Segment Cdp V2

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

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 {children}; }

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

return Select {plan}; }

// 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( 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; } ) { 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 { 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 { 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

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

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

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

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.

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.