workflow-migrate

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Migrate N8N/Zapier/Make workflows to production-grade Python or Node.js scripts. Given a workflow description or paste, rewrites automation logic with retry,...

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About This Skill

# Workflow Migrate — Automation Migration Tool
## Why This Exists
N8N/Zapier/Make workflows break silently, can't be version-controlled, and cost $50-500/month in SaaS fees. This skill rewrites them as standalone scripts that run forever with zero subscription cost. Each migration is a $500-5000 billable deliverable.
## Trigger
Use when: "migrate this workflow", "convert N8N to Python", "rewrite my Zapier", "turn this automation into a script", "get off N8N"
Invoked as: `/workflow-migrate [workflow description or paste]`
---
## Process
### Step 1: Parse the Workflow Input
From `$ARGUMENTS`:
If it's a description ("when a form is submitted, send email and update Airtable"): parse directly
If it's N8N JSON: read and extract nodes/connections
If it's Zapier steps: parse the trigger + action chain
If it's Make (formerly Integromat) scenario: parse modules
Extract and document:
Triggers:
Webhook (POST endpoint)
Cron/schedule (every X minutes/hours)
Form submission
Email received
File drop (S3, Google Drive, local folder)
DB row created/updated
Actions:
HTTP/API calls (list each endpoint, method, payload)
Database reads/writes
Email sends
File operations
Conditional logic (if/else branches)
Loops over arrays
Data transformations
Data flow:
Input payload fields used
Intermediate computed values
Output destinations
If the workflow description is too vague, ask 2-3 targeted questions before proceeding:
"What triggers it — webhook, schedule, or something else?"
"Which API endpoints does it call and with what data?"
"What counts as success? What should happen on failure?"
---
### Step 2: Choose Language
Default to Python unless:
The workflow is heavily async/event-driven (prefer Node.js)
Existing codebase is Node.js
Kevin explicitly requests Node
Python stack: `requests`, `schedule`, `logging`, `tenacity` (retry), `python-dotenv`
Node.js stack: `axios`, `node-cron`, `winston`, `async-retry`, `dotenv`
---
### Step 3: Write the Script
Generate a complete, runnable script. Required elements:
#### Python Template Structure:
```python
#!/usr/bin/env python3
"""
[Workflow Name] — Migrated from [N8N/Zapier/Make]
Original: [brief description of what the workflow did]
Migrated: [date]
Usage:
python workflow_[name].py # run once
python workflow_[name].py --schedule # run on schedule
python workflow_[name].py --dry-run # test without side effects
"""
import os
import sys
import logging
import time
import argparse
from datetime import datetime
from typing import Optional, Dict, Any
import requests
from tenacity import retry, stop_after_attempt, wait_exponential, retry_if_exception_type
from dotenv import load_dotenv
load_dotenv()
# ─── Logging ───────────────────────────────────────────────────────────────────
logging.basicConfig(
level=logging.INFO,
format="%(asctime)s [%(levelname)s] %(message)s",
handlers=[
logging.StreamHandler(sys.stdout),
logging.FileHandler(f"logs/workflow_{datetime.now().strftime('%Y%m')}.log"),
]
)
log = logging.getLogger(__name__)
# ─── Config ────────────────────────────────────────────────────────────────────
API_KEY = os.getenv("API_KEY") # from .env
WEBHOOK_URL = os.getenv("WEBHOOK_URL") # destination
DRY_RUN = False
# ─── Retry Decorator ───────────────────────────────────────────────────────────
@retry(
stop=stop_after_attempt(3),
wait=wait_exponential(multiplier=1, min=2, max=30),
retry=retry_if_exception_type((requests.RequestException, ConnectionError)),
before_sleep=lambda rs: log.warning(f"Retrying (attempt {rs.attempt_number})..."),
reraise=True
)
def api_call(method: str, url: str, **kwargs) -> Dict[str, Any]:
"""Make an HTTP call with automatic retry and exponential backoff."""
if DRY_RUN:
log.info(f"[DRY RUN] {method.upper()} {url} payload={kwargs.get('json', {})}")
return {"dry_run": True}
resp = requests.request(method, url, timeout=30, **kwargs)
resp.raise_for_status()
return resp.json()
```
#### Node.js Template Structure:
```javascript
#!/usr/bin/env node
/**
* [Workflow Name] — Migrated from [N8N/Zapier/Make]
* Original: [brief description]
* Migrated: [date]
*
* Usage:
* node workflow_[name].js # run once
* node workflow_[name].js --schedule # run on schedule
* node workflow_[name].js --dry-run # test without side effects
*/
require('dotenv').config();
const axios = require('axios');
const retry = require('async-retry');
const cron = require('node-cron');
const winston = require('winston');
const fs = require('fs');
// ─── Logger ────────────────────────────────────────────────────────────────────
const logger = winston.createLogger({
level: 'info',
format: winston.format.combine(winston.format.timestamp(), winston.format.json()),
transports: [
new winston.transports.Console({ format: winston.format.simple() }),
new winston.transports.File({ filename: `logs/workflow_${new Date().toISOString().slice(0,7)}.log` }),
],
});
// ─── Config ────────────────────────────────────────────────────────────────────
const API_KEY = process.env.API_KEY;
const DRY_RUN = process.argv.includes('--dry-run');
// ─── Retry Wrapper ─────────────────────────────────────────────────────────────
async function apiCall(method, url, data = {}, headers = {}) {
return retry(async (bail, attempt) => {
if (DRY_RUN) {
logger.info(`[DRY RUN] ${method.toUpperCase()} ${url}`, { data });
return { dry_run: true };
}
try {
const resp = await axios({ method, url, data, headers, timeout: 30000 });
return resp.data;
} catch (err) {
if (err.response && err.response.status < 500) bail(err); // 4xx = don't retry
logger.warn(`Retrying attempt ${attempt}...`, { error: err.message });
throw err;
}
}, { retries: 3, minTimeout: 2000, maxTimeout: 30000, factor: 2 });
}
```
For each action in the workflow, write a dedicated function:
One function per logical action (e.g., `fetch_leads()`, `send_notification()`, `update_database()`)
Functions are composable and testable in isolation
Every function logs what it's doing: start, result, any errors
Main orchestrator:
```python
def run(dry_run: bool = False):
global DRY_RUN
DRY_RUN = dry_run
log.info("=== Workflow started ===")
try:
# Step 1: [action name]
data = fetch_source_data()
log.info(f"Fetched {len(data)} records")
# Step 2: [action name]
for item in data:
result = process_item(item)
if result:
send_to_destination(result)
log.info("=== Workflow completed successfully ===")
except Exception as e:
log.error(f"Workflow failed: {e}", exc_info=True)
send_alert(f"Workflow [name] failed: {e}") # self-healing alert
raise
```
Self-healing patterns to include:
Alert on failure (Telegram message via Kevin's bot token if available, else log to file)
Idempotency: skip already-processed records (use a state file or DB flag)
Dead-letter queue: failed items saved to `failed_[date].json` for manual review
Heartbeat: log "still alive" every N runs for scheduled workflows
---
### Step 4: Generate .env.example
```bash
# [Workflow Name] — Environment Variables
# Copy to .env and fill in values
API_KEY=your_api_key_here
WEBHOOK_URL=https://...
DATABASE_URL=...
# Optional: Telegram alerts on failure
TELEGRAM_BOT_TOKEN=
TELEGRAM_CHAT_ID=8062428674
```
---
### Step 5: Generate requirements.txt or package.json
Python:
```
requests>=2.31.0
tenacity>=8.2.0
python-dotenv>=1.0.0
schedule>=1.2.0 # only if cron-triggered
```
Node.js:
```json
{
"dependencies": {
"axios": "^1.6.0",
"async-retry": "^1.3.3",
"node-cron": "^3.0.3",
"winston": "^3.11.0",
"dotenv": "^16.3.1"
}
}
```
---
### Step 6: If the Workflow is Recurring — Generate a SKILL.md
If the workflow runs on a schedule or will be reused:
Generate a `SKILL.md` in the same output directory
Name it after the workflow function
Description: "Run [workflow name] — [what it does in 10 words]"
Instructions: path to script, how to run it, what env vars are needed
---
### Step 7: Save Outputs and Print Migration Summary
Output location: Ask Kevin where to save, default to `./workflow_[name]/`
Create:
`workflow_[name].py` (or `.js`)
`.env.example`
`requirements.txt` (or `package.json`)
`SKILL.md` (if recurring)
`README.md` (quick usage guide — 20 lines max)
Print migration summary:
```
Migration complete.
Original: [N8N/Zapier/Make] workflow — [X] nodes/steps
Output: ./workflow_[name]/workflow_[name].py
What changed:
- [X] N8N nodes → [Y] lines of Python
- Added: retry with exponential backoff (3 attempts, 2s-30s)
- Added: rotating log file (monthly)
- Added: dry-run mode (--dry-run flag)
- Added: failure alerts via [Telegram/log]
- Removed: $XX/month SaaS subscription
To run:
cd workflow_[name]/
cp .env.example .env # fill in your keys
pip install -r requirements.txt
python workflow_[name].py --dry-run # test first
python workflow_[name].py # run for real
```
---
## Error Handling
Ambiguous workflow: ask 2-3 targeted questions, don't guess at API endpoints
Proprietary N8N nodes (e.g., OpenAI node): rewrite using the raw API — include API docs link in comments
Very complex workflow (>15 nodes): break into multiple scripts with a coordinator, document the dependency order
No credentials visible: generate .env.example with clear placeholders, add comments explaining where each key comes from
Webhook trigger: generate a Flask/Express endpoint stub that receives the webhook and calls the workflow function
## Notes
Always test with `--dry-run` before running for real
State file for idempotency: `./state/processed_ids.json` — create `state/` dir if it doesn't exist
For scheduled runs, prefer `cron` / `schedule` over external task runners (fewer dependencies)

Use Cases

Convert N8N workflows to production-grade Python or Node.js scripts
Migrate Zapier automations to self-hosted code implementations
Transform Make (Integromat) scenarios into maintainable codebases
Eliminate low-code platform lock-in by migrating to open-source code
Reduce automation costs by replacing paid workflow platforms with custom scripts

Pros & Cons

Pros

+Supports migration from all three major platforms — N8N, Zapier, and Make
+Produces production-grade code rather than simple script translations
+Accepts both workflow descriptions and pasted workflow definitions

Cons

-Migrated code may not handle all edge cases of the original low-code platform
-Complex workflows with many integrations may be difficult to fully replicate

FAQ

What does workflow-migrate do?

Migrate N8N/Zapier/Make workflows to production-grade Python or Node.js scripts. Given a workflow description or paste, rewrites automation logic with retry,...

What platforms support workflow-migrate?

workflow-migrate is available on Claude Code, OpenClaw.

What are the use cases for workflow-migrate?

Convert N8N workflows to production-grade Python or Node.js scripts. Migrate Zapier automations to self-hosted code implementations. Transform Make (Integromat) scenarios into maintainable codebases.

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