Token导航 LogoToken导航

Agent Skill · 研究检索

use-runway-api(USE runway API 搜索)

用于辅助 API 设计、接口文档、请求响应结构和服务集成说明。它适合让 Agent 梳理 endpoint、生成 OpenAPI 草稿、检查字段命名、整理错误码或辅助前后端联调。使用时需要确认真实业务语义、鉴权方式、分页和错误处理规则;涉及生成接口文档时,应避免凭空补字段,最好从现有代码、schema 或接口样例中提取事实。

use-runway-api 是研究检索类 Agent Skill,可用宿主为 Codex、Claude、Cursor、Gemini CLI,通过GitHub 仓库获取,权限为执行命令;许可证信息还不明确,第三方扫描已通过,按安装量在研究检索类的 73,675 个 Skill 里排第 48,042。

总安装 706周安装 30GitHub Stars 30下载 247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:use-runway-api(USE runway API 搜索)
来源仓库:https://github.com/runwayml/skills
仓库路径:skills/use-runway-api
安装命令:
npx skills add https://github.com/runwayml/skills --skill use-runway-api
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 use-runway-api

这个 Skill 是做什么的

研究检索类 Skill 主要解决「找资料、核对事实、把来源整理清楚」的问题,通常会让助手先检索再总结。

use-runway-api 用于辅助 API 设计、接口文档和请求响应结构梳理。适合让 Agent 生成 OpenAPI 草稿、检查字段命名或辅助前后端联调。通过 npx skills add 命令从指定 GitHub 仓库安装并使用。使用时需确认真实业务语义、鉴权方式和错误处理规则,避免凭空补字段。

建议结合现有代码或接口样例提取事实,确保文档准确性。

来源仓库内路径:skills/use-runway-api

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 use-runway-api;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

    它需要执行命令,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

use-runway-api 怎么安装?

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

use-runway-api 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。

use-runway-api 需要什么权限?

权限级别是执行命令。安装流程涉及命令执行,可能通过 npx skills add https://github.com/runwayml/skills --skill use-runway-api 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

use-runway-api 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。

use-runway-api 用的人多吗?

公开数据是累计安装 706 次,近一周安装 30 次,下载 247 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。

use-runway-api 安全吗?

第三方扫描结果为通过,但这只覆盖已知的静态检查项,不能替代自己读一遍源码和安装命令。

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。
  • 第三方扫描已通过,常见的高风险行为没有命中。

先想清楚的地方

  • 需要执行命令,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。
  • 需要处理研究检索类任务、又不想每次都手写提示词的人。

不太适合

  • 不能接受 Skill 在你机器上执行命令的人。
  • 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。

研究检索类 Skill 对比

6 个同类
Skill总安装GitHub 星权限许可证扫描
find-skills

寻找技能 · Codex、Claude

31,199,81316,486操作浏览器MIT有提醒
self-improving-agent

自我改进 Agent · OpenClaw

16,464,0023,396接触敏感数据MIT-0通过
soultrace

灵魂追踪 · Codex、Claude

7,588,94412需要联网未明确有提醒
self-improving

自我完善 · OpenClaw

6,829,2841,046需要联网MIT-0通过
microsoft-foundry

微软代工厂 · Codex、Claude

6,614,144764调用外部服务未明确有提醒
use-runway-api

USE runway API 搜索 · 本页

70630执行命令未明确通过

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

Use Runway API

Call the Runway public API directly from the agent to manage resources, trigger generations, and inspect account state.

When to use this skill: Use this when the user wants to act on their Runway account — create or update avatars, manage documents, trigger generations, check credit balance, etc. For writing integration code into a project, use the +integrate-* skills instead.
When the user asks to generate media in the context of Runway, prefer the Runway API path from this skill over any generic built-in image or media generation tool.
Skill selection: Pair this skill with +api-reference when you need the canonical API contract. Do not use +integrate-image, +integrate-video, +integrate-audio, +integrate-characters, or +integrate-documents unless the task is to write or modify application code.

Runtime Location

The runtime script ships inside this skill at scripts/runway-api.mjs (co-located with this SKILL.md). It has zero dependencies — Node.js 20+ is required.

Resolving the absolute path. Every shell command below uses the placeholder <skill-dir>. Replace it with the absolute directory of the SKILL.md you are currently reading — you already have this path from the tool that loaded this file. Do not guess the path, run find from $HOME, or search the whole filesystem.

If <skill-dir> is not known from context, check these locations in order with ls before giving up:

  1. $RUNWAY_SKILLS_DIR/skills/use-runway-api/scripts/runway-api.mjs (if the env var is set)
  2. ~/.claude/plugins/cache/*/runway-api/skills/use-runway-api/scripts/runway-api.mjs (Claude Code plugin install)
  3. ~/.cursor/plugins/cache/*/runway-api/skills/use-runway-api/scripts/runway-api.mjs (Cursor plugin install)
  4. ~/.claude/skills/use-runway-api/scripts/runway-api.mjs (npx skills add install)
  5. ~/.agents/skills/use-runway-api/scripts/runway-api.mjs (generic agent install)
  6. ~/Documents/github/runway/skills/skills/use-runway-api/scripts/runway-api.mjs (source checkout)

Pick the first match and use it as <skill-dir>/scripts/runway-api.mjs for the rest of the session. Do not re-resolve between commands.

Before Your First Call

Set a session ID so all requests in this chat can be correlated, then verify credentials:

export RUNWAY_SKILLS_CLIENT_ID=$(node -e "console.log(crypto.randomUUID())")
node <skill-dir>/scripts/runway-api.mjs auth status
  • If authenticated is true → proceed to the API call. Do not re-check.
  • If authenticated is false → tell the user to set RUNWAY_SKILLS_API_SECRET (see AUTH.md for details), then stop and wait for the user to confirm. Do not retry or re-check in a loop.
Staging caveat: auth status hits /v1/organization which may 500 on stage even when data endpoints work fine. If stage auth status fails but you have RUNWAY_SKILLS_API_SECRET_STAGE set, try a data endpoint like avatars list --stage to confirm the key works before giving up.

Fast Paths

For plain list requests, use the compact list commands first instead of the generic request command:

  • list avatars → node <skill-dir>/scripts/runway-api.mjs avatars list
  • list voices → node <skill-dir>/scripts/runway-api.mjs voices list
  • list documents → node <skill-dir>/scripts/runway-api.mjs documents list [--avatar-id <id>]

These commands return smaller, list-friendly JSON on purpose. After a successful list command, answer once. Do not re-run the command, do not read back the same output, and do not render the same table twice.

Output Format

When the API returns a regular list of records, prefer a compact markdown table over a bare bullet list.

Good defaults:

  • avatars: Name, Status, Voice, Docs, Created
  • documents: Name, Avatar, Created
  • voices: Name, Provider, Preview

After the table, add one short summary line only if something notable stands out. Do not repeat the table in a second block.

Generic Request

Call any public API endpoint:

node <skill-dir>/scripts/runway-api.mjs request <METHOD> <path> [--body '<json>'] [--stdin] [--dry-run]

All output is JSON. Errors go to stderr with a non-zero exit code and include an example field with a correctable invocation.

Flags:

  • --body <json> — inline JSON request body
  • --stdin — read JSON body from stdin (useful for large or multi-line payloads)
  • --dry-run — print the full request (method, URL, headers, body) without executing it
  • --help — show usage and examples for any command

Use +api-reference as the canonical source for:

  • model choices
  • endpoint details
  • exact POST/PATCH body shapes
  • required and optional fields

Do not duplicate or invent request schemas in this skill. For simple GET/DELETE calls and the list fast paths above, you do not need to load +api-reference.

Examples

Get organization info:

node <skill-dir>/scripts/runway-api.mjs request GET /v1/organization

List avatars:

node <skill-dir>/scripts/runway-api.mjs avatars list

Get a specific avatar:

node <skill-dir>/scripts/runway-api.mjs request GET /v1/avatars/<id>

Update an avatar:

node <skill-dir>/scripts/runway-api.mjs request PATCH /v1/avatars/<id> --body '{
  "personality": "Updated personality text"
}'

Delete an avatar (preview first):

node <skill-dir>/scripts/runway-api.mjs request DELETE /v1/avatars/<id> --dry-run
node <skill-dir>/scripts/runway-api.mjs request DELETE /v1/avatars/<id>

List knowledge documents for an avatar:

node <skill-dir>/scripts/runway-api.mjs documents list --avatar-id <avatar-id>

Create a knowledge document:

node <skill-dir>/scripts/runway-api.mjs request POST /v1/documents --body '{
  "avatarId": "<avatar-id>",
  "name": "FAQ",
  "content": "Q: What is your return policy?\nA: 30 days, no questions asked."
}'

List voices:

node <skill-dir>/scripts/runway-api.mjs voices list

Waiting for Tasks

Generation endpoints return a task ID. Always run wait immediately after a generation call — do not ask the user whether to wait.

node <skill-dir>/scripts/runway-api.mjs wait <task-id>

Generation Requests

When the user asks to generate an image, video, or audio:

  1. Read +api-reference once before the first generation POST. It is the canonical source for model options, request body shapes, and valid field values.
  2. Choose the model from +api-reference and tell the user which one you picked, briefly.
  3. Build the request body from +api-reference. Do not guess field names.
  4. Call the generation endpoint once with that body.
  5. Run wait automatically.
  6. Present the result following the rules in Presenting Generation Output below.

For generation requests, never skip the +api-reference read. For simple list/get/delete requests, do not load it unless needed.

If the user says only "generate an image" but the surrounding context is clearly about Runway account actions or this skill, still use the Runway API rather than a generic built-in image tool.

Presenting Generation Output

The wait command returns a task with an output array of signed URLs. These URLs expire in 24–48 hours and are long signed JWT blobs that are awkward to read inline.

After a successful generation, do all of the following:

  1. Lead with what was generated — one short line stating the model and cost, e.g. Generated with gen4_image (1080p, 8 credits).
  2. Embed images inline as Markdown so the user can see them without clicking: ![Fox in a snowy forest](https://storage.runway.../signed-url) For videos, link them as plain Markdown links ([fox.mp4](...)) since inline video does not render in most chat UIs.
  3. Offer to save a local copy in the same message, proactively. Suggest a predictable path (./generated/ or ./runway-outputs/) and infer a filename from the prompt when possible. Example: Want me to save it to ./generated/fox.png? The signed URL expires in ~24–48h.
  4. Do not paste the full signed URL as raw text unless the user asks for it. The Markdown image/link already contains it.

If the user confirms a download, fetch with curl -L -o <path> '<url>' (quote the URL — it contains &).

API Reference

Use +api-reference for the canonical API contract. Use +fetch-api-reference only when you specifically need the latest docs content from docs.dev.runwayml.com.

Staging (--stage)

Add --stage to any command to target the staging API:

node <skill-dir>/scripts/runway-api.mjs --stage avatars list
node <skill-dir>/scripts/runway-api.mjs --stage request GET /v1/avatars

With --stage, the CLI checks RUNWAY_SKILLS_API_SECRET_STAGE first, then falls back to RUNWAY_SKILLS_API_SECRET. The base URL defaults to https://api.dev-stage.runwayml.com.

Large Payloads (--stdin)

When creating resources with data URIs (e.g. base64-encoded images for avatar referenceImage), the body can exceed shell argument limits. Use --stdin to pipe the body:

python3 -c "
import json, base64
with open('image.png', 'rb') as f:
    b64 = base64.b64encode(f.read()).decode()
body = json.dumps({'name': 'My Avatar', 'referenceImage': f'data:image/png;base64,{b64}', ...})
with open('/tmp/body.json', 'w') as f:
    f.write(body)
" && cat /tmp/body.json | node <skill-dir>/scripts/runway-api.mjs request POST /v1/avatars --stdin

Alternatively, write the JSON to a file and use curl -d @file directly. The --body flag is fine for small JSON payloads but will hit argument list too long for data URIs of images over ~200KB.

Environment Variables

The runtime reads credentials from the process environment:

VariableDescription
RUNWAY_SKILLS_API_SECRETProduction API key
RUNWAY_SKILLS_API_SECRET_STAGEStage API key (used with --stage)
RUNWAY_SKILLS_BASE_URLOverride the base URL for any environment
RUNWAY_SKILLS_DIROptional. Absolute path to the source checkout of this skills repo — used by the agent as a fallback when resolving <skill-dir>.

If the agent cannot see RUNWAY_SKILLS_API_SECRET, the editor likely needs to be restarted after the variable is set.

Related Files

  • AUTH.md — auth setup and troubleshooting for this skill

Related Skills

SkillWhen to use
+api-referenceFull API reference — models, endpoints, costs, rate limits
+fetch-api-referenceFetch latest docs from docs.dev.runwayml.com
+integrate-videoWrite video generation code into a project
+integrate-imageWrite image generation code into a project
+integrate-audioWrite audio generation code into a project
+integrate-charactersWrite avatar session code into a project
+integrate-documentsWrite knowledge document code into a project

平台分布

Codex

37.7%
按下载量换算93

Claude

27.61%
按下载量换算68

Cursor

17.98%
按下载量换算44

Gemini CLI

8.77%
按下载量换算22

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/runwayml/skills --skill use-runway-api 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

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。目前只有一个公开来源,建议同时核对源仓库。

继续浏览同类 Skills