunComfy domains for model execution and media downloads.

Socket PassNo alerts

Snyk PassLOW ·Risk: LOW · No issues

SKILL.md

The instructions your agent reads when the skill is triggered.

Image-to-Video — Pro Pack on RunComfy

runcomfy.com · HappyHorse I2V · Wan 2.7 · Seedance 2.0 Pro · GitHub

Image-to-video, intent-routed. This skill doesn't lock you to one model — it picks the right i2v model in the RunComfy catalog based on what the user actually wants: portrait animation, custom-voiceover lip-sync, or multi-modal composition.

npx skills add agentspace-so/runcomfy-skills --skill image-to-video -g

Pick the right model for the user's intent

User intent	Model	Why
Animate a portrait — keep identity stable	HappyHorse 1.0 I2V	#1 on Artificial Analysis Arena (Elo 1392); strong facial fidelity
Product reveal / 360 / macro motion	HappyHorse 1.0 I2V	Geometry preservation + smooth camera moves
Native synchronized ambient audio in one pass	HappyHorse 1.0 I2V	In-pass audio synthesis
Animate and lip-sync to a custom voiceover track	Wan 2.7 + `audio_url`	Accepts your own MP3/WAV (3–30s, ≤15MB) and drives lip-sync to it
Multi-language dub variants (same image, different audio per call)	Wan 2.7 + `audio_url`	Same shot, swap `audio_url` per language
Multi-modal — image + reference video + reference audio together	Seedance 2.0 Pro	Up to 9 image refs, 3 video refs (2–15s each), 3 audio refs
Brand-consistent narrative with character ref + scene ref + voice ref	Seedance 2.0 Pro	Image holds identity, video holds scene, audio holds voice
Default if unspecified	HappyHorse 1.0 I2V	Best all-round quality + native audio

The agent reads this table, classifies the user's intent, and picks the matching subsection below.

Prerequisites

RunComfy CLI — npm i -g @runcomfy/cli
RunComfy account — runcomfy login opens a browser device-code flow.
CI / containers — set RUNCOMFY_TOKEN=<token>.
A source image URL — JPEG/PNG/WebP, min 300px, ≤10MB; aspect 1:2.5 to 2.5:1 (HappyHorse) — other models have similar specs.

Route 1: HappyHorse 1.0 I2V — default for portrait / product / general animation

Model: happyhorse/happyhorse-1-0/image-to-video · Arena rank: #1 (Elo 1392)

Schema

Field	Type	Required	Default	Notes
`image_url`	string	yes	—	JPEG/JPG/PNG/WEBP. Min 300px. Aspect 1:2.5–2.5:1. ≤10MB.
`prompt`	string	yes	—	≤5000 non-CJK or 2500 CJK chars. Motion / camera / lighting description.
`resolution`	enum	no	`1080P`	`720P` or `1080P`.
`duration`	int	no	5	3–15 seconds.
`seed`	int	no	0	Reuse for variant comparisons.
`watermark`	bool	no	true	Provider watermark toggle.

Output aspect = input aspect. No independent reframing.

Invoke

runcomfy run happyhorse/happyhorse-1-0/image-to-video \
  --input '{
    "image_url": "https://.../portrait.jpg",
    "prompt": "Gentle camera drift around the subject'\''s face, subtle breathing motion, identity-stable features, soft natural light."
  }' \
  --output-dir <absolute/path>

Prompting tips

Lead with motion verbs: "drift", "dolly in", "orbit", "tilt up", "reveal", "blink", "breathe". Front-load what's MOVING.
Don't restate the image — the model sees it. Focus tokens on what changes.
Preservation goals explicit: "identity-stable features", "packaging unchanged", "background geometry stable".
Lighting evolution: "rim light intensifying", "shadows shortening as camera rises".
One beat per clip — single primary motion (orbit OR dolly OR tilt OR character action).

Route 2: Wan 2.7 + `audio_url` — when the user has a custom voiceover

Model: wan-ai/wan-2-7/text-to-video (NOT /image-to-video — Wan 2.7's t2v endpoint accepts an audio_url that drives lip-sync)

Note on i2v with Wan 2.7: Wan 2.7's primary i2v animation isn't on a dedicated endpoint here. For pure i2v (image animated by motion prompt only), prefer HappyHorse i2v. Use Wan 2.7 specifically when the user has a custom audio track they want lip-synced to a generated talking-head clip.

Schema (Wan 2.7 t2v with audio)

Field	Type	Required	Default	Notes
`prompt`	string	yes	—	Up to ~5000 chars. Describe the talking-head shot: framing, lighting, motion.
`audio_url`	string	yes (for lip-sync)	—	WAV/MP3, 3–30s, ≤15MB. Drives lip-sync.
`aspect_ratio`	enum	no	`16:9`	`16:9`, `9:16`, `1:1`, `4:3`, `3:4`.
`resolution`	enum	no	`1080p`	`720p` or `1080p`.
`duration`	enum	no	`5`	2–15 (whole seconds). Match your audio length.
`negative_prompt`	string	no	—	Concrete issues to avoid (e.g. "no subtitles, no flicker").
`seed`	int	no	—	Reproducibility.

Invoke

runcomfy run wan-ai/wan-2-7/text-to-video \
  --input '{
    "prompt": "Medium close-up of a confident spokesperson in a softly-lit recording booth, leaning slightly toward the camera, locked tripod, shallow DOF, warm key light from camera-left.",
    "audio_url": "https://.../voiceover-en.mp3",
    "duration": 12,
    "aspect_ratio": "9:16"
  }' \
  --output-dir <absolute/path>

Prompting tips

Describe the talking-head shot — framing, lighting, lens feel. The audio drives the lip-sync; the prompt builds the visual frame around it.
Match duration to audio length — clip will be silent past the audio if too long.
Use negative_prompt for issues: "no subtitles, no flicker, no distorted hands".
For multi-language dubs — same prompt, swap audio_url per call. Lock seed for visual consistency across languages.

Route 3: Seedance 2.0 Pro — multi-modal animation (image + ref video + ref audio)

Model: bytedance/seedance-v2/pro

Use when the user wants a single clip that combines: a subject image + scene from a reference video + voice tone from a reference audio.

Schema (Seedance 2.0 Pro, i2v-relevant fields)

Field	Type	Required	Default	Notes
`prompt`	string	yes	—	CN ≤500 chars OR EN ≤1000 words.
`image_url`	array	yes (for i2v)	`[]`	0–9 images. First is the primary subject.
`video_url`	array	no	`[]`	0–3 reference clips (MP4/MOV), 2–15s each.
`audio_url`	array	no	`[]`	0–3 reference audio (WAV/MP3), 2–15s, < 15MB each.
`aspect_ratio`	enum	no	`adaptive`	`adaptive`, `16:9`, `9:16`, `4:3`, `3:4`, `1:1`, `21:9`.
`duration`	int	no	5	4–15 (whole seconds).
`resolution`	enum	no	`720p`	`480p` or `720p`.
`generate_audio`	bool	no	true	In-pass synchronized speech / SFX / music.
`seed`	int	no	—	Reproducibility.

Invoke

runcomfy run bytedance/seedance-v2/pro \
  --input '{
    "prompt": "Subject from image 1 walks through the café in video 1, voice tone matches audio 1. Medium close-up, slow push-in, warm light, gentle ambience.",
    "image_url": ["https://.../subject.jpg"],
    "video_url": ["https://.../cafe-locked-shot.mp4"],
    "audio_url": ["https://.../voice-tone.mp3"],
    "duration": 8
  }' \
  --output-dir <absolute/path>

Prompting tips

Image vs text division — use image_url for what must stay stable (face, costume, brand); use prompt for what should evolve (action, mood, lighting).
Number the refs in the prompt: "subject from image 1, lighting from video 1, voice from audio 1". Seedance routes cues correctly.
Reference media specs — videos / audio must be 2–15s; audio < 15MB.
Don't mix radically different aesthetics — if image 1 is a watercolor and video 1 is photoreal, output drifts.

Limitations

Each route inherits its model's limits. HappyHorse: 15s cap, output aspect = input aspect. Wan 2.7: 15s cap, audio 3–30s/15MB. Seedance: 720p ceiling on this template, 15s cap.
No multi-route blending. This skill picks one model per call. If the user wants HappyHorse animation + Wan-style lip-sync in the same clip, that's two calls + a stitch (out of scope here).
Brand-specific overrides — if the user named a specific model variant not listed (e.g. Wan 2.6, Seedance 1.5), route to the corresponding brand skill (wan-2-7, seedance-v2) instead of forcing it through here.

Exit codes

code	meaning
0	success
64	bad CLI args
65	bad input JSON / schema mismatch
69	upstream 5xx
75	retryable: timeout / 429
77	not signed in or token rejected

Full reference: docs.runcomfy.com/cli/troubleshooting.

How it works

The skill picks one of HappyHorse 1.0 I2V / Wan 2.7 t2v+audio / Seedance 2.0 Pro based on user intent and invokes runcomfy run <model_id> with the matching JSON body. The CLI POSTs to the Model API, polls the request, fetches the result, and downloads any .runcomfy.net/.runcomfy.com URL into --output-dir. Ctrl-C cancels the remote request before exit.

Security & Privacy

Token storage: runcomfy login writes the API token to ~/.config/runcomfy/token.json with mode 0600 (owner-only read/write). Set RUNCOMFY_TOKEN env var to bypass the file entirely in CI / containers.
Input boundary: the user prompt is passed as a JSON string to the CLI via --input. The CLI does NOT shell-expand the prompt; it transmits the JSON body directly to the Model API over HTTPS. No shell injection surface from prompt content.
Third-party content: image / mask / video URLs you pass are fetched by the RunComfy model server, not by the CLI on your machine. Treat external URLs as untrusted; image-based prompt injection is a known risk for any image-edit / video-edit model.
Outbound endpoints: only model-api.runcomfy.net (request submission) and *.runcomfy.net / *.runcomfy.com (download whitelist for generated outputs). No telemetry, no callbacks.
Generated-file size cap: the CLI aborts any single download > 2 GiB to prevent disk-fill from a malicious or runaway model output.

FAQ

What does the image-to-video skill do?

How do I install image-to-video?

Run npx skills add https://github.com/prime-skills/runcomfy-agent-skills --skill image-to-video in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/image-to-video/ (personal) or .claude/skills/image-to-video/ (project).

Which AI agents can use image-to-video?

Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.

Is image-to-video safe to install?

Security partners have reviewed it: Gen Agent Trust Hub passed; Socket passed; Snyk passed. As with any skill, read the SKILL.md and bundled scripts before installing.

Who maintains image-to-video?

It is published by prime-skills in prime-skills/runcomfy-agent-skills. It has 438,589 recorded installs.