tfl-generator

Category: Development & Coding | Uploader: imgwho | Downloads: 0 | Version: v1.0（Latest）

Generate Tableau Prep flows (.tfl/.tflx) using cwprep MCP Server or Python SDK.

Changelog: Source: GitHub https://github.com/imgwho/cwprep

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Current level: .agents/skills/tfl-generator/

📄 SKILl.md 2.0 KB
📄 SKILL_Zh-cn.md 1.4 KB

SKILL.md

---
name: tfl-generator
description: Generate Tableau Prep flows (.tfl/.tflx) using cwprep MCP Server or Python SDK.
---

# TFL Generator

## MCP Server (Recommended)

When the cwprep MCP Server is connected, use MCP Tools directly:

| Tool | Purpose |
|------|---------|
| `generate_tfl` | Generate .tfl/.tflx file from a flow definition |
| `validate_flow_definition` | Validate definition before generating |
| `list_supported_operations` | List all supported node types and parameters |

Before generating, read MCP Resources for context:

| Resource | Content |
|----------|---------|
| `cwprep://docs/api-reference` | SDK API reference (database + file connections, all transforms) |
| `cwprep://docs/calculation-syntax` | Tableau Prep formula syntax (differs from SQL!) |
| `cwprep://docs/best-practices` | Common pitfalls and flow design rules |

### Supported Connection Types
- **Database**: MySQL, PostgreSQL, SQL Server (SSPI + username/password)
- **File**: Excel (.xlsx/.xls), CSV — auto-detected from extension

### Output Formats
- `.tfl` — Standard flow (references external data)
- `.tflx` — Packaged flow (embeds data files inside)

## Fallback: Python SDK

If MCP is unavailable, use the SDK directly:

```python
from cwprep import TFLBuilder, TFLPackager

builder = TFLBuilder(flow_name="My Flow")

# Database connection
conn_id = builder.add_connection(host="localhost", username="root", dbname="mydb")
orders = builder.add_input_table("orders", "orders", conn_id)

# File connection (Excel/CSV)
file_conn = builder.add_file_connection("returns.xlsx")
returns = builder.add_input_excel("Returns", "Sheet1", file_conn)

# Multi-column join
joined = builder.add_join("Join", orders, returns,
    ["product_id", "order_id"], ["product_id", "order_id"])
builder.add_output_server("Output", joined, "My_Datasource")

flow, display, meta = builder.build()
TFLPackager.save_to_folder("./output/my_flow", flow, display, meta)
TFLPackager.pack_zip("./output/my_flow", "./output/my_flow.tfl")
```

See the project README for full SDK documentation.

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tfl-generator

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