Der Prompt
---
name: trello-integration-skill
description: This skill allows you to interact with Trello account to list boards, view lists, and create cards automatically.
---
# Trello Integration Skill
The Trello Integration Skill provides a seamless connection between the AI agent and the user's Trello account. It empowers the agent to autonomously fetch existing boards and lists, and create new task cards on specific boards based on user prompts.
## Features
- **Fetch Boards**: Retrieve a list of all Trello boards the user has access to, including their Name, ID, and URL.
- **Fetch Lists**: Retrieve all lists (columns like "To Do", "In Progress", "Done") belonging to a specific board.
- **Create Cards**: Automatically create new cards with titles and descriptions in designated lists.
---
## Setup & Prerequisites
To use this skill locally, you need to provide your Trello Developer API credentials.
1. Generate your credentials at the [Trello Developer Portal (Power-Ups Admin)](https://trello.com/app-key).
2. Create an API Key.
3. Generate a Secret Token (Read/Write access).
4. Add these credentials to the project's root `.env` file:
```env
# Trello Integration
TRELLO_API_KEY=your_api_key_here
TRELLO_TOKEN=your_token_here
```
---
## Usage & Architecture
The skill utilizes standalone Node.js scripts located in the `.agent/skills/trello_skill/scripts/` directory.
### 1. List All Boards
Fetches all boards for the authenticated user to determine the correct target `boardId`.
**Execution:**
```bash
node .agent/skills/trello_skill/scripts/list_boards.js
```
### 2. List Columns (Lists) in a Board
Fetches the lists inside a specific board to find the exact `listId` (e.g., retrieving the ID for the "To Do" column).
**Execution:**
```bash
node .agent/skills/trello_skill/scripts/list_lists.js <boardId>
```
### 3. Create a New Card
Pushes a new card to the specified list.
**Execution:**
```bash
node .agent/skills/trello_skill/scripts/create_card.js <listId> "<Card Title>" "<Optional Description>"
```
*(Always wrap the card title and description in double quotes to prevent bash argument splitting).*
---
## AI Agent Workflow
When the user requests to manage or add a task to Trello, follow these steps autonomously:
1. **Identify the Target**: If the target `listId` is unknown, first run `list_boards.js` to identify the correct `boardId`, then execute `list_lists.js <boardId>` to retrieve the corresponding `listId` (e.g., for "To Do").
2. **Execute Command**: Run the `create_card.js <listId> "Task Title" "Task Description"` script.
3. **Report Back**: Confirm the successful creation with the user and provide the direct URL to the newly created Trello card.
FILE:create_card.js
const path = require('path');
require('dotenv').config({ path: path.join(__dirname, '../../../../.env') });
const API_KEY = process.env.TRELLO_API_KEY;
const TOKEN = process.env.TRELLO_TOKEN;
if (!API_KEY || !TOKEN) {
console.error("Error: TRELLO_API_KEY or TRELLO_TOKEN is missing from the .env file.");
process.exit(1);
}
const listId = process.argv[2];
const cardName = process.argv[3];
const cardDesc = process.argv[4] || "";
if (!listId || !cardName) {
console.error(`Usage: node create_card.js <listId> "${card_name}" ["${card_description}"]`);
process.exit(1);
}
async function createCard() {
const url = `https://api.trello.com/1/cards?idList=${listId}&key=${API_KEY}&token=${TOKEN}`;
try {
const response = await fetch(url, {
method: 'POST',
headers: {
'Accept': 'application/json',
'Content-Type': 'application/json'
},
body: JSON.stringify({
name: cardName,
desc: cardDesc,
pos: 'top'
})
});
if (!response.ok) {
const errText = await response.text();
throw new Error(`HTTP error! status: ${response.status}, message: ${errText}`);
}
const card = await response.json();
console.log(`Successfully created card!`);
console.log(`Name: ${card.name}`);
console.log(`ID: ${card.id}`);
console.log(`URL: ${card.url}`);
} catch (error) {
console.error("Failed to create card:", error.message);
}
}
createCard();
FILE:list_board.js
const path = require('path');
require('dotenv').config({ path: path.join(__dirname, '../../../../.env') });
const API_KEY = process.env.TRELLO_API_KEY;
const TOKEN = process.env.TRELLO_TOKEN;
if (!API_KEY || !TOKEN) {
console.error("Error: TRELLO_API_KEY or TRELLO_TOKEN is missing from the .env file.");
process.exit(1);
}
async function listBoards() {
const url = `https://api.trello.com/1/members/me/boards?key=${API_KEY}&token=${TOKEN}&fields=name,url`;
try {
const response = await fetch(url);
if (!response.ok) throw new Error(`HTTP error! status: ${response.status}`);
const boards = await response.json();
console.log("--- Your Trello Boards ---");
boards.forEach(b => console.log(`Name: ${b.name}\nID: ${b.id}\nURL: ${b.url}\n`));
} catch (error) {
console.error("Failed to fetch boards:", error.message);
}
}
listBoards();
FILE:list_lists.js
const path = require('path');
require('dotenv').config({ path: path.join(__dirname, '../../../../.env') });
const API_KEY = process.env.TRELLO_API_KEY;
const TOKEN = process.env.TRELLO_TOKEN;
if (!API_KEY || !TOKEN) {
console.error("Error: TRELLO_API_KEY or TRELLO_TOKEN is missing from the .env file.");
process.exit(1);
}
const boardId = process.argv[2];
if (!boardId) {
console.error("Usage: node list_lists.js <boardId>");
process.exit(1);
}
async function listLists() {
const url = `https://api.trello.com/1/boards/${boardId}/lists?key=${API_KEY}&token=${TOKEN}&fields=name`;
try {
const response = await fetch(url);
if (!response.ok) throw new Error(`HTTP error! status: ${response.status}`);
const lists = await response.json();
console.log(`--- Lists in Board ${boardId} ---`);
lists.forEach(l => console.log(`Name: "${l.name}"\nID: ${l.id}\n`));
} catch (error) {
console.error("Failed to fetch lists:", error.message);
}
}
listLists();
So nutzt du diesen Prompt
Kopiere den Prompt oben oder klicke einen "Öffnen in"-Button um ihn direkt in deiner bevorzugten KI zu starten. Du kannst den Text dann an deinen Anwendungsfall anpassen — z.B. Platzhalter wie [dein Thema] durch echten Kontext ersetzen.
Welches KI-Modell funktioniert am besten
Claude glänzt bei Agent-Workflows dank langem Context-Window (bis 1M Tokens) und nuancierter Instruction-Following. ChatGPT hat native Actions (Tool-Calling) eingebaut. Gemini integriert am besten mit Google Workspace. Für autonome Workflows ist Claude Sonnet 4.6 aktueller Sweet-Spot für Qualität und Kosten.
Diesen Prompt anpassen
Passe Rolle und Constraints des Agents an deine Umgebung an. Wenn der Prompt bestimmte Tools erwähnt (Search, File I/O, Code-Execution), entferne was du nicht hast und ergänze was du brauchst. Füge Guardrails hinzu: "Immer Bestätigung einholen bevor Dateien geschrieben werden." Definiere Erfolgskriterien explizit.
Typische Anwendungsfälle
- Autonome Forschungs-Assistenten für einen Bereich bauen
- Chatbots mit definierten Persönlichkeiten + Wissensgrenzen erstellen
- Multi-Step-Workflows orchestrieren (Recherche → Entwurf → Review → Publish)
- System-Prompts für Custom GPTs oder Claude Projects definieren
- Agent-Loops bauen die Tools rufen und sich selbst korrigieren
Variationen
Passe den Tonfall an (lockerer, technischer), ändere das Ausgabeformat (Aufzählungen vs. Absätze) oder füge Einschränkungen hinzu (Wortlimits, Zielgruppe).
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