| name | managing-temp-scripts |
| description | Create and execute temporary scripts (Python, Node.js, shell) during workflow execution for API integrations, data processing, and custom tools. Use when user needs to interact with external APIs, process data with specific libraries, or create temporary executable code. |
Managing Temporary Scripts
I help you create and execute temporary scripts during workflow execution. Perfect for API integrations, data processing with specialized libraries, and creating temporary tools that execute and return results.
When I Activate
I automatically activate when you:
- Need to interact with external APIs (Reddit, Twitter, GitHub, etc.)
- Want to use specific libraries not available in Claude Code
- Need to process data with custom code
- Ask "how do I call an API in a workflow?"
- Mention "temporary script", "execute code", "API client"
- Need credentials/API keys for external services
Key Concept
Temporary scripts are code files that:
- Are created during workflow execution
- Execute via Bash tool
- Return results to workflow
- Are automatically cleaned up after workflow completion
Supported Languages:
- Python (with pip packages)
- Node.js/JavaScript (with npm packages)
- Shell/Bash scripts
- Ruby, Go, or any executable language
Quick Example
# 1. Ask for API credentials
AskUserQuestion:"Reddit API key needed":api_key ->
# 2. Create Python script with embedded credentials
general-purpose:"Create Python script: reddit_client.py with {api_key}":script_path ->
# 3. Execute script and capture output
Bash:"python3 {script_path}":reddit_data ->
# 4. Process results in workflow
general-purpose:"Analyze {reddit_data} and create summary":analysis ->
# 5. Cleanup happens automatically
Script Lifecycle
See script-lifecycle.md for complete details.
Overview:
1. Creation
↓
Write script to /tmp/workflow-scripts/
2. Preparation
↓
Set permissions (chmod +x)
Install dependencies if needed
3. Execution
↓
Run via Bash tool
Capture stdout/stderr
4. Data Return
↓
Parse output (JSON, CSV, text)
Pass to next workflow step
5. Cleanup
↓
Remove script files
Clean temp directories
Common Use Cases
1. API Integration
Reddit API Client:
# /tmp/workflow-scripts/reddit_client.py
import requests
import json
import sys
api_key = sys.argv[1]
subreddit = sys.argv[2]
headers = {'Authorization': f'Bearer {api_key}'}
response = requests.get(
f'https://oauth.reddit.com/r/{subreddit}/hot.json',
headers=headers
)
print(json.dumps(response.json(), indent=2))
In workflow:
$script-creator:"Create reddit_client.py":script ->
Bash:"python3 {script} {api_key} programming":posts ->
general-purpose:"Parse {posts} and extract top 10 titles"
2. Data Processing
CSV Analysis:
# /tmp/workflow-scripts/analyze_data.py
import pandas as pd
import sys
df = pd.read_csv(sys.argv[1])
summary = df.describe().to_json()
print(summary)
In workflow:
general-purpose:"Create analyze_data.py script":script ->
Bash:"pip install pandas && python3 {script} data.csv":analysis ->
general-purpose:"Interpret {analysis} and create report"
3. Web Scraping
Article Scraper:
// /tmp/workflow-scripts/scraper.js
const axios = require('axios');
const cheerio = require('cheerio');
async function scrapeArticles(url) {
const {data} = await axios.get(url);
const $ = cheerio.load(data);
const articles = [];
$('.article').each((i, el) => {
articles.push({
title: $(el).find('.title').text(),
url: $(el).find('a').attr('href')
});
});
console.log(JSON.stringify(articles));
}
scrapeArticles(process.argv[2]);
In workflow:
general-purpose:"Create scraper.js":script ->
Bash:"npm install axios cheerio && node {script} https://news.site":articles ->
general-purpose:"Process {articles}"
Script Templates
See script-templates.md for complete library.
Quick templates:
- API Client (REST, GraphQL)
- Data Processing (CSV, JSON, XML)
- Web Scraping (HTML parsing)
- File Processing (PDF, images, documents)
- Database Access (PostgreSQL, MySQL, MongoDB)
- Message Queues (RabbitMQ, Kafka)
- Cloud Services (AWS S3, GCS, Azure)
Security Best Practices
See security.md for comprehensive guide.
Quick checklist:
✅ Credentials Management:
- Pass via command-line arguments (not hardcoded)
- Use environment variables for sensitive data
- Clean up after execution
✅ File Permissions:
chmod 700 /tmp/workflow-scripts/script.py # Owner only
✅ Output Sanitization:
- Validate script output before using
- Escape special characters
- Limit output size
✅ Dependency Management:
- Use virtual environments for Python
- Specify exact package versions
- Avoid running arbitrary code
Integration with Workflows
See integration-patterns.md for detailed patterns.
Pattern 1: Simple Script Execution
general-purpose:"Create script.py that fetches data":script ->
Bash:"python3 {script}":data ->
general-purpose:"Process {data}"
Pattern 2: Script with User Input
AskUserQuestion:"API credentials needed":creds ->
general-purpose:"Create api_client.py with {creds}":script ->
Bash:"python3 {script}":results ->
general-purpose:"Analyze {results}"
Pattern 3: Parallel Script Execution
general-purpose:"Create multiple API clients":scripts ->
[
Bash:"python3 {scripts.reddit}":reddit_data ||
Bash:"python3 {scripts.twitter}":twitter_data ||
Bash:"python3 {scripts.github}":github_data
] ->
general-purpose:"Merge all data sources"
Pattern 4: Iterative Processing
@process_batch ->
general-purpose:"Create batch_processor.py":script ->
Bash:"python3 {script} batch_{n}":results ->
(if results.has_more)~> @process_batch ~>
(if results.complete)~> general-purpose:"Finalize"
Script Directory Structure
/tmp/workflow-scripts/
├── {workflow-id}/ # Unique per workflow
│ ├── reddit_client.py
│ ├── data_processor.py
│ ├── requirements.txt # Python dependencies
│ ├── package.json # Node.js dependencies
│ └── .env # Environment variables
Automatic cleanup after workflow:
rm -rf /tmp/workflow-scripts/{workflow-id}
Creating Scripts in Workflows
Method 1: Inline Script Creation
general-purpose:"Create Python script:
```python
import requests
import sys
api_key = sys.argv[1]
response = requests.get(
'https://api.example.com/data',
headers={'Authorization': f'Bearer {api_key}'}
)
print(response.text)
Save to /tmp/workflow-scripts/api_client.py":script_path ->
Bash:"python3 {script_path} {api_key}":data
### Method 2: Template-Based Creation
```flow
general-purpose:"Use template: api-rest-client
- Language: Python
- API: Reddit
- Auth: Bearer token
- Output: JSON
Create script in /tmp/workflow-scripts/":script ->
Bash:"python3 {script}":data
Method 3: Multi-File Scripts
general-purpose:"Create script package:
- main.py (entry point)
- utils.py (helper functions)
- requirements.txt (dependencies)
Save to /tmp/workflow-scripts/package/":package_path ->
Bash:"cd {package_path} && pip install -r requirements.txt && python3 main.py":data
Dependency Management
Python (pip)
general-purpose:"Create requirements.txt:
requests==2.31.0
pandas==2.0.0
Save to /tmp/workflow-scripts/":deps ->
general-purpose:"Create script.py":script ->
Bash:"pip install -r {deps} && python3 {script}":data
Node.js (npm)
general-purpose:"Create package.json with dependencies":package ->
general-purpose:"Create script.js":script ->
Bash:"cd /tmp/workflow-scripts && npm install && node {script}":data
Virtual Environments
Bash:"python3 -m venv /tmp/workflow-scripts/venv":venv ->
general-purpose:"Create script in venv":script ->
Bash:"source /tmp/workflow-scripts/venv/bin/activate && python3 {script}":data
Error Handling
Capturing Errors
Bash:"python3 {script} 2>&1":output ->
(if output.contains('Error'))~>
general-purpose:"Parse error: {output}":error ->
@review-error:"Script failed: {error}" ~>
(if output.success)~>
general-purpose:"Process {output}"
Retry Logic
@retry ->
Bash:"python3 {script}":result ->
(if result.failed)~>
general-purpose:"Wait 5 seconds" ->
@retry ~>
(if result.success)~>
general-purpose:"Process {result}"
Output Formats
Scripts can return data in various formats:
JSON (Recommended)
import json
result = {"data": [...], "status": "success"}
print(json.dumps(result))
CSV
import csv
import sys
writer = csv.writer(sys.stdout)
writer.writerows(data)
Plain Text
for item in results:
print(f"{item['title']}: {item['url']}")
Cleanup
Automatic Cleanup
Cleanup happens automatically after workflow completion:
# At end of workflow execution:
general-purpose:"Remove all scripts in /tmp/workflow-scripts/{workflow-id}"
Manual Cleanup
For long-running workflows:
general-purpose:"Create and execute script":result ->
general-purpose:"Process {result}":output ->
Bash:"rm -rf /tmp/workflow-scripts/{script-dir}":cleanup
Best Practices
DO:
✅ Use unique workflow IDs for script directories ✅ Pass credentials as arguments, not hardcoded ✅ Validate and sanitize script output ✅ Use virtual environments for Python ✅ Specify exact dependency versions ✅ Return structured data (JSON preferred) ✅ Clean up after workflow completion ✅ Set restrictive file permissions ✅ Use timeouts for script execution ✅ Log script output for debugging
DON'T:
❌ Hardcode API keys in scripts ❌ Execute untrusted code ❌ Store sensitive data in script files ❌ Leave scripts after workflow ❌ Use global Python/Node packages ❌ Ignore script errors ❌ Return massive outputs (>1MB) ❌ Use system-wide directories
Tips for Effective Script Management
Use Descriptive Names:
reddit_api_client.pynotscript.pyReturn Structured Data: Always use JSON when possible
Error Messages: Include detailed error messages in output
Logging: Add logging for debugging:
import logging
logging.basicConfig(level=logging.INFO)
logging.info(f"Fetching data from {url}")
Validation: Validate inputs before execution
Timeouts: Set execution timeouts:
Bash:"timeout 30 python3 {script}":data
Related Skills
- creating-workflows: Create workflows that use temp scripts
- executing-workflows: Execute workflows with script steps
- managing-agents: Temp agents vs temp scripts
- debugging-workflows: Debug script execution issues
Advanced Topics
See detail files for:
- script-lifecycle.md - Complete lifecycle management
- script-templates.md - 20+ ready-to-use templates
- security.md - Security best practices
- integration-patterns.md - Workflow integration patterns
Ready to use temporary scripts? Just describe what API or processing you need!