--- id: daily-happyhorse-1-0 name: "happyhorse-1-0" url: https://skills.yangsir.net/skill/daily-happyhorse-1-0 author: agentspace-so domain: multimedia tags: ["video-generation", "text-to-video", "generative-ai", "realistic-video"] install_count: 121300 rating: 4.80 (11 reviews) github: https://github.com/agentspace-so/runcomfy-agent-skills --- # happyhorse-1-0 > 阿里巴巴 HappyHorse 1.0 文本生成视频模型，生成物理逼真的视频内容 **Stats**: 121,300 installs · 4.8/5 (11 reviews) ## Before / After 对比 ### 逼真视频制作成本 **Before**: 制作物理逼真的视频需要专业设备、场地和演员，加上后期特效处理，一个 15 秒场景成本超过 5000 元，周期 3-5 天 **After**: 直接描述场景自动生成物理逼真视频，无需拍摄场地和演员，15 秒场景成本低于 10 元，3 分钟完成生成，质量接近实拍效果 | Metric | Before | After | Change | |---|---|---|---| | 制作成本 | 5000元 | 10元 | -99% | | 制作周期 | 4天 | 0.02天 | -99% | ## Readme # happyhorse-1-0 # HappyHorse 1.0 — Pro Pack on RunComfy [runcomfy.com](https://www.runcomfy.com/?utm_source=skills.sh&utm_medium=skill&utm_campaign=happyhorse-1-0) · [Text-to-video](https://www.runcomfy.com/models/happyhorse/happyhorse-1-0/text-to-video?utm_source=skills.sh&utm_medium=skill&utm_campaign=happyhorse-1-0) · [GitHub](https://github.com/agentspace-so/runcomfy-skills/tree/main/happyhorse-1-0) **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=` 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": ""}' \ --output-dir ``` **Vertical short (9:16, 8s, no watermark):** ``` runcomfy run happyhorse/happyhorse-1-0/text-to-video \ --input '{ "prompt": "", "aspect_ratio": "9:16", "duration": 8, "watermark": false }' \ --output-dir ``` **Cheaper test pass (720p):** ``` runcomfy run happyhorse/happyhorse-1-0/text-to-video \ --input '{"prompt": "", "resolution": "720P", "duration": 3}' \ --output-dir ``` 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](https://docs.runcomfy.com/cli/troubleshooting?utm_source=skills.sh&utm_medium=skill&utm_campaign=happyhorse-1-0). ## 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//status` every 2 seconds. - On terminal status, the CLI fetches `GET .../requests//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//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. Weekly Installs10.6KRepository[agentspace-so/r…t-skills](https://github.com/agentspace-so/runcomfy-agent-skills)First SeenTodaySecurity Audits[Gen Agent Trust HubPass](/agentspace-so/runcomfy-agent-skills/happyhorse-1-0/security/agent-trust-hub)[SocketPass](/agentspace-so/runcomfy-agent-skills/happyhorse-1-0/security/socket)[SnykPass](/agentspace-so/runcomfy-agent-skills/happyhorse-1-0/security/snyk) --- *Source: https://skills.yangsir.net/skill/daily-happyhorse-1-0* *Markdown mirror: https://skills.yangsir.net/api/skill/daily-happyhorse-1-0/markdown*