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Agent Skill · 待分类

runwayml(runwayml 音频)

runwayml 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

runwayml 是待分类类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为接触敏感数据;许可证信息还不明确,第三方扫描有提醒项,按安装量在待分类类的 11,209 个 Skill 里排第 4,459。

总安装 737周安装 31GitHub Stars 30下载 258核验 2026-05-01

安装说明

本站只整理中文说明,不托管安装包,也不代用户安装。
GitHub
许可证
unknown

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:runwayml(runwayml 音频)
来源仓库:https://github.com/runwayml/skills
仓库路径:skills/runwayml
安装命令:
npx skills add https://github.com/runwayml/skills --skill runwayml
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/runwayml/skills --skill runwayml

这个 Skill 是做什么的

这个 Skill 的分类还没最终确定,用法以来源仓库的说明为准。

用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息。适合在 Codex、Claude、Cursor、Gemini CLI 中围绕仓库状态、代码变更或协作事项进行整理。可结合来源仓库、安装命令和原始 README 继续核验具体用法。

安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。安装方式:github,安装命令:npx skills add https://github.com/runwayml/skills --skill runwayml

来源仓库内路径:skills/runwayml

上手步骤

4 步
  1. 1

    确认自己的宿主工具

    公开资料标注支持 Codex、Claude、Cursor、Gemini CLI;先确认自己用的是其中之一,再按对应工具的 Skills 目录放置。

  2. 2

    拿到安装命令

    可以直接复制的命令是 npx skills add https://github.com/runwayml/skills --skill runwayml;命令里的占位符换成自己的路径或密钥再执行。

  3. 3

    安装后重启宿主

    命令执行完要完全退出宿主工具再打开,让新装的 Skill 被重新扫描到,否则列表里可能看不到。

  4. 4

    按最小权限试用

    它需要接触敏感数据,先在测试目录或测试账号里跑,确认没问题再放到正式项目。

常见问题

6 条

runwayml 怎么安装?

在终端执行 npx skills add https://github.com/runwayml/skills --skill runwayml。装完完全退出宿主工具再打开,让它重新扫描本地 Skill。

runwayml 支持哪些 AI 工具?

公开资料标注支持 Codex、Claude、Cursor、Gemini CLI。其他工具只要能读取本地 Skill 目录,一般也能手动放进去,但要自己确认触发方式是否一致。

runwayml 需要什么权限?

权限级别是接触敏感数据。该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

runwayml 是免费的吗?

公开资料没有标注明确许可证,收费和商用限制都无法确认。正式使用前请到来源仓库核对授权说明。

runwayml 用的人多吗?

公开数据是累计安装 737 次,近一周安装 31 次,下载 258 次,GitHub 30 星。这些数字来自第三方目录统计,只能当作热度参考,不代表质量或安全性。

runwayml 安全吗?

第三方扫描有提醒项,说明存在需要人工确认的行为。安装前请打开源码看清它读了什么、联网到哪里。

值得选的地方和要先想清楚的地方

值得选的地方

  • 同时适配 4 种工具,换客户端不用重新找替代品。

先想清楚的地方

  • 需要接触敏感数据,装到常用环境前要先评估影响面。
  • 许可证没有明确标注,能不能商用、能不能再分发都不确定。
  • 第三方扫描存在提醒项或未通过项,需要人工逐条确认。
  • 第三方目录整理,版本更新和行为细节以来源仓库为准。

适不适合你

更适合

  • 已经在用 Codex,想直接扩展它能力的人。
  • 需要处理待分类类任务、又不想每次都手写提示词的人。

不太适合

  • 环境里有大量密钥、凭证,不方便给第三方 Skill 读取的人。
  • 需要明确授权才能用到公司项目里的场景。
  • 需要厂商级技术支持和 SLA 的生产系统。

待分类类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
infsh-cli

infsh CLI · Codex、Claude

4,374,576382权限未标注未明确未收录
ai-video-generation

AI 视频生成 · Codex、Claude

4,313,376382调用外部服务未明确有提醒
lark-openapi-explorer

云雀 OpenAPI 浏览器 · Codex、Claude

2,064,1209,011需要联网未明确有提醒
lark-workflow-standup-report

Lark 工作流程站立报告 · Codex、Claude

2,041,6328,978需要联网未明确通过
use-my-browser

使用我的浏览器 · Codex、Claude

1,848,49140操作浏览器未明确未通过
runwayml

runwayml 音频 · 本页

73730接触敏感数据未明确有提醒

按安装量取同分类前几名;数字来自第三方目录统计,只作热度参考,不代表质量结论。

SKILL.md 原文

Runway API

Generate AI videos, images, and audio using Runway's API. Features Runway's latest Gen-4.5 model for high-quality text-to-video and image-to-video generation, plus Gen-4 variants and third-party models from Google (Veo, Gemini) and ElevenLabs.

Recommended: Use gen4.5 for best results - the newest and most capable video generation model.
Setup: See Installation Guide. API key goes in RUNWAYML_API_SECRET env var.

Quick Start

Python

from runwayml import RunwayML

client = RunwayML()

# Image-to-video with latest Gen-4.5 model
task = client.image_to_video.create(
    model="gen4.5",
    prompt_image="https://example.com/image.jpg",
    prompt_text="A timelapse on a sunny day with clouds flying by",
    ratio="1280:720",
    duration=10
).wait_for_task_output()

print(f"Video URL: {task.output[0]}")

# Text-to-video (no image required)
task = client.image_to_video.create(
    model="gen4.5",
    prompt_text="A serene mountain landscape at sunset with clouds drifting",
    ratio="1280:720",
    duration=10
).wait_for_task_output()

Node.js

import RunwayML from "@runwayml/sdk";

const client = new RunwayML();

// Image-to-video with latest Gen-4.5 model
const task = await client.imageToVideo
  .create({
    model: "gen4.5",
    promptImage: "https://example.com/image.jpg",
    promptText: "A timelapse on a sunny day with clouds flying by",
    ratio: "1280:720",
    duration: 10,
  })
  .waitForTaskOutput();

console.log(`Video URL: ${task.output[0]}`);

// Text-to-video (no image required)
const textTask = await client.imageToVideo
  .create({
    model: "gen4.5",
    promptText: "A serene mountain landscape at sunset",
    ratio: "1280:720",
    duration: 10,
  })
  .waitForTaskOutput();

cURL

# Image-to-video
curl -X POST "https://api.dev.runwayml.com/v1/image_to_video" \
  -H "Authorization: Bearer $RUNWAYML_API_SECRET" \
  -H "X-Runway-Version: 2024-11-06" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gen4.5",
    "promptImage": "https://example.com/image.jpg",
    "promptText": "A timelapse on a sunny day",
    "ratio": "1280:720",
    "duration": 10
  }'

# Text-to-video (no image required)
curl -X POST "https://api.dev.runwayml.com/v1/image_to_video" \
  -H "Authorization: Bearer $RUNWAYML_API_SECRET" \
  -H "X-Runway-Version: 2024-11-06" \
  -H "Content-Type: application/json" \
  -d '{
    "model": "gen4.5",
    "promptText": "A serene mountain landscape at sunset",
    "ratio": "1280:720",
    "duration": 10
  }'

# Poll for result (use returned task id)
curl "https://api.dev.runwayml.com/v1/tasks/{task_id}" \
  -H "Authorization: Bearer $RUNWAYML_API_SECRET" \
  -H "X-Runway-Version: 2024-11-06"

All Available Models

Video Generation

ModelInputPricingUse Case
gen4.5 ⭐Text or Image12 credits/secNewest & recommended - Best quality text/image-to-video (no audio)
gen4_turboImage5 credits/secFast image-to-video (no audio), iteration
gen4_alephVideo + Text/Image15 credits/secVideo-to-video transformation (no audio)
act_twoImage or Video5 credits/secCharacter performance/motion (no audio)
veo3Text or Image40 credits/secGoogle Veo high-quality video with audio
veo3.1Text or Image40 credits/secGoogle Veo 3.1 with keyframes & audio
veo3.1_fastText or Image15 credits/secGoogle Veo 3.1 faster/cheaper & audio

Image Generation

ModelInputPricingUse Case
gen4_imageText + References (optional)5 credits/720p, 8 credits/1080pHigh-quality with style transfer
gen4_image_turboText + References (required)2 credits/image (any res)Fast iteration
gemini_2.5_flashText + References5 credits/imageGoogle Gemini image gen

Audio Generation (ElevenLabs)

ModelInput → OutputPricing
eleven_multilingual_v2Text → Speech1 credit/50 chars
eleven_text_to_sound_v2Text → Sound Effects1 credit/6 sec
eleven_voice_isolationAudio → Clean Audio1 credit/6 sec
eleven_voice_dubbingAudio → Dubbed Audio1 credit/2 sec
eleven_multilingual_sts_v2Speech → Speech1 credit/2 sec
1 credit = $0.01. Get credits at dev.runwayml.com

Video Generation

Gen-4.5 (Text-to-Video and Image-to-Video)

The latest and most capable Runway model supporting both text-only and image-to-video generation.

Text-to-Video

Generate videos from text descriptions only:

task = client.image_to_video.create(
    model="gen4.5",
    prompt_text="A serene mountain lake at sunrise with mist rising from the water",
    ratio="1280:720",
    duration=10,
    seed=12345  # Optional: reproducibility
).wait_for_task_output()

Text-to-Video Aspect Ratios: Landscape 1280:720 (16:9) | Portrait 720:1280 (9:16)

Image-to-Video

Animate existing images with motion:

task = client.image_to_video.create(
    model="gen4.5",
    prompt_image="https://example.com/image.jpg",
    prompt_text="Camera slowly pushes in, leaves rustling in the breeze",
    ratio="1584:672",
    duration=10,
    seed=12345
).wait_for_task_output()

Image-to-Video Aspect Ratios:

  • Widescreen: 1280:720 (16:9), 1584:672 (21:9 ultra-wide)
  • Standard: 1104:832 (4:3)
  • Portrait: 720:1280 (9:16), 832:1104 (3:4)

Duration: 2-10 seconds | Pricing: 12 credits/second (60 credits minimum for 5 sec)

Gen-4 Turbo (Image-to-Video)

task = client.image_to_video.create(
    model="gen4_turbo",
    prompt_image="https://example.com/image.jpg",
    prompt_text="Camera slowly pushes in, leaves rustling",
    ratio="1280:720",
    duration=5,
    seed=12345           # Optional: reproducibility
).wait_for_task_output()

Aspect Ratios: Landscape 1280:720, 1584:672, 1104:832 | Portrait 720:1280, 832:1104 | Square 960:960

Aleph (Video-to-Video)

Transform existing videos with text/image guidance:

task = client.video_to_video.create(
    model="gen4_aleph",
    video_uri="https://example.com/source.mp4",
    prompt_text="Transform to anime style",
    references=[{"uri": "https://example.com/style_ref.jpg"}]  # Optional style reference
).wait_for_task_output()

Aspect Ratios: Adds 848:480 (landscape) and 480:848 (portrait) to Gen-4 options.

Act-Two (Character Performance)

Drive character motion from reference performance. Objects require type discriminators:

task = client.character_performance.create(
    model="act_two",
    character={"type": "image", "uri": "https://example.com/character.jpg"},  # or type: "video"
    reference={"type": "video", "uri": "https://example.com/performance.mp4"}
).wait_for_task_output()

Character types: image (character performs in static environment) or video (character performs with some of its own movement)

Veo (Google)

Google's Veo models for text-to-video and image-to-video. Veo models include audio generation - making them ideal when you need video with sound.

# Text-to-video with audio (no image required)
task = client.image_to_video.create(
    model="veo3.1",  # or "veo3", "veo3.1_fast"
    prompt_text="A cinematic shot of a rocket launching at sunset with roaring engines"
).wait_for_task_output()

# Image-to-video with audio
task = client.image_to_video.create(
    model="veo3.1",
    prompt_image="https://example.com/starting_frame.jpg",
    prompt_text="Smooth camera movement through the scene with ambient nature sounds"
).wait_for_task_output()
Note: Gen-4.5 and Gen-4 models produce silent video. Use Veo if you need audio, or add audio separately with ElevenLabs models (see Audio Generation section).

Image Generation

Gen-4 Image with References

Use reference images with @mention syntax in prompts:

# gen4_image - reference_images is optional
task = client.text_to_image.create(
    model="gen4_image",
    ratio="1920:1080",
    prompt_text="A beautiful mountain landscape at sunset"
).wait_for_task_output()

# With references
task = client.text_to_image.create(
    model="gen4_image",
    ratio="1920:1080",
    prompt_text="@EiffelTower painted in the style of @StarryNight",
    reference_images=[
        {"uri": "https://example.com/eiffel.jpg", "tag": "EiffelTower"},
        {"uri": "https://example.com/starry.jpg", "tag": "StarryNight"}
    ]
).wait_for_task_output()

Note: gen4_image_turbo requires reference_images (at least one). Use gen4_image for text-only generation.

Untagged references apply as general style:

reference_images=[
    {"uri": "https://example.com/subject.jpg", "tag": "subject"},
    {"uri": "https://example.com/style.jpg"}  # No tag = style reference
]

Audio Generation

ElevenLabs models for text-to-speech, sound effects, and voice processing.

Voice Presets: Maya, Arjun, Serene, Bernard, Billy, Mark, Clint, Mabel, Chad, Leslie, Eleanor, Elias, Elliot, Noah, Rachel, James, Katie, Tom, Wanda, Benjamin

Text-to-Speech

task = client.text_to_speech.create(
    model="eleven_multilingual_v2",
    prompt_text="Hello, welcome to RunwayML!",
    voice={"type": "runway-preset", "preset_id": "Maya"}
).wait_for_task_output()

Sound Effects

task = client.sound_effect.create(
    model="eleven_text_to_sound_v2",
    prompt_text="Thunder rumbling in the distance, rain on a window"
).wait_for_task_output()

Voice Isolation

task = client.voice_isolation.create(
    model="eleven_voice_isolation",
    audio_uri="https://example.com/noisy_audio.mp3"
).wait_for_task_output()

Voice Dubbing

task = client.voice_dubbing.create(
    model="eleven_voice_dubbing",
    audio_uri="https://example.com/speech.mp3",
    target_lang="es"  # Spanish
).wait_for_task_output()

Supported languages: en, hi, pt, zh, es, fr, de, ja, ar, ru, ko, id, it, nl, tr, pl, sv, fil, ms, ro, uk, el, cs, da, fi, bg, hr, sk, ta

Speech-to-Speech

Convert speech to a different voice. Requires type discriminators:

task = client.speech_to_speech.create(
    model="eleven_multilingual_sts_v2",
    media={"type": "audio", "uri": "https://example.com/original.mp3"},  # or type: "video"
    voice={"type": "runway-preset", "preset_id": "Maya"}
).wait_for_task_output()

Input Requirements

Size Limits

TypeURL LimitData URI LimitEphemeral Upload
Image16MB5MB (3.3MB pre-encoding)200MB
Video32MB16MB200MB
Audio32MB16MB200MB

Supported Formats

Images: JPEG, PNG, WebP (no GIF)

Videos: MP4 (H.264/H.265/AV1), MOV (ProRes), MKV, WebM

Audio: MP3, WAV, FLAC, M4A, AAC

Base64 Data URIs

import base64

with open("image.jpg", "rb") as f:
    data_uri = f"data:image/jpeg;base64,{base64.b64encode(f.read()).decode()}"

task = client.image_to_video.create(
    model="gen4_turbo",
    prompt_image=data_uri,
    prompt_text="Gentle movement"
).wait_for_task_output()

Task Management

All operations are async. Use wait_for_task_output() (polls automatically, 10 min timeout).

Statuses: PENDING → RUNNING → SUCCEEDED / FAILED / CANCELED

THROTTLED = rate-limited, treat as PENDING

Canceling/Deleting Tasks

# Cancel running task or delete completed task
client.tasks.delete(task.id)

See Task Management for manual polling and batch processing.


Prompting Tips

Gen-4 thrives on simplicity. Start simple, iterate.

  • Describe single scenes (5-10 sec clips)
  • Use clear physical descriptions, not conceptual language
  • Reference subjects generically: "the subject", "she"
  • Avoid negative phrasing - "no blur" produces unpredictable results

See Prompting Guide for camera movements and advanced techniques.


Error Handling

from runwayml import RunwayML, APIError, RateLimitError

client = RunwayML()

try:
    task = client.image_to_video.create(...).wait_for_task_output()
    if task.status == "FAILED":
        print(f"Generation failed: {task.failure}")
except RateLimitError:
    print("Rate limited - SDK retries automatically")
except APIError as e:
    print(f"API error {e.status_code}: {e.message}")
CodeMeaningAction
400Invalid inputFix request parameters
401Invalid API keyCheck RUNWAYML_API_SECRET
429Rate limitSDKs auto-retry with backoff
503Service unavailableSDKs auto-retry

Parameters Quick Reference

Video (gen4.5)

ParameterTypeOptions
modelstring"gen4.5", "gen4_turbo", "veo3", "veo3.1"
durationnumber2 to 10 (seconds)
ratiostringText-to-video: "1280:720" (16:9), "720:1280" (9:16)Image-to-video adds: "1584:672" (21:9), "1104:832" (4:3), "832:1104" (3:4)
prompt_textstringMotion/scene description (required)
prompt_imagestringURL or base64 (optional for text-to-video, required for image-to-video)
seednumberOptional, for reproducibility

Image (gen4_image)

ParameterTypeOptions
modelstring"gen4_image", "gen4_image_turbo"
ratiostring"1920:1080", "1280:720", etc.
prompt_textstringImage description
reference_imagesarray[{"uri": "...", "tag": "..."}]

References

Official Documentation

平台分布

Codex

35.12%
按下载量换算91

Claude

29.35%
按下载量换算76

Cursor

19.34%
按下载量换算50

Gemini CLI

7.81%
按下载量换算20

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

可疑

权限和风险

接触敏感数据

该 Skill 可能接触密钥、Token、环境变量或敏感配置,应进入高风险复核队列,默认不自动发布。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在提醒或未通过项,安装前请自行复核。目前只有一个公开来源,建议同时核对源仓库。

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