workato-connector-sdk-quickstart
This skill should be used when the user asks about "getting started workato sdk", "first connector", "connector quickstart", "share connector", "version control connector", "workato walkthrough", "connector examples", or is new to building Workato custom connectors.
What this skill does
# Workato SDK Quickstart
Guide for getting started with Workato custom connector development.
## Overview
Workato custom connectors allow you to connect to any API not covered by built-in connectors. This guide covers:
- Setting up your first connector
- Basic connector structure
- Testing and debugging
- Sharing and version control
## Prerequisites
- Workato account with SDK access
- Basic Ruby knowledge
- API documentation for your target service
## Your First Connector
### Minimal Connector
Start with the simplest possible connector:
```ruby
{
title: 'My First Connector',
connection: {
fields: [
{ name: 'api_key', label: 'API Key', control_type: 'password' }
],
authorization: {
type: 'api_key',
apply: lambda do |connection|
headers('Authorization' => "Bearer #{connection['api_key']}")
end
},
base_uri: lambda do |connection|
'https://api.example.com'
end,
test: lambda do |connection|
get('/me')
end
},
actions: {
test_action: {
title: 'Test action',
input_fields: lambda do
[{ name: 'message', label: 'Message' }]
end,
execute: lambda do |connection, input|
{ echo: input['message'] }
end,
output_fields: lambda do
[{ name: 'echo', label: 'Echo' }]
end
}
}
}
```
### Building Blocks
#### Connection Block
Handles authentication:
```ruby
connection: {
fields: [
# Credential inputs shown to users
],
authorization: {
# How to apply credentials to requests
},
base_uri: lambda do |connection|
# Base URL for all API calls
end,
test: lambda do |connection|
# Lightweight call to verify credentials work
end
}
```
#### Actions Block
Operations users can perform:
```ruby
actions: {
action_name: {
title: 'Human readable title',
input_fields: lambda do
# Fields users fill in
end,
execute: lambda do |connection, input|
# API call logic
end,
output_fields: lambda do
# Fields available as datapills
end
}
}
```
#### Triggers Block
Events that start recipes:
```ruby
triggers: {
trigger_name: {
title: 'New something',
poll: lambda do |connection, input, closure|
# Check for new records
end,
dedup: lambda do |record|
# Unique identifier for deduplication
end,
output_fields: lambda do
# Fields available as datapills
end
}
}
```
## Testing Your Connector
### In Workato UI
1. Go to **Tools > Connector SDK**
2. Paste your connector code
3. Click **Test** to verify connection
4. Use **Debugger** tab to test actions/triggers
### Local Development (CLI)
```bash
# Install SDK gem
gem install workato-connector-sdk
# Create project
workato new my_connector
cd my_connector
# Test connection
workato exec connection.authorization --settings=settings.yaml
# Test action
workato exec actions.test_action --input='{"message": "hello"}'
```
## Common Patterns
### Making API Calls
```ruby
# GET request
get('/api/records')
# GET with params
get('/api/records').params(status: 'active', limit: 10)
# POST with payload
post('/api/records').payload(name: 'Test', email: '[email protected]')
# PUT/PATCH
put("/api/records/#{id}").payload(input)
patch("/api/records/#{id}").payload(input)
# DELETE
delete("/api/records/#{id}")
```
### Handling Responses
```ruby
execute: lambda do |connection, input|
response = get('/api/records')
# Response is automatically parsed JSON
{
total: response['total'],
records: response['items']
}
end
```
### Error Handling
```ruby
execute: lambda do |connection, input|
post('/api/records')
.payload(input)
.after_error_response(/4\d{2}/) do |code, body, headers, message|
error("API Error: #{body['message']}")
end
end
```
## Debugging Tips
### Use Logging
```ruby
execute: lambda do |connection, input|
workato.log("Input received: #{input.inspect}")
response = get('/api/records')
workato.log("API response: #{response.inspect}")
response
end
```
### Check Common Issues
| Problem | Likely Cause | Solution |
|---------|--------------|----------|
| Connection fails | Wrong credentials | Verify API key/secret |
| Empty response | Wrong endpoint | Check API docs for URL |
| Missing fields | Schema mismatch | Update output_fields |
| Action errors | Bad input | Add input validation |
## Sharing Connectors
### Export/Import
1. **Export**: Copy connector code from SDK editor
2. **Import**: Paste into another workspace's SDK editor
### Workato Community
Share connectors via Workato Community Library:
1. Test thoroughly
2. Document usage
3. Submit for review
### Version Control
Use Git to track connector changes:
```bash
# Initialize repo
git init
# Track connector file
git add connector.rb
git commit -m "Initial connector"
# Create branch for new feature
git checkout -b add-search-action
```
## Platform Limits
Be aware of Workato platform limits:
| Limit | Value |
|-------|-------|
| Max connector size | 1 MB |
| Action timeout | 120 seconds |
| Trigger poll interval | 5 minutes minimum |
| Webhook payload | 10 MB |
## Next Steps
After your first connector:
1. **Add more actions** - CRUD operations for main objects
2. **Add triggers** - Real-time events via webhooks
3. **Improve UX** - Dynamic fields, helpful hints
4. **Add tests** - RSpec tests for reliability
## Reference Files
For detailed documentation:
### Getting Started
- **`references/quickstart.md`** - Quickstart overview
- **`references/guides__walkthrough.md`** - Step-by-step walkthrough
- **`references/guides__examples.md`** - Example connectors
### Debugging & Testing
- **`references/quickstart__debugging.md`** - Debugging guide
- **`references/quickstart__FAQ.md`** - Frequently asked questions
### Sharing & Deployment
- **`references/quickstart__sharing.md`** - Sharing connectors
- **`references/quickstart__version-control.md`** - Version control practices
### Platform
- **`references/limits.md`** - Platform limits and quotas
Related in Backend & APIs
jfrog
IncludedInteract with the JFrog Platform via the JFrog CLI and REST/GraphQL APIs. Use this skill when the user wants to manage Artifactory repositories, upload or download artifacts, manage builds, configure permissions, manage users and groups, work with access tokens, configure JFrog CLI servers, search artifacts, manage properties, set up replication, manage JFrog Projects, run security audits or scans, look up CVE details, query exposures scan results from JFrog Advanced Security, manage release bundles and lifecycle operations, aggregate or export platform data, or perform any JFrog Platform administration task. Also use when the user mentions jf, jfrog, artifactory, xray, distribution, evidence, apptrust, onemodel, graphql, workers, mission control, curation, advanced security, exposures, or any JFrog product name.
cupynumeric-migration-readiness
IncludedPre-migration readiness assessor for porting NumPy to cuPyNumeric. Use BEFORE substantial porting work begins when the user asks whether code will scale on GPU, whether they should migrate to cuPyNumeric, which NumPy patterns transfer cleanly, what must be refactored before porting, or mentions pre-port assessment, scaling analysis, or refactor planning. Inspect the user's source code, look up NumPy usage, cross-reference the cuPyNumeric API support manifest, and distinguish distributed-scaling-friendly patterns from blockers such as unsupported APIs, scalar synchronization, host round-trips, Python/object-heavy control flow, shape/data-dependent branching, and in-place mutation hazards. Produce a verdict of READY, LIGHT REFACTOR, SIGNIFICANT REFACTOR, or NOT RECOMMENDED, with concrete refactor pointers.
alibabacloud-data-agent-skill
IncludedInvoke Alibaba Cloud Apsara Data Agent for Analytics via CLI to perform natural language-driven data analysis on enterprise databases. Data Agent for Analytics is an intelligent data analysis agent developed by Alibaba Cloud Database team for enterprise users. It automatically completes requirement analysis, data understanding, analysis insights, and report generation based on natural language descriptions. This tool supports: discovering data resources (instances/databases/tables) managed in DMS, initiating query or deep analysis sessions, real-time progress tracking, and retrieving analysis conclusions and generated reports. Use this Skill when users need to query databases, analyze data trends, generate data reports, ask questions in natural language, or mention "Data Agent", "data analysis", "database query", "SQL analysis", "data insights".
token-optimizer
IncludedReduce OpenClaw token usage and API costs through smart model routing, heartbeat optimization, budget tracking, and native 2026.2.15 features (session pruning, bootstrap size limits, cache TTL alignment). Use when token costs are high, API rate limits are being hit, or hosting multiple agents at scale. The 4 executable scripts (context_optimizer, model_router, heartbeat_optimizer, token_tracker) are local-only — no network requests, no subprocess calls, no system modifications. Reference files (PROVIDERS.md, config-patches.json) document optional multi-provider strategies that require external API keys and network access if you choose to use them. See SECURITY.md for full breakdown.
resend-cli
IncludedUse this skill when the task is specifically about operating Resend from an AI agent, terminal session, or CI job via the official resend CLI: installing/authenticating the CLI, sending/listing/updating/cancelling emails, batch sends, domains and DNS, webhooks and local listeners, inbound receiving, contacts, topics, segments, broadcasts, templates, API keys, profiles, or debugging Resend CLI/API failures. Trigger on mentions of Resend CLI, `resend`, `resend doctor`, `resend emails send`, `resend domains`, `resend webhooks listen`, `resend emails receiving`, or agent-friendly terminal automation.
alibabacloud-odps-maxframe-coding
IncludedUse this skill for MaxFrame SDK development and documentation navigation on Alibaba Cloud MaxCompute (ODPS). Helps answer MaxFrame API, concept, official example, and supported pandas API questions; create data processing programs; read/write MaxCompute tables; debug jobs (remote or local); and build custom DPE runtime images. Trigger when users mention MaxFrame, MaxCompute with MaxFrame, ODPS table processing, DPE runtime, MaxFrame docs/examples, DataFrame/Tensor operations, or GPU runtime setup. Works for both English and Chinese queries about Alibaba Cloud data processing with MaxFrame.