Atlas / Skills / jeremylongshore / Customerio Deploy Pipeline

Customerio Deploy PipelineSAFE

skills/jeremylongshore/customerio-deploy-pipeline

Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
1.14.0
Hosts
1 documented
License
MIT
Stars
2,823
01

Overview

Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.

Read from source at commit 4f83675ca38aOBSERVED · 2026-10-08
02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
claude-codementioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: customerio-deploy-pipeline
description: 'Deploy Customer.io integrations to production cloud platforms.

  Use when deploying to Cloud Run, Vercel, AWS Lambda, or Kubernetes

  with proper secrets management and health checks.

  Trigger: "deploy customer.io", "customer.io cloud run",

  "customer.io kubernetes", "customer.io lambda", "customer.io vercel".

  '
allowed-tools: Read, Write, Edit, Bash(npm:*), Bash(gcloud:*), Bash(kubectl:*), Glob,
  Grep
version: 1.14.0
license: MIT
author: Jeremy Longshore <[email protected]>
tags:
- saas
- customer-io
- deployment
- cloud-run
- kubernetes
compatibility: Designed for Claude Code
---
# Customer.io Deploy Pipeline

## Output

- A versioned, staged deployment of Customer.io configuration/code with owner approval, validation evidence, and a rollback reference.
- A protected promotion path that prevents unreviewed changes from affecting production recipients.

## Examples

Validate an event/template configuration in development and staging with synthetic profiles, attach schema/template test results to the change, then release through an approved canary. If the canary shows wrong audience, consent, or rendering behavior, stop promotion and restore the last approved configuration.

## Overview

Deploy Customer.io integrations to production: GCP Cloud Run with Secret Manager, Vercel serverless functions, AWS Lambda with SSM, Kubernetes with external secrets, plus health check endpoints and blue-green deployment scripts.

## Prerequisites

- CI/CD pipeline configured (see `customerio-ci-integration`)
- Cloud platform credentials and access
- Production Customer.io credentials in a secrets manager

## Instructions

### Step 1: Deploy to Google Cloud Run

```yaml
# .github/workflows/deploy-cloud-run.yml
name: Deploy to Cloud Run
on:
  push:
    branches: [main]

jobs:
  deploy:
    runs-on: ubuntu-latest
    permissions:
      contents: read
      id-token: write  # Required for Workload Identity Federation
    steps:
      - uses: actions/checkout@v4

      - id: auth
        uses: google-github-actions/auth@v2
        with:
          workload_identity_provider: ${{ secrets.WIF_PROVIDER }}
          service_account: ${{ secrets.WIF_SA }}

      - uses: google-github-actions/setup-gcloud@v2

      - name: Build and push
        run: |
          gcloud builds submit --tag gcr.io/${{ secrets.GCP_PROJECT }}/cio-service

      - name: Deploy
        run: |
          gcloud run deploy cio-service \
            --image gcr.io/${{ secrets.GCP_PROJECT }}/cio-service \
            --region us-central1 \
            --set-secrets "CUSTOMERIO_SITE_ID=cio-site-id:latest,\
              CUSTOMERIO_TRACK_API_KEY=cio-track-key:latest,\
              CUSTOMERIO_APP_API_KEY=cio-app-key:latest" \
            --set-env-vars "CUSTOMERIO_REGION=us,NODE_ENV=production" \
            --min-instances 1 \
            --max-instances 10 \
            --memory 512Mi \
            --cpu 1 \
            --allow-unauthenticated
```

### Step 2: Health Check Endpoint

```typescript
// routes/health.ts
import { TrackClient, RegionUS } from "customerio-node";
import { Router } from "express";

const router = Router();

router.get("/health", async (_req, res) => {
  const checks: Record<string, { status: string; latency_ms?: number }> = {};

  // Check Track API
  const cio = new TrackClient(
    process.env.CUSTOMERIO_SITE_ID!,
    process.env.CUSTOMERIO_TRACK_API_KEY!,
    { region: RegionUS }
  );

  const start = Date.now();
  try {
    await cio.identify("health-check", {
      email: "[email protected]",
      _health_check: true,
    });
    checks.track_api = { status: "ok", latency_ms: Date.now() - start };
  } catch (err: any) {
    checks.track_api = { status: `error: ${err.statusCode}` };
  }

  const allOk = Object.values(checks).every((c) => c.status === "ok");

  res.status(allOk ? 200 : 503).json({
    status: allOk ? "healthy" : "degraded",
    checks,
    version: process.env.npm_package_version ?? "unknown",
    uptime_seconds: Math.floor(process.uptime()),
    timestamp: new Date().toISOString(),
  });
});

export default router;
```

### Step 3: Vercel Serverless Functions

```typescript
// api/customerio/identify.ts (Vercel serverless function)
import type { VercelRequest, VercelResponse } from "@vercel/node";
import { TrackClient, RegionUS } from "customerio-node";

const cio = new TrackClient(
  process.env.CUSTOMERIO_SITE_ID!,
  process.env.CUSTOMERIO_TRACK_API_KEY!,
  { region: RegionUS }
);

export default async function handler(req: VercelRequest, res: VercelResponse) {
  if (req.method !== "POST") {
    return res.status(405).json({ error: "Method not allowed" });
  }

  const { userId, attributes } = req.body;
  if (!userId || !attributes?.email) {
    return res.status(400).json({ error: "userId and attributes.email required" });
  }

  try {
    await cio.identify(userId, {
      ...attributes,
      last_seen_at: Math.floor(Date.now() / 1000),
    });
    return res.status(200).json({ success: true });
  } catch (err: any) {
    return res.status(err.statusCode ?? 500).json({ error: err.message });
  }
}
```

### Step 4: Kubernetes Deployment

```yaml
# k8s/customerio-service.yaml
apiVersion: apps/v1
kind: Deployment
metadata:
  name: customerio-service
spec:
  replicas: 2
  selector:
    matchLabels:
      app: customerio-service
  template:
    metadata:
      labels:
        app: customerio-service
    spec:
      containers:
        - name: app
          image: gcr.io/my-project/cio-service:latest
          ports:
            - containerPort: 3000
          env:
            - name: CUSTOMERIO_SITE_ID
              valueFrom:
                secretKeyRef:
                  name: customerio-secrets
                  key: site-id
            - name: CUSTOMERIO_TRACK_API_KEY
              valueFrom:
                secretKeyRef:
                  name: customerio-secrets
                  key: track-api-key
            - 
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codePASS
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-08 · audit v0.4.1 · source sha 4f83675ca38afull audit observations/trust-audit/skill/jeremylongshore__customerio-deploy-pipeline.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-084f83675ca38aSAFEB89first audit
06

Questions

What does the Customerio Deploy Pipeline skill do?

Model-agnostic agent-skills platform with a harness-free canonical layer, verified adapters, and the ccpi package manager. Explore at tonsofskills.com.

Is Customerio Deploy Pipeline safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Customerio Deploy Pipeline access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does Customerio Deploy Pipeline work with?

Its documentation mentions claude-code. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (4f83675ca38a), read on 2026-10-08. The repository is watched, and a new audit runs when it changes — this is the first audit.

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