happyhorse-1-0

Q: How do I install happyhorse-1-0?

Run npx skills add https://github.com/prime-skills/runcomfy-agent-skills --skill happyhorse-1-0 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/happyhorse-1-0/ (personal) or .claude/skills/happyhorse-1-0/ (project).

by prime-skillsMedia & Creative

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.

Installs: 436.7K
Last 24h: +524
Trending rank: #659
Security: Pass

Install

Works with every agent the skills CLI supports.

npx skills add https://github.com/prime-skills/runcomfy-agent-skills --skill happyhorse-1-0

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 happyhorse-1-0 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 ·This skill facilitates text-to-video generation using the HappyHorse 1.0 model via the RunComfy platform. It utilizes the official @runcomfy/cli to manage model requests, poll for status, and download results to a user-specified local directory. The skill includes documentation on secure token management and describes the use of JSON encapsulation to prevent command injection from user-provided prompts.

Socket PassNo alerts

Snyk PassLOW ·Risk: LOW · No issues

SKILL.md

The instructions your agent reads when the skill is triggered.

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:

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.

How it works

The skill invokes runcomfy run happyhorse/happyhorse-1-0/text-to-video with a JSON body matching the schema.
The CLI POSTs to https://model-api.runcomfy.net/v1/models/happyhorse/happyhorse-1-0/text-to-video with the user's bearer token.
The Model API returns a request_id; the CLI polls GET .../requests/<id>/status every 2 seconds.
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.
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.

FAQ

What does the happyhorse-1-0 skill do?

How do I install happyhorse-1-0?

Run npx skills add https://github.com/prime-skills/runcomfy-agent-skills --skill happyhorse-1-0 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/happyhorse-1-0/ (personal) or .claude/skills/happyhorse-1-0/ (project).

Which AI agents can use happyhorse-1-0?

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 happyhorse-1-0 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 happyhorse-1-0?

It is published by prime-skills in prime-skills/runcomfy-agent-skills. It has 436,662 recorded installs.