Agent skill · software engineering · jeremylongshore
lindy-ci-integration
Configure CI/CD pipelines for testing Lindy AI agent integrations.
Why this skill is useful
Adds a complete CI/CD pipeline setup for testing Lindy AI integrations, including GitHub Actions workflows and executable test scripts.
What it needs
Requires node installed locally. Requires github account access. About 3k tokens when loaded. Last updated 2026-08-07. 2,604 stars on the source repository.
What this skill does
Lindy CI Integration Overview Lindy agents run on Lindy's managed platform — CI/CD tests your integration code: webhook receivers, callback handlers, and application logic that interacts with Lindy agents. Test webhook signature verification, payload processing, and error handling without hitting live Lindy endpoints. Prerequisites GitHub repository with Actions enabled Lindy API key and webhook secret stored as GitHub secrets Node.js project with webhook receiver code Completed lindy-install-auth setup Instructions Step 1: Store Secrets in GitHub Step 2: Create GitHub Actions Workflow Step 3: Write Webhook Handler Tests Step 4: Add Smoke Test for Live Connectivity Step 5: PR Status Check Test Categories Category What It Tests Requires Live Lindy? ---------- ------------- --------------------- Auth verification Webhook signature checking No Payload processing Data extraction and transformation No Error handling Malformed input, edge cases No Connectivity Webhook endpoint reachability Yes (non-blocking) End-to-end Full trigger -> callback cycle Yes Error Handling Issue Cause Solution ------- ------- ---------- Secret not found in CI Not configured gh secret set LINDYWEBHOOKSECRET Connectivity test fails Lindy endpoint unreachable in CI Mark as continue-on-error: true Tests timeout Network latency Set timeout-minutes: 10 on job Flaky live tests Lindy processing delay Add retry logic or mock external calls Output Produce a CI integration record containing the workflow trigger, test fixtures, required secrets by name only, failure ownership, and the command or dashboard evidence proving that the automation ran against a non-production agent. Examples For a pull request, trigger a disposable Lindy test agent with fixed fixture input, wait for its terminal status, and fail the workflow when the expected action is absent or the agent reports an error. Keep the production agent ID out of the workflow and promote only after the fixture result is reviewed. …
How to use it
Reference it in AdaL, Claude Code, Cursor or any coding agent — nothing to install:
@skills jeremylongshore/lindy-ci-integration