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self-integration自我整合

Agent Skill

self-integration 用于查找、检索和筛选相关信息,适合在 OpenClaw 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

24,088

周安装

984

GitHub Stars

2

下载量

7,715
OpenClaw

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

MIT-0

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:self-integration(自我整合)
来源仓库:https://github.com/bratchenko/self-integration
安装命令:
openclaw skills install self-integration
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 OpenClaw 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。

ClawHubOpenClaw
openclaw skills install self-integration

简介

连接到任何外部应用程序并对其执行操作。当用户想要与 Slack、Linear、HubSpot、Salesforce、Jira、GitHub、Google Sheets 或任何其他应用程序等外部服务交互时使用 - 发送消息、创建任务、同步数据、管理联系人或执行任何 API 操作。

SKILL.md

name
self-integration
description
Connect to any external app and perform actions on it. Use when the user wants to interact with external services like Slack, Linear, HubSpot, Salesforce, Jira, GitHub, Google Sheets, or any other app — send messages, create tasks, sync data, manage contacts, or perform any API operation.
license
MIT
metadata
author
Membrane Inc
version
1.0.0
homepage
https://getmembrane.com
openclaw
requires
env
primaryEnv
MEMBRANE_TOKEN
homepage
https://getmembrane.com

Self-Integration

Connect to any external app and perform actions on it. Uses the Membrane API.

Making API Requests

All requests go to ${MEMBRANE_API_URL:-https://api.getmembrane.com} with a Bearer token:

Authorization: Bearer $MEMBRANE_TOKEN
Content-Type: application/json

Get the API token from the Membrane dashboard.

Workflow

Step 1: Get a Connection

A connection is an authenticated link to an external app (e.g. a user's Slack workspace, a HubSpot account). You need one before you can run actions.

1a. Check for existing connections

GET /connections

Look for a connection matching the target app. Key fields: id, name, connectorId, disconnected.

If a matching connection exists and disconnected is false, skip to Step 2.

1b. Find a connector

A connector is a pre-built adapter for an external app. Search by app name:

GET /search?q=slack

Look for results with elementType: "connector". Use element.id as connectorId in step 1d.

If nothing is found, go to step 1c to build a connector.

1c. Build a connector (if none exists)

Create a Membrane Agent session to build a connector:

POST /agent/sessions with body {"prompt": "Build a connector for Slack (https://slack.com)"}

Adjust the prompt to describe the actual app you need. Poll GET /agent/sessions/{sessionId}?wait=true&timeout=30 until state is "idle" or status is "completed".

You can send follow-up instructions via POST /agent/sessions/{sessionId}/message or abort via POST /agent/sessions/{sessionId}/interrupt.

After the connector is built, search for it again (step 1b).

1d. Request a connection

Create a connection request so the user can authenticate with the external app:

POST /connection-requests with body {"connectorId": "cnt_abc123"}

The response includes a url. Tell the user to open the url to complete authentication (OAuth, API key, etc.).

1e. Check connection result

Poll until the user completes authentication:

GET /connection-requests/{requestId}

  • status: "pending" — user hasn't completed yet, poll again.
  • status: "success" — done. Use resultConnectionId as the connection ID going forward.
  • status: "error" — failed. Check resultError for details.

Step 2: Get an Action

An action is an operation you can perform on a connected app (e.g. "Create task", "Send message", "List contacts").

2a. Search for actions

Search using a natural language description of what you want to do:

GET /actions?connectionId=con_abc123&intent=send+a+message&limit=10

Each result includes id, name, description, inputSchema (what parameters the action accepts), and outputSchema (what it returns).

If no suitable action exists, go to step 2b.

2b. Build an action (if none exists)

Use Membrane Agent. ALWAYS include the connection ID in the prompt:

POST /agent/sessions with body {"prompt": "Create a tool to send a message in a channel for connection con_abc123"}

Adjust the prompt to describe the actual action you need. Poll for completion the same way as step 1c. After the action is built, search for it again (step 2a).

Step 3: Run an Action

Execute the action using the action ID from step 2 and the connection ID from step 1:

POST /actions/{actionId}/run?connectionId=con_abc123 with body {"input": {"channel": "#general", "text": "Hello!"}}

Provide input matching the action's inputSchema.

The result is in the output field of the response.

API Reference

Base URL: ${MEMBRANE_API_URL:-https://api.getmembrane.com} Auth header: Authorization: Bearer $MEMBRANE_TOKEN

GET /connections

List all connections.

Response:

{
  "items": [
    {
      "id": "string",
      "name": "string",
      "connectorId": "string",
      "integrationId": "string (optional)",
      "disconnected": "boolean",
      "state": "NOT_CONFIGURED | SETUP_IN_PROGRESS | SETUP_FAILED | READY",
      "error": "object (optional)",
      "createdAt": "datetime",
      "updatedAt": "datetime"
    }
  ]
}

GET /search

Search workspace elements by keyword.

Query parameters:

ParamTypeDescription
qstring (required)Search query (1-200 chars)
elementTypestring (optional)Filter by type: Connector, Integration, Action, etc.
limitnumber (optional)Max results (1-100)

Response:

{
  "items": [
    {
      "elementType": "Connector",
      "element": {
        "id": "string",
        "name": "string",
        "logoUri": "string (optional)"
      }
    }
  ]
}

POST /connection-requests

Create a connection request for user authentication.

Request body (at least one identifier required):

FieldTypeDescription
connectorIdstringConnector ID
integrationIdstringIntegration ID (alternative)
integrationKeystringIntegration key (alternative)
connectionIdstringExisting connection ID (for reconnecting)
namestringCustom connection name
connectorVersionstringConnector version
connectorParametersobjectConnector-specific parameters

Response:

{
  "requestId": "string",
  "url": "string",
  "status": "pending | success | cancelled | error",
  "connectorId": "string (optional)",
  "integrationId": "string (optional)",
  "resultConnectionId": "string (optional, set on success)",
  "resultError": "object (optional, set on error)",
  "createdAt": "datetime"
}

GET /connection-requests/:requestId

Check connection request status. Same response schema as POST.

GET /actions

List or search actions.

Query parameters:

ParamTypeDescription
connectionIdstringFilter by connection
integrationIdstringFilter by integration
intentstringNatural language search (max 200 chars)
limitnumberMax results (default 10)

Response:

{
  "items": [
    {
      "id": "string",
      "name": "string",
      "key": "string",
      "description": "string (optional)",
      "type": "string",
      "inputSchema": "JSON Schema (optional)",
      "outputSchema": "JSON Schema (optional)",
      "integrationId": "string (optional)",
      "connectionId": "string (optional)"
    }
  ]
}

POST /actions/:actionId/run

Run an action.

Query parameters:

ParamTypeDescription
connectionIdstringConnection to run the action on

Request body:

FieldTypeDescription
inputanyParameters matching the action's inputSchema

Response:

{
  "output": "any"
}

POST /agent/sessions

Create an agent session to build connectors or actions.

Request body:

FieldTypeDescription
promptstring (required)Task description

Response:

{
  "id": "string",
  "status": "queued | starting | running | completed | failed | cancelled",
  "state": "busy | idle",
  "prompt": "string",
  "createdAt": "datetime",
  "updatedAt": "datetime"
}

GET /agent/sessions/:id

Get agent session status.

Query parameters:

ParamTypeDescription
waitbooleanIf true, long-poll until session is idle or timeout
timeoutnumberMax wait in seconds (1-60, default 30)

Response: same schema as POST /agent/sessions.

POST /agent/sessions/:id/message

Send a follow-up message to an active agent session.

Request body:

FieldTypeDescription
inputstring (required)Message to send

Response: same schema as POST /agent/sessions.

POST /agent/sessions/:id/interrupt

Abort an agent session.

Response:

{
  "interrupted": "boolean"
}

External Endpoints

All requests go to the Membrane API. No other external services are contacted directly by this skill.

EndpointData Sent
${MEMBRANE_API_URL:-https://api.getmembrane.com}/*API token, connection parameters, action inputs, agent prompts

Security & Privacy

  • All data is sent to the Membrane API over HTTPS.
  • MEMBRANE_TOKEN is a high-privilege credential that can create connections and run actions across external apps. Treat it as a secret.
  • Connection authentication (OAuth, API keys) is handled by Membrane — credentials for external apps are stored by the Membrane service, not locally.
  • Action inputs and outputs pass through the Membrane API to the connected external app.

By using this skill, data is sent to Membrane. Only install if you trust Membrane with access to your connected apps.

适合场景

01

OpenClaw 用户查找和安装 Skill 时

02

用户想查找某类 Agent Skill 时

03

需要根据任务场景推荐可安装能力包时

04

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

补充不同宿主或平台的使用分布数据

能力 5

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

OpenClaw

87.24%
按下载量换算6,731

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

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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