apollo-reference-architecture
Implement Apollo.io reference architecture. Use when designing Apollo integrations, establishing patterns, or building production-grade sales intelligence systems. Trigger with phrases like "apollo architecture", "apollo system design", "apollo integration patterns", "apollo best practices architecture".
Best use case
apollo-reference-architecture is best used when you need a repeatable AI agent workflow instead of a one-off prompt.
Implement Apollo.io reference architecture. Use when designing Apollo integrations, establishing patterns, or building production-grade sales intelligence systems. Trigger with phrases like "apollo architecture", "apollo system design", "apollo integration patterns", "apollo best practices architecture".
Teams using apollo-reference-architecture should expect a more consistent output, faster repeated execution, less prompt rewriting.
When to use this skill
- You want a reusable workflow that can be run more than once with consistent structure.
When not to use this skill
- You only need a quick one-off answer and do not need a reusable workflow.
- You cannot install or maintain the underlying files, dependencies, or repository context.
Installation
Claude Code / Cursor / Codex
Manual Installation
- Download SKILL.md from GitHub
- Place it in
.claude/skills/apollo-reference-architecture/SKILL.mdinside your project - Restart your AI agent — it will auto-discover the skill
How apollo-reference-architecture Compares
| Feature / Agent | apollo-reference-architecture | Standard Approach |
|---|---|---|
| Platform Support | Not specified | Limited / Varies |
| Context Awareness | High | Baseline |
| Installation Complexity | Unknown | N/A |
Frequently Asked Questions
What does this skill do?
Implement Apollo.io reference architecture. Use when designing Apollo integrations, establishing patterns, or building production-grade sales intelligence systems. Trigger with phrases like "apollo architecture", "apollo system design", "apollo integration patterns", "apollo best practices architecture".
Where can I find the source code?
You can find the source code on GitHub using the link provided at the top of the page.
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SKILL.md Source
# Apollo Reference Architecture
## Overview
Production-ready reference architecture for Apollo.io integrations. Layered design with API client, service layer, background jobs, database models, CRM sync, and deals pipeline — all built around Apollo's REST API with correct endpoints and `x-api-key` authentication.
## Prerequisites
- Apollo master API key
- Node.js 18+ with TypeScript
- PostgreSQL for data layer
- Redis for job queues
## Instructions
### Step 1: Architecture Diagram
```
┌───────────────────────────────────────────────┐
│ API Layer │ Express routes
│ POST /api/leads/search GET /api/org/:d │ POST /api/deals
├───────────────────────────────────────────────┤
│ Service Layer │ Business logic
│ LeadService EnrichService DealService │ SequenceService
├───────────────────────────────────────────────┤
│ Client Layer │ Apollo API wrapper
│ ApolloClient RateLimiter Cache │ CreditTracker
├───────────────────────────────────────────────┤
│ Background Jobs │ BullMQ queues
│ EnrichJob SyncJob StageChangeJob │ TaskCreatorJob
├───────────────────────────────────────────────┤
│ Data Layer │ Prisma/TypeORM
│ Contact Organization Deal AuditLog │
└───────────────────────────────────────────────┘
```
### Step 2: Service Layer
```typescript
// src/services/lead-service.ts
import { getApolloClient } from '../apollo/client';
import { withRetry } from '../apollo/retry';
import { cachedRequest } from '../apollo/cache';
export class LeadService {
private client = getApolloClient();
async searchPeople(params: { domains: string[]; titles?: string[]; seniorities?: string[]; page?: number }) {
return cachedRequest('/mixed_people/api_search',
() => withRetry(() => this.client.post('/mixed_people/api_search', {
q_organization_domains_list: params.domains,
person_titles: params.titles,
person_seniorities: params.seniorities,
page: params.page ?? 1, per_page: 100,
})),
params,
);
}
async enrichPerson(email: string) {
return withRetry(() => this.client.post('/people/match', { email }));
}
async enrichOrg(domain: string) {
return cachedRequest('/organizations/enrich',
() => withRetry(() => this.client.get('/organizations/enrich', { params: { domain } })),
{ domain },
);
}
}
```
### Step 3: Deals/Opportunities Service
Apollo has a full Deals API for tracking revenue pipeline.
```typescript
// src/services/deal-service.ts
export class DealService {
private client = getApolloClient();
async createDeal(params: {
name: string;
amount: number;
ownerId: string; // Apollo user ID
accountId?: string; // Apollo account ID
contactIds?: string[]; // Apollo contact IDs
stageId?: string; // Deal stage ID
}) {
const { data } = await this.client.post('/opportunities', {
name: params.name,
amount: params.amount,
owner_id: params.ownerId,
account_id: params.accountId,
contact_ids: params.contactIds,
opportunity_stage_id: params.stageId,
});
return { dealId: data.opportunity.id, name: data.opportunity.name };
}
async listDeals(page: number = 1) {
const { data } = await this.client.post('/opportunities/search', { page, per_page: 50 });
return data.opportunities.map((d: any) => ({
id: d.id, name: d.name, amount: d.amount,
stage: d.opportunity_stage?.name, owner: d.owner?.name,
}));
}
async getDealStages() {
const { data } = await this.client.get('/opportunity_stages');
return data.opportunity_stages.map((s: any) => ({ id: s.id, name: s.name, order: s.display_order }));
}
async updateDeal(dealId: string, updates: { amount?: number; stageId?: string }) {
await this.client.patch(`/opportunities/${dealId}`, {
amount: updates.amount,
opportunity_stage_id: updates.stageId,
});
}
}
```
### Step 4: Background Job Processing
```typescript
// src/jobs/enrichment-job.ts
import { Queue, Worker, Job } from 'bullmq';
import { LeadService } from '../services/lead-service';
const connection = { host: process.env.REDIS_HOST ?? 'localhost', port: 6379 };
export const enrichmentQueue = new Queue('apollo-enrichment', {
connection,
defaultJobOptions: {
attempts: 3,
backoff: { type: 'exponential', delay: 5000 },
removeOnComplete: 1000,
},
});
const leadService = new LeadService();
new Worker('apollo-enrichment', async (job: Job) => {
switch (job.name) {
case 'enrich-person':
return leadService.enrichPerson(job.data.email);
case 'enrich-org':
return leadService.enrichOrg(job.data.domain);
case 'bulk-search': {
const results: any[] = [];
for (const domain of job.data.domains) {
const { data } = await leadService.searchPeople({ domains: [domain] });
results.push(...data.people);
await job.updateProgress(results.length);
}
return { total: results.length };
}
}
}, { connection, concurrency: 3, limiter: { max: 50, duration: 60_000 } });
```
### Step 5: Database Model
```typescript
// src/models/contact.ts (Prisma schema excerpt)
// model Contact {
// id String @id @default(cuid())
// apolloId String @unique
// email String @unique
// name String
// title String?
// seniority String?
// phone String?
// linkedinUrl String?
// organizationId String?
// rawApolloData Json?
// enrichedAt DateTime?
// createdAt DateTime @default(now())
// updatedAt DateTime @updatedAt
// }
// TypeORM version
import { Entity, Column, PrimaryColumn, CreateDateColumn, UpdateDateColumn } from 'typeorm';
@Entity('contacts')
export class Contact {
@PrimaryColumn() apolloId: string;
@Column({ unique: true }) email: string;
@Column() name: string;
@Column({ nullable: true }) title: string;
@Column({ nullable: true }) seniority: string;
@Column({ nullable: true }) phone: string;
@Column({ nullable: true }) linkedinUrl: string;
@Column({ type: 'jsonb', nullable: true }) rawApolloData: Record<string, any>;
@Column({ nullable: true }) enrichedAt: Date;
@CreateDateColumn() createdAt: Date;
@UpdateDateColumn() updatedAt: Date;
}
```
### Step 6: API Routes
```typescript
// src/api/routes.ts
import { Router } from 'express';
import { LeadService } from '../services/lead-service';
import { DealService } from '../services/deal-service';
const router = Router();
const leads = new LeadService();
const deals = new DealService();
router.post('/api/leads/search', async (req, res) => {
const { data } = await leads.searchPeople(req.body);
res.json({ leads: data.people, pagination: data.pagination });
});
router.post('/api/leads/enrich', async (req, res) => {
const { data } = await leads.enrichPerson(req.body.email);
res.json({ contact: data.person });
});
router.get('/api/organizations/:domain', async (req, res) => {
const { data } = await leads.enrichOrg(req.params.domain);
res.json({ organization: data.organization });
});
router.post('/api/deals', async (req, res) => {
const result = await deals.createDeal(req.body);
res.json(result);
});
router.get('/api/deals', async (req, res) => {
const list = await deals.listDeals(parseInt(req.query.page as string) || 1);
res.json({ deals: list });
});
export { router };
```
## Output
- Layered architecture: API, Service, Client, Jobs, Data
- `LeadService` with cached search and retried enrichment
- `DealService` with create, list, update, and stage management
- BullMQ background jobs for async enrichment
- Database model (Prisma + TypeORM)
- Express API routes for search, enrichment, and deals
## Error Handling
| Layer | Strategy |
|-------|----------|
| Client | Retry with backoff, circuit breaker for prolonged outages |
| Service | Cache fallback on failure, credit budget enforcement |
| Jobs | 3 retries with exponential backoff, dead letter after max |
| API | Structured JSON error responses with error codes |
## Resources
- [Apollo API Overview](https://docs.apollo.io/docs/api-overview)
- [Create Deal](https://docs.apollo.io/reference/create-deal)
- [List Deals](https://docs.apollo.io/reference/list-all-deals)
- [Deal Stages](https://docs.apollo.io/reference/list-deal-stages)
- [BullMQ Documentation](https://docs.bullmq.io/)
## Next Steps
Proceed to `apollo-multi-env-setup` for environment configuration.Related Skills
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