HappyHorse 1.0 — Pro Pack on RunComfy

HappyHorse 1.0 — Pro Pack on RunComfy

runcomfy.com · Text-to-video · GitHub

HappyHorse 1.0 — currently #1 on Artificial Analysis Video Arena (Elo 1333 t2v / 1392 i2v) — hosted on the RunComfy Model API. Native 1080p video with in-pass synchronized audio (dialogue, ambient, Foley) and multi-shot character consistency.

npx skills add agentspace-so/runcomfy-skills --skill happyhorse-1-0 -g

When to pick this model (vs siblings)

If the user said "HappyHorse" / "happy horse video" explicitly, route here regardless.

Prerequisites

1. RunComfy CLI — npm i -g @runcomfy/cli
2. RunComfy account — runcomfy login opens a browser device-code flow.
3. CI / containers — set RUNCOMFY_TOKEN=<token> instead of runcomfy login.

Endpoints + input schema

happyhorse/happyhorse-1-0/text-to-video

How to invoke

Default (16:9 1080p 5s):

runcomfy run happyhorse/happyhorse-1-0/text-to-video \  --input '{"prompt": "<user prompt>"}' \  --output-dir <absolute/path>

Vertical short (9:16, 8s, no watermark):

runcomfy run happyhorse/happyhorse-1-0/text-to-video \  --input '{    "prompt": "<user prompt>",    "aspect_ratio": "9:16",    "duration": 8,    "watermark": false  }' \  --output-dir <absolute/path>

Cheaper test pass (720p):

runcomfy run happyhorse/happyhorse-1-0/text-to-video \  --input '{"prompt": "<user prompt>", "resolution": "720P", "duration": 3}' \  --output-dir <absolute/path>

The CLI submits, polls every 2s until terminal, then downloads any *.runcomfy.net / *.runcomfy.com URL from the result into --output-dir. Stdout is the result JSON. Stderr is progress.

Prompting — what actually works

Describe motion over time, not a still. "A woman turns from the window, walks two paces to the desk, picks up the cup, lifts it to her face, takes a sip" beats "a woman drinking coffee".

Camera + shot in plain English. Front-load the shot: "Wide shot. ..." / "Tracking shot. ..." / "Locked tripod, low angle. ..." works as a real directive. Specify lens feel: "35mm anamorphic", "shallow DOF", "crushed shadows".

One visual beat per clip when iterating. Don't pile up "she walks AND the dog runs AND a car passes". Pick the beat, get it sharp, then layer with multi-shot prompts.

Multi-shot consistency — when describing two beats, restate the anchor at each: "Shot 1: tall woman in red wool coat, blue scarf, in a rainy alley. Shot 2: same woman in red coat / blue scarf, now ducking under an awning." HappyHorse holds the look but needs the anchor.

Audio direction — say what you want to hear: "distant temple bells, footsteps on wet pavement, no dialogue" or "warm friendly tone, English".

Anti-patterns:

• Static-frame descriptions (no temporal verbs) → motion will be vague.
• Conflicting style directions → cancels.

• 2500 char prompts → degrades.

• Aspect ratios outside the 5 supported → 422.

Where it shines

Sample prompts (verified to produce strong results)

From the model page (cinematic scope):

Wide shot. A lone astronaut in dusty orange suit with blue-gray harnessskis across lunar plain, leaving parallel tracks in gray regolith.Mid-stride, poles planted, pushing in 1/6th gravity with subtle upwarddrift. Fine dust haze along ski tracks. Crescent Earth above lunarhorizon, blue-white glow against black sky. Raw sunlight, crushedshadows, no fill. 8K photorealistic.

Multi-shot consistency:

Shot 1: Medium close-up. A woman in a navy trench coat enters arain-slick neon-lit Tokyo alley, looks left, holds up an umbrella.Shot 2: Same woman in same navy trench, now under the awning of aramen shop, shaking water off the umbrella. Warm interior glow, softchatter, gentle rain on metal roof in the audio.

Vertical platform-native:

9:16 vertical short. A barista in a black apron pulls a singleespresso shot, steam rising into the morning sun, rich crema slowlyforming. Close-up handheld, shallow DOF, warm cafe ambience and thehiss of the steam wand.

Limitations

• Duration cap 15s — for longer narratives, segment into multi-shot prompts and stitch.
• Aspect ratios — only the 5 documented values; ultra-wide cinematic gets cropped or rejected.
• Audio is in-pass only — you can't pass external audio to drive lip-sync. For audio-driven lip-sync, use Wan 2.7 (which accepts an audio_url) or Seedance 2.0 Pro.
• No free image-to-video on this template — i2v is supported by HappyHorse via a separate pipeline; the t2v endpoint here is text-only.

Exit codes

The runcomfy CLI uses sysexits-style codes:

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

How it works

1. The skill invokes runcomfy run happyhorse/happyhorse-1-0/text-to-video with a JSON body matching the schema.
2. The CLI POSTs to https://model-api.runcomfy.net/v1/models/happyhorse/happyhorse-1-0/text-to-video with the user's bearer token.
3. The Model API returns a request_id; the CLI polls GET .../requests/<id>/status every 2 seconds.
4. On terminal status, the CLI fetches GET .../requests/<id>/result and downloads any URL whose host ends with .runcomfy.net or .runcomfy.com into --output-dir. Other URLs are listed but not fetched.
5. Ctrl-C while polling sends POST .../requests/<id>/cancel so you don't get billed for GPU you stopped.

What this skill is not

Not a self-hosted video runner. Not a capability grant — depends on a working RunComfy account.

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.