segment-cdp-v2

---
name: segment-cdp-v2
description: "Segment CDP workflow skill. Use this skill when the user needs Expert patterns for Segment Customer Data Platform including and the operator should preserve the upstream workflow, copied support files, and provenance before merging or handing off."
version: "0.0.1"
category: frontend
tags: ["segment-cdp-v2", "segment-cdp", "expert", "patterns", "for", "segment", "customer", "data"]
complexity: advanced
risk: caution
tools: ["codex-cli", "claude-code", "cursor", "gemini-cli", "opencode"]
source: community
author: "sickn33"
date_added: "2026-04-25"
date_updated: "2026-04-25"
---

# Segment CDP

## Overview

This public intake copy packages `plugins/antigravity-awesome-skills/skills/segment-cdp` from `https://github.com/sickn33/antigravity-awesome-skills` into the native Omni Skills editorial shape without hiding its origin.

Use it when the operator needs the upstream workflow, support files, and repository context to stay intact while the public validator and private enhancer continue their normal downstream flow.

This intake keeps the copied upstream files intact and uses the `external_source` block in `metadata.json` plus `ORIGIN.md` as the provenance anchor for review.

# Segment CDP Expert patterns for Segment Customer Data Platform including Analytics.js, server-side tracking, tracking plans with Protocols, identity resolution, destinations configuration, and data governance best practices.

Imported source sections that did not map cleanly to the public headings are still preserved below or in the support files. Notable imported sections: Patterns, Sharp Edges, Validation Checks, Collaboration, Limitations.

## When to Use This Skill

Use this section as the trigger filter. It should make the activation boundary explicit before the operator loads files, runs commands, or opens a pull request.

- User mentions or implies: segment
- User mentions or implies: analytics.js
- User mentions or implies: customer data platform
- User mentions or implies: cdp
- User mentions or implies: tracking plan
- User mentions or implies: event tracking

## Operating Table

| Situation | Start here | Why it matters |
| --- | --- | --- |
| First-time use | `metadata.json` | Confirms repository, branch, commit, and imported path through the `external_source` block before touching the copied workflow |
| Provenance review | `ORIGIN.md` | Gives reviewers a plain-language audit trail for the imported source |
| Workflow execution | `SKILL.md` | Starts with the smallest copied file that materially changes execution |
| Supporting context | `SKILL.md` | Adds the next most relevant copied source file without loading the entire package |
| Handoff decision | `## Related Skills` | Helps the operator switch to a stronger native skill when the task drifts |

## Workflow

This workflow is intentionally editorial and operational at the same time. It keeps the imported source useful to the operator while still satisfying the public intake standards that feed the downstream enhancer flow.

1. Confirm the user goal, the scope of the imported workflow, and whether this skill is still the right router for the task.
2. Read the overview and provenance files before loading any copied upstream support files.
3. Load only the references, examples, prompts, or scripts that materially change the outcome for the current request.
4. Execute the upstream workflow while keeping provenance and source boundaries explicit in the working notes.
5. Validate the result against the upstream expectations and the evidence you can point to in the copied files.
6. Escalate or hand off to a related skill when the work moves out of this imported workflow's center of gravity.
7. Before merge or closure, record what was used, what changed, and what the reviewer still needs to verify.

### Imported Workflow Notes

#### Imported: Patterns

### Analytics.js Browser Integration

Client-side tracking with Analytics.js. Include track, identify, page,
and group calls. Anonymous ID persists until identify merges with user.

// Next.js - Analytics provider component
// lib/segment.ts
import { AnalyticsBrowser } from '@segment/analytics-next';

export const analytics = AnalyticsBrowser.load({
  writeKey: process.env.NEXT_PUBLIC_SEGMENT_WRITE_KEY!,
});

// Typed event helpers
export interface UserTraits {
  email?: string;
  name?: string;
  plan?: 'free' | 'pro' | 'enterprise';
  createdAt?: string;
  company?: {
    id: string;
    name: string;
  };
}

export function identify(userId: string, traits?: UserTraits) {
  analytics.identify(userId, traits);
}

export function track<T extends Record<string, any>>(
  event: string,
  properties?: T
) {
  analytics.track(event, properties);
}

export function page(name?: string, properties?: Record<string, any>) {
  analytics.page(name, properties);
}

export function group(groupId: string, traits?: Record<string, any>) {
  analytics.group(groupId, traits);
}

// React hook for analytics
// hooks/useAnalytics.ts
import { useEffect } from 'react';
import { usePathname, useSearchParams } from 'next/navigation';
import { analytics, page } from '@/lib/segment';

export function usePageTracking() {
  const pathname = usePathname();
  const searchParams = useSearchParams();

  useEffect(() => {
    // Track page view on route change
    page(pathname, {
      path: pathname,
      search: searchParams.toString(),
      url: window.location.href,
      title: document.title,
    });
  }, [pathname, searchParams]);
}

// Usage in _app.tsx or layout.tsx
function RootLayout({ children }) {
  usePageTracking();

  return <html>{children}</html>;
}

// Event tracking in components
function PricingButton({ plan }: { plan: string }) {
  const handleClick = () => {
    track('Plan Selected', {
      plan_name: plan,
      page: 'pricing',
      source: 'pricing_page',
    });
  };

  return <button onClick={handleClick}>Select {plan}</button>;
}

// Identify on auth
function onUserLogin(user: User) {
  identify(user.id, {
    email: user.email,
    name: user.name,
    plan: user.plan,
    createdAt: user.createdAt,
  });

  track('User Signed In', {
    method: 'email',
  });
}

### Context

- browser tracking
- website analytics
- client-side events

### Server-Side Tracking with Node.js

High-performance server-side tracking using @segment/analytics-node.
Non-blocking with internal batching. Essential for backend events,
webhooks, and sensitive data.

// lib/segment-server.ts
import { Analytics } from '@segment/analytics-node';

// Initialize once
const analytics = new Analytics({
  writeKey: process.env.SEGMENT_WRITE_KEY!,
  flushAt: 20,      // Batch size before flush
  flushInterval: 10000,  // Flush every 10 seconds
});

// Typed server-side tracking
export interface ServerContext {
  ip?: string;
  userAgent?: string;
  locale?: string;
}

export function serverIdentify(
  userId: string,
  traits: Record<string, any>,
  context?: ServerContext
) {
  analytics.identify({
    userId,
    traits,
    context: {
      ip: context?.ip,
      userAgent: context?.userAgent,
      locale: context?.locale,
    },
  });
}

export function serverTrack(
  userId: string,
  event: string,
  properties?: Record<string, any>,
  context?: ServerContext
) {
  analytics.track({
    userId,
    event,
    properties,
    timestamp: new Date(),
    context: {
      ip: context?.ip,
      userAgent: context?.userAgent,
    },
  });
}

// Flush on shutdown
export async function closeAnalytics() {
  await analytics.closeAndFlush();
}

// Usage in API routes
// app/api/webhooks/stripe/route.ts
export async function POST(req: Request) {
  const event = await req.json();

  switch (event.type) {
    case 'checkout.session.completed':
      const session = event.data.object;

      serverTrack(
        session.client_reference_id,
        'Order Completed',
        {
          order_id: session.id,
          total: session.amount_total / 100,
          currency: session.currency,
          payment_method: session.payment_method_types[0],
        },
        { ip: req.headers.get('x-forwarded-for') || undefined }
      );

      // Also update user traits
      serverIdentify(session.client_reference_id, {
        total_spent: session.amount_total / 100,
        last_purchase_date: new Date().toISOString(),
      });
      break;

    case 'customer.subscription.created':
      serverTrack(
        event.data.object.metadata.user_id,
        'Subscription Started',
        {
          plan: event.data.object.items.data[0].price.nickname,
          amount: event.data.object.items.data[0].price.unit_amount / 100,
          interval: event.data.object.items.data[0].price.recurring.interval,
        }
      );
      break;
  }

  return new Response('ok');
}

// Graceful shutdown
process.on('SIGTERM', async () => {
  await closeAnalytics();
  process.exit(0);
});

### Context

- server-side tracking
- backend events
- webhook processing

### Tracking Plan Design

Design event schemas using Object + Action naming convention.
Define required properties, types, and validation rules.
Connect to Protocols for enforcement.

// Tracking plan definition (conceptual YAML structure)
// This maps to Segment Protocols configuration
/*
tracking_plan:
  display_name: "MyApp Tracking Plan"
  rules:
    events:
      - name: "User Signed Up"
        description: "User completed registration"
        rules:
          required:
            - signup_method
          properties:
            signup_method:
              type: string
              enum: [email, google, github]
            referral_code:
              type: string
            utm_source:
              type: string

      - name: "Product Viewed"
        description: "User viewed a product page"
        rules:
          required:
            - product_id
            - product_name
          properties:
            product_id:
              type: string
            product_name:
              type: string
            category:
              type: string
            price:
              type: number
            currency:
              type: string
              default: USD

      - name: "Order Completed"
        description: "User completed a purchase"
        rules:
          required:
            - order_id
            - total
            - products
          properties:
            order_id:
              type: string
            total:
              type: number
            currency:
              type: string
            products:
              type: array
              items:
                type: object
                properties:
                  product_id: { type: string }
                  name: { type: string }
                  price: { type: number }
                  quantity: { type: integer }

    identify:
      traits:
        - name: email
          type: string
          required: true
        - name: name
          type: string
        - name: plan
          type: string
          enum: [free, pro, enterprise]
        - name: company
          type: object
          properties:
            id: { type: string }
            name: { type: string }
*/

// TypeScript implementation with type safety
// types/segment-events.ts
export interface TrackingEvents {
  'User Signed Up': {
    signup_method: 'email' | 'google' | 'github';
    referral_code?: string;
    utm_source?: string;
  };

  'Product Viewed': {
    product_id: string;
    product_name: string;
    category?: string;
    price?: number;
    currency?: string;
  };

  'Order Completed': {
    order_id: string;
    total: number;
    currency?: string;
    products: Array<{
      product_id: string;
      name: string;
      price: number;
      quantity: number;
    }>;
  };

  'Feature Used': {
    feature_name: string;
    usage_count?: number;
  };
}

// Type-safe track function
export function trackEvent<T extends keyof TrackingEvents>(
  event: T,
  properties: TrackingEvents[T]
) {
  analytics.track(event, properties);
}

// Usage - compile-time type checking
trackEvent('Order Completed', {
  order_id: 'ord_123',
  total: 99.99,
  products: [
    { product_id: 'prod_1', name: 'Widget', price: 49.99, quantity: 2 },
  ],
});

// This would be a TypeScript error:
// trackEvent('Order Completed', { total: 99.99 });  // Missing order_id

### Context

- tracking plan
- data governance
- event schema

### Identity Resolution

Track anonymous users, then merge with identified users via identify().
Use alias() for identity merging between systems. Group users into
companies/organizations.

// Identity flow implementation
// lib/identity.ts

// Anonymous user tracking
export function trackAnonymousAction(event: string, properties?: object) {
  // Analytics.js automatically generates anonymousId
  analytics.track(event, properties);
}

// When user signs up or logs in
export async function identifyUser(user: {
  id: string;
  email: string;
  name?: string;
  plan?: string;
}) {
  // This merges anonymous history with user profile
  await analytics.identify(user.id, {
    email: user.email,
    name: user.name,
    plan: user.plan,
    created_at: new Date().toISOString(),
  });

  // Track the identification event
  analytics.track('User Identified', {
    method: 'signup',
  });
}

// B2B: Associate user with company
export function associateWithCompany(company: {
  id: string;
  name: string;
  plan?: string;
  employees?: number;
  industry?: string;
}) {
  analytics.group(company.id, {
    name: company.name,
    plan: company.plan,
    employees: company.employees,
    industry: company.industry,
  });
}

// Alias: Link identities (e.g., pre-signup email to user ID)
export function linkIdentities(previousId: string, newUserId: string) {
  // Use when you identified someone with a temporary ID
  // and now have their permanent user ID
  analytics.alias(newUserId, previousId);
}

// Full signup flow
export async function handleSignup(
  email: string,
  password: string,
  company?: { name: string; size: string }
) {
  // 1. Create user in your system
  const user = await createUser(email, password);

  // 2. Identify with Segment (merges anonymous history)
  await identifyUser({
    id: user.id,
    email: user.email,
    name: user.name,
    plan: 'free',
  });

  // 3. Track signup event
  analytics.track('User Signed Up', {
    signup_method: 'email',
    plan: 'free',
  });

  // 4. If B2B, associate with company
  if (company) {
    const companyRecord = await createCompany(company, user.id);

    associateWithCompany({
      id: companyRecord.id,
      name: company.name,
      employees: parseInt(company.size),
    });
  }
}

### Context

- user identification
- anonymous tracking
- b2b tracking

### Destinations Configuration

Route data to analytics tools, data warehouses, and marketing platforms.
Use device-mode for client-side tools, cloud-mode for server processing.

// Segment destinations are configured in the Segment UI
// but here's how to optimize your implementation

// Conditional tracking based on destination needs
// lib/segment-destinations.ts

interface DestinationConfig {
  mixpanel: boolean;
  amplitude: boolean;
  googleAnalytics: boolean;
  warehouse: boolean;
  hubspot: boolean;
}

// Only send events needed by specific destinations
export function trackWithDestinations(
  event: string,
  properties: Record<string, any>,
  options?: {
    integrations?: Partial<DestinationConfig>;
  }
) {
  analytics.track(event, properties, {
    integrations: {
      // Override specific destinations
      All: true,  // Send to all by default
      ...options?.integrations,
    },
  });
}

// Example: Track revenue event only to revenue-tracking destinations
export function trackRevenue(order: {
  orderId: string;
  total: number;
  currency: string;
}) {
  analytics.track('Order Completed', {
    order_id: order.orderId,
    revenue: order.total,
    currency: order.currency,
  }, {
    integrations: {
      // Explicitly enable revenue destinations
      'Google Analytics 4': true,
      'Mixpanel': true,
      'Amplitude': true,
      // Disable non-revenue destinations
      'Intercom': false,
      'Zendesk': false,
    },
  });
}

// Send PII only to secure destinations
export function identifyWithPII(userId: string, traits: {
  email: string;
  phone?: string;
  address?: string;
}) {
  analytics.identify(userId, traits, {
    integrations: {
      'All': false,  // Disable all by default
      // Only send PII to trusted destinations
      'HubSpot': true,
      'Salesforce': true,
      'Warehouse': true,  // Your data warehouse
      // Don't send PII to analytics tools
      'Mixpanel': false,
      'Amplitude': false,
    },
  });
}

// Context enrichment for all events
export function enrichedTrack(
  event: string,
  properties: Record<string, any>
) {
  analytics.track(event, {
    ...properties,
    // Add common context
    app_version: process.env.NEXT_PUBLIC_APP_VERSION,
    environment: process.env.NODE_ENV,
    timestamp: new Date().toISOString(),
  }, {
    context: {
      app: {
        name: 'MyApp',
        version: process.env.NEXT_PUBLIC_APP_VERSION,
      },
    },
  });
}

### Context

- data routing
- destination setup
- tool integration

### HTTP Tracking API

Direct HTTP API for any environment. Useful for edge functions,
workers, and non-Node.js backends. Batch up to 500KB per request.

// Edge/Serverless tracking via HTTP API
// lib/segment-http.ts

const SEGMENT_WRITE_KEY = process.env.SEGMENT_WRITE_KEY!;
const SEGMENT_API = 'https://api.segment.io/v1';

// Base64 encode write key for auth
const authHeader = `Basic ${btoa(SEGMENT_WRITE_KEY + ':')}`;

interface SegmentEvent {
  userId?: string;
  anonymousId?: string;
  event?: string;
  name?: string;  // For page calls
  properties?: Record<string, any>;
  traits?: Record<string, any>;
  context?: Record<string, any>;
  timestamp?: string;
}

async function segmentRequest(
  endpoint: string,
  payload: SegmentEvent
): Promise<void> {
  const response = await fetch(`${SEGMENT_API}${endpoint}`, {
    method: 'POST',
    headers: {
      'Authorization': authHeader,
      'Content-Type': 'application/json',
    },
    body: JSON.stringify({
      ...payload,
      timestamp: payload.timestamp || new Date().toISOString(),
    }),
  });

  if (!response.ok) {
    console.error('Segment API error:', await response.text());
  }
}

// HTTP API methods
export async function httpIdentify(
  userId: string,
  traits: Record<string, any>,
  context?: Record<string, any>
) {
  await segmentRequest('/identify', {
    userId,
    traits,
    context,
  });
}

export async function httpTrack(
  userId: string,
  event: string,
  properties?: Record<string, any>,
  context?: Record<string, any>
) {
  await segmentRequest('/track', {
    userId,
    event,
    properties,
    context,
  });
}

export async function httpPage(
  userId: string,
  name: string,
  properties?: Record<string, any>
) {
  await segmentRequest('/page', {
    userId,
    name,
    properties,
  });
}

// Batch API for high volume
export async function httpBatch(
  events: Array<{
    type: 'identify' | 'track' | 'page' | 'group';
    userId?: string;
    anonymousId?: string;
    event?: string;
    name?: string;
    properties?: Record<string, any>;
    traits?: Record<string, any>;
  }>
) {
  // Max 500KB per batch, 32KB per event
  await segmentRequest('/batch', {
    batch: events.map(e => ({
      ...e,
      timestamp: new Date().toISOString(),
    })),
  } as any);
}

// Cloudflare Worker example
export default {
  async fetch(request: Request): Promise<Response> {
    const { userId, action, data } = await request.json();

    // Track in edge function
    await httpTrack(userId, action, data, {
      ip: request.headers.get('cf-connecting-ip'),
      userAgent: request.headers.get('user-agent'),
    });

    return new Response('ok');
  },
};

### Context

- edge functions
- serverless
- http tracking

## Examples

### Example 1: Ask for the upstream workflow directly

```text
Use @segment-cdp-v2 to handle <task>. Start from the copied upstream workflow, load only the files that change the outcome, and keep provenance visible in the answer.
```

**Explanation:** This is the safest starting point when the operator needs the imported workflow, but not the entire repository.

### Example 2: Ask for a provenance-grounded review

```text
Review @segment-cdp-v2 against metadata.json and ORIGIN.md, then explain which copied upstream files you would load first and why.
```

**Explanation:** Use this before review or troubleshooting when you need a precise, auditable explanation of origin and file selection.

### Example 3: Narrow the copied support files before execution

```text
Use @segment-cdp-v2 for <task>. Load only the copied references, examples, or scripts that change the outcome, and name the files explicitly before proceeding.
```

**Explanation:** This keeps the skill aligned with progressive disclosure instead of loading the whole copied package by default.

### Example 4: Build a reviewer packet

```text
Review @segment-cdp-v2 using the copied upstream files plus provenance, then summarize any gaps before merge.
```

**Explanation:** This is useful when the PR is waiting for human review and you want a repeatable audit packet.



## Best Practices

Treat the generated public skill as a reviewable packaging layer around the upstream repository. The goal is to keep provenance explicit and load only the copied source material that materially improves execution.

- Keep the imported skill grounded in the upstream repository; do not invent steps that the source material cannot support.
- Prefer the smallest useful set of support files so the workflow stays auditable and fast to review.
- Keep provenance, source commit, and imported file paths visible in notes and PR descriptions.
- Point directly at the copied upstream files that justify the workflow instead of relying on generic review boilerplate.
- Treat generated examples as scaffolding; adapt them to the concrete task before execution.
- Route to a stronger native skill when architecture, debugging, design, or security concerns become dominant.



## Troubleshooting

### Problem: The operator skipped the imported context and answered too generically

**Symptoms:** The result ignores the upstream workflow in `plugins/antigravity-awesome-skills/skills/segment-cdp`, fails to mention provenance, or does not use any copied source files at all.
**Solution:** Re-open `metadata.json`, `ORIGIN.md`, and the most relevant copied upstream files. Check the `external_source` block first, then restate the provenance before continuing.

### Problem: The imported workflow feels incomplete during review

**Symptoms:** Reviewers can see the generated `SKILL.md`, but they cannot quickly tell which references, examples, or scripts matter for the current task.
**Solution:** Point at the exact copied references, examples, scripts, or assets that justify the path you took. If the gap is still real, record it in the PR instead of hiding it.

### Problem: The task drifted into a different specialization

**Symptoms:** The imported skill starts in the right place, but the work turns into debugging, architecture, design, security, or release orchestration that a native skill handles better.
**Solution:** Use the related skills section to hand off deliberately. Keep the imported provenance visible so the next skill inherits the right context instead of starting blind.



## Related Skills

- `@00-andruia-consultant` - Use when the work is better handled by that native specialization after this imported skill establishes context.
- `@00-andruia-consultant-v2` - Use when the work is better handled by that native specialization after this imported skill establishes context.
- `@10-andruia-skill-smith` - Use when the work is better handled by that native specialization after this imported skill establishes context.
- `@10-andruia-skill-smith-v2` - Use when the work is better handled by that native specialization after this imported skill establishes context.

## Additional Resources

Use this support matrix and the linked files below as the operator packet for this imported skill. They should reflect real copied source material, not generic scaffolding.

| Resource family | What it gives the reviewer | Example path |
| --- | --- | --- |
| `references` | copied reference notes, guides, or background material from upstream | `references/n/a` |
| `examples` | worked examples or reusable prompts copied from upstream | `examples/n/a` |
| `scripts` | upstream helper scripts that change execution or validation | `scripts/n/a` |
| `agents` | routing or delegation notes that are genuinely part of the imported package | `agents/n/a` |
| `assets` | supporting assets or schemas copied from the source package | `assets/n/a` |



### Imported Reference Notes

#### Imported: Sharp Edges

### Anonymous ID Persists Until Explicit Reset

Severity: MEDIUM

### Device Mode Bypasses Protocols Blocking

Severity: HIGH

### HTTP API Has Strict Size Limits

Severity: MEDIUM

### Track Calls Without Identify Are Anonymous

Severity: HIGH

### Write Key in Client is Visible (But Intentional)

Severity: LOW

### Events May Be Lost on Page Navigation

Severity: MEDIUM

### Timestamps Without Timezone Cause Analytics Issues

Severity: MEDIUM

### Tracking Before Consent Violates GDPR

Severity: HIGH

#### Imported: Validation Checks

### Dynamic Event Name

Severity: ERROR

Event names should be static, not include dynamic values

Message: Dynamic event name detected. Use static event names with dynamic properties.

### Inconsistent Event Name Casing

Severity: WARNING

Event names should follow consistent casing convention

Message: Mixed casing in event name. Use consistent convention (e.g., Title Case).

### Track Without Prior Identify

Severity: WARNING

Users should be identified before tracking critical events

Message: Revenue/conversion event without identify. Ensure user is identified.

### Missing Analytics Reset on Logout

Severity: WARNING

Analytics should be reset when user logs out

Message: Logout without analytics.reset(). Anonymous ID will persist to next user.

### Hardcoded Segment Write Key

Severity: ERROR

Write key should use environment variables

Message: Hardcoded Segment write key. Use environment variables.

### PII Sent to All Destinations

Severity: WARNING

PII should have destination controls

Message: PII in tracking without destination controls. Consider limiting destinations.

### Event Without Proper Timestamp

Severity: INFO

Explicit timestamps help with historical data

Message: Server track without explicit timestamp. Consider adding timestamp.

### Potentially Large Property Values

Severity: WARNING

Properties over 32KB will be rejected

Message: Potentially large property value. Segment has 32KB per event limit.

### Tracking Before Consent Check

Severity: ERROR

GDPR requires consent before tracking

Message: Tracking without consent check. Implement consent management for GDPR.

#### Imported: Collaboration

### Delegation Triggers

- user needs A/B testing -> analytics-specialist (Segment + LaunchDarkly/Optimizely integration)
- user needs data warehouse -> data-engineer (Segment to BigQuery/Snowflake/Redshift)
- user needs customer support integration -> zendesk-integration (Identify calls syncing to support tools)
- user needs marketing automation -> hubspot-integration (Segment to HubSpot destination)
- user needs consent management -> privacy-specialist (GDPR/CCPA compliance with Segment)

#### Imported: Limitations

- Use this skill only when the task clearly matches the scope described above.
- Do not treat the output as a substitute for environment-specific validation, testing, or expert review.
- Stop and ask for clarification if required inputs, permissions, safety boundaries, or success criteria are missing.