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integrate-documents整合文件

Agent Skill

integrate-documents 用于查找、检索和筛选相关信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。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。

总安装

1,117

周安装

47

GitHub Stars

30

下载量

391
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

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:integrate-documents(整合文件)
来源仓库:https://github.com/runwayml/skills
仓库路径:skills/integrate-documents
安装命令:
npx skills add https://github.com/runwayml/skills --skill integrate-documents
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 integrate-documents

简介

用于查找、检索和筛选相关信息。适用宿主包括 Codex、Claude、Cursor、Gemini CLI,接入前应确认版本、权限和运行环境要求。

  • 适合根据关键词或任务场景快速定位候选结果。
  • 通过 npx skills add 命令从指定仓库安装并使用。
  • 建议确认权限范围、维护状态及是否触发联网或文件读写操作。
  • integrate-documents 属于研究检索类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Integrate Documents (Knowledge Base)

PREREQUISITE: Run +check-compatibility first. Run +fetch-api-reference to load the latest API reference before integrating. +setup-api-key — API credentials must be configured USED BY: +integrate-characters — Documents are linked to Avatars to give them domain-specific knowledge

Give your Characters access to domain-specific knowledge. Upload content that your Avatar can reference during conversations for accurate, contextual responses.

When to Use Documents

Use CaseExample Content
Customer supportFAQs, product info, company policies, return procedures
Quizzes & gamesQuestion banks, correct answers, scoring rules
EducationCourse material, reference content, learning objectives
Brand experiencesBrand guidelines, messaging, product catalogs

Constraints

  • Each Avatar supports up to 50,000 tokens of knowledge
  • Supported formats: plain text and Markdown
  • More formats planned for future releases

Flow

The flow is: Create a DocumentLink it to an Avatar

Step 1: Create a Document

Node.js

import RunwayML from '@runwayml/sdk';

const client = new RunwayML();

const document = await client.documents.create({
  name: 'Product FAQ',
  content: `# Product FAQ

## What is your return policy?
We offer a 30-day return policy for all unused items in original packaging.

## How do I track my order?
Log in to your account and visit the Orders page. You'll find tracking information for all shipped orders.

## Do you offer international shipping?
Yes, we ship to over 50 countries. Shipping costs and delivery times vary by destination.`,
});

console.log('Document created:', document.id);

Python

from runwayml import RunwayML

client = RunwayML()

document = client.documents.create(
    name='Product FAQ',
    content="""# Product FAQ

## What is your return policy?
We offer a 30-day return policy for all unused items in original packaging.

## How do I track my order?
Log in to your account and visit the Orders page.

## Do you offer international shipping?
Yes, we ship to over 50 countries.""",
)

print('Document created:', document.id)

Step 2: Link the Document to an Avatar

Update your Avatar to attach the document. This replaces any existing document attachments — pass all document IDs you want linked.

Node.js

await client.avatars.update(avatarId, {
  documentIds: [document.id],
});

Python

client.avatars.update(
    avatar_id,
    document_ids=[document.id],
)

Multiple Documents

You can link multiple documents to a single avatar (total must stay under 50,000 tokens):

const faq = await client.documents.create({
  name: 'FAQ',
  content: '...',
});

const policies = await client.documents.create({
  name: 'Company Policies',
  content: '...',
});

await client.avatars.update(avatarId, {
  documentIds: [faq.id, policies.id],
});

Step 3: Start a Session

Once documents are linked, the Avatar automatically has access to the knowledge during conversations. Start a session as usual — no additional configuration needed:

const session = await client.realtimeSessions.create({
  model: 'gwm1_avatars',
  avatar: {
    type: 'custom',
    avatarId: avatarId,
  },
});
session = client.realtime_sessions.create(
    model='gwm1_avatars',
    avatar={
        'type': 'custom',
        'avatar_id': avatar_id,
    },
)

See +integrate-characters for the full session creation, polling, and WebRTC flow.

Integration Patterns

Load Documents from Files

Read content from local files and create documents:

import fs from 'fs';
import RunwayML from '@runwayml/sdk';

const client = new RunwayML();

// Read a local markdown file
const content = fs.readFileSync('./knowledge/product-faq.md', 'utf-8');

const document = await client.documents.create({
  name: 'Product FAQ',
  content,
});
from pathlib import Path
from runwayml import RunwayML

client = RunwayML()

content = Path('./knowledge/product-faq.md').read_text()

document = client.documents.create(
    name='Product FAQ',
    content=content,
)

Dynamic Knowledge Updates

Update documents programmatically — useful for syncing with a CMS or database:

// Example: API endpoint to update character knowledge
app.post('/api/avatar/update-knowledge', async (req, res) => {
  const { avatarId, documents } = req.body;

  // Create new documents
  const docIds = [];
  for (const doc of documents) {
    const created = await client.documents.create({
      name: doc.name,
      content: doc.content,
    });
    docIds.push(created.id);
  }

  // Link all documents to the avatar (replaces existing)
  await client.avatars.update(avatarId, {
    documentIds: docIds,
  });

  res.json({ success: true, documentCount: docIds.length });
});

Tips

  • Use Markdown for structured content — headings help the Avatar navigate the knowledge.
  • Be concise — stay well under the 50,000 token limit for best retrieval quality.
  • Organize by topic — multiple focused documents work better than one giant document.
  • Update regularly — keep knowledge current by re-creating documents when content changes.
  • Documents can also be managed via the Developer Portal UI.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

38.03%
按下载量换算149

Claude

30.76%
按下载量换算120

Cursor

17.79%
按下载量换算70

Gemini CLI

9.96%
按下载量换算39

安全审计

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通过

Socket

通过

Snyk

通过

权限和风险

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。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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