happyhorse-1-0

Generate text-to-video with HappyHorse 1.0 on RunComfy. Documents HappyHorse 1.0's strengths (#1 on Artificial Analysis Video Arena, native 1080p with in-pass synchronized audio, multi-shot character consistency, 6-language prompt support), the duration / aspect-ratio / resolution schema, and when to route to Wan 2.7 / Seedance 2 / LTX 2 instead. Calls `runcomfy run happyhorse/happyhorse-1-0/text-to-video` through the local RunComfy CLI. Triggers on "happyhorse", "happy horse", "happyhorse 1.0", "happyhorse video", or any explicit ask to generate video with this model.

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Updated: less than a month ago
In the catalog since: 1 Oct 2026
From: runcomfy-com/skills

Get it through your agent npx skills add runcomfy-com/skills@happyhorse-1-0

Skill instructions

Rendered from the published SKILL.md, 179 lines.

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)

You want	Use
Multi-shot story with character / wardrobe consistency	HappyHorse 1.0
Native audio in the same generation pass	HappyHorse 1.0
Currently-#1 blind-vote video model	HappyHorse 1.0
Detailed lip-synced dialogue + reference video	Seedance 2.0 Pro
Fine motion control + multi-reference conditioning	Wan 2.7
Ultra-fast iteration (sub-second per frame)	LTX 2
Cinematic motion editing on existing footage	Kling Video O1

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

Prerequisites

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

Endpoints + input schema

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

Field	Type	Required	Default	Notes
`prompt`	string	yes	—	Up to 2,500 chars. 6 languages (CN/EN/JP/KR/DE/FR).
`aspect_ratio`	enum	no	`16:9`	`16:9`, `9:16`, `1:1`, `4:3`, `3:4` only.
`resolution`	enum	no	`1080P`	`720P` or `1080P`.
`duration`	int	no	5	3–15 seconds.
`seed`	int	no	0	0..2^31-1. Reuse for variant comparisons.
`watermark`	bool	no	true	Provider watermark.

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

Use case	Why HappyHorse 1.0
Multi-shot brand stories with one consistent character	Native cross-shot identity preservation
Talking-head explainers needing in-clip voiceover + ambient	Synchronized audio in the same pass
Multilingual short-form ads	6 prompt languages, no script-quality drop
Cinematic 1080p delivery	Native 1080p output, broadcast-ready
Blind-vote leader for general video quality	#1 on Artificial Analysis Video Arena

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 harness
skis across lunar plain, leaving parallel tracks in gray regolith.
Mid-stride, poles planted, pushing in 1/6th gravity with subtle upward
drift. Fine dust haze along ski tracks. Crescent Earth above lunar
horizon, blue-white glow against black sky. Raw sunlight, crushed
shadows, no fill. 8K photorealistic.

Multi-shot consistency:

Show the whole skill (59 more lines)

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


**Vertical platform-native:**

9:16 vertical short. A barista in a black apron pulls a single espresso shot, steam rising into the morning sun, rich crema slowly forming. Close-up handheld, shallow DOF, warm cafe ambience and the hiss 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:

| code | meaning |
|---|---|
| 0  | success |
| 64 | bad CLI args |
| 65 | bad input JSON / schema mismatch (e.g. `duration: 30` would 422) |
| 69 | upstream 5xx |
| 75 | retryable: timeout / 429 |
| 77 | not signed in or token rejected |

Full reference: [docs.runcomfy.com/cli/troubleshooting](https://docs.runcomfy.com/cli/troubleshooting?utm_source=skills.sh&utm_medium=skill&utm_campaign=happyhorse-1-0).

## 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.

Get it through your agent

Call the Graph-of-Skills MCP server's retrieve_skill_bundle tool and it returns this skill's text inside your budget.

{
  "tool": "retrieve_skill_bundle",
  "arguments": {
    "query": "happyhorse-1-0"
  }
}

New to this? Set up Graph-of-Skills or get a free key. The text on this page comes from its authors: how skills are sourced and what we check. If none fits your task, your agent can write a skill for your own library. To keep a skill from your own library on a machine, see how to install one of your skills.

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Source

Source repository runcomfy-com/skills
Listing on skills.sh

From runcomfy-com/skills via skills.sh

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