api-enrichment

name	api-enrichment
description	Build API-first enrichment pipelines — provider selection, batching, retries, rate limits, idempotency, webhooks, cost tracking, and CRM writes. Use when integrating enrichment APIs directly into GTM systems or replacing manual data workflows with programmatic pipelines.
license	MIT
compatibility	Claude Code, Jesse, Codex, Hermes, Windsurf, OpenCode, Gemini CLI, Copilot, Zed, VS Code, Goose
metadata	{"version":"1.0.0","author":"LeadMagic","category":"automation","tags":["api","enrichment","automation","pipelines","data-quality"],"related_skills":["waterfall-enrichment","data-enrichment-strategy","crm-integration","campaign-analytics"],"frameworks":["REST API Best Practices","Bulk Enrichment Patterns","DAMA-DMBOK Data Quality Dimensions","Idempotent API Design"]}

API Enrichment

Overview

API enrichment fails when teams treat it like a simple loop over contacts. The hard parts are not the HTTP calls — they are data quality, deduplication, retry safety, rate limiting, cost controls, and knowing when not to enrich.

This skill builds a production-ready enrichment pipeline that can process leads, contacts, and accounts without silent failures or uncontrolled vendor spend.

When to Use

Use this skill when the user asks to: "build an enrichment API pipeline", "integrate enrichment directly into our app", "set up automated enrichment via API", "replace manual enrichment with API calls", "batch enrich contacts", "add enrichment to inbound routing", "push enriched data to CRM", or "handle enrichment retries and webhooks".

Do not use this for tool-specific no-code workflows. Use clay-automation or n8n-automation when the user wants a no-code platform.

Authoritative Foundations

REST API Best Practices — Idempotency and Retries

Any bulk enrichment job needs idempotent writes and retry-safe requests. A retry should never create duplicate contacts, duplicate CRM notes, or duplicate sequence enrollment.

DAMA-DMBOK — Data Quality Dimensions

Provider waterfalls improve coverage and cost control by trying the best-fit source first, then falling back only when needed. This avoids paying multiple providers for the same field.

Data Quality Management — Source Priority and Freshness

Fields need source attribution and timestamps. A title from two years ago should not override a title returned yesterday. Freshness and source priority are part of the data model.

Webhook Integration Patterns

Async jobs should call back when complete instead of forcing the client to poll. Webhooks need signature verification, retry handling, and event deduplication.

Prerequisites

• Canonical record ID for every contact/account
• Source-of-truth CRM fields
• Provider API keys
• Rate limits and pricing model for each provider
• Field-level priority rules
• Error logging destination
• Webhook endpoint if processing async jobs

Step-by-Step Process

Phase 1: Define the Enrichment Contract

Field Type	Examples	Owner
Identity	name, email, phone	Enrichment pipeline
Company	domain, size, industry, funding	Enrichment pipeline
Sales context	lifecycle stage, owner, next step	CRM / rep
Compliance	suppression, opt-out, consent	Compliance system / CRM

Never let enrichment overwrite human-owned sales fields without explicit rules.

Phase 2: Build the Request Model

For every request, include external ID, input fields, provider selected, requested field set, idempotency key, timestamp, and callback URL if async. Use deterministic idempotency keys such as record_id + provider + field_set + date_bucket.

Phase 3: Design the Provider Waterfall

Step	Use When	Stop Condition
Primary provider	Best cost/coverage for segment	Required fields returned
Secondary provider	Primary misses critical field	Critical fields returned
Specialist provider	Region/persona/company-type gap	Specialist field returned
Manual review	High-value account still incomplete	Human decides

Do not call every provider for every record. Waterfall only when the previous step misses.

Phase 4: Implement Reliability Controls

Minimum controls: exponential backoff, dead-letter queue, rate-limit budget, cost ceiling, field source attribution, hash-based dedupe before CRM write, webhook signature verification.

Phase 5: Monitor the Pipeline

Track coverage by field, match rate by provider, cost per enriched record, error rate by provider, latency p50/p95, CRM write success rate, and duplicate rate.

Output Format

# API Enrichment Pipeline Plan

## Fields Owned
| Field | Source Priority | Freshness Rule | CRM Write Rule |
|---|---|---|---|

## Provider Waterfall
| Step | Provider Type | Trigger | Stop Condition | Cost Guardrail |
|---|---|---|---|---|

## Request Contract
- Required inputs:
- Idempotency key:
- Retry policy:
- Webhook policy:

## Monitoring
- Coverage:
- Cost:
- Errors:
- Latency:

Quality Check

Before delivering, verify:

• Every field has source attribution
• Retry logic is idempotent
• Provider calls stop when required fields are found
• CRM writes cannot duplicate records
• Rate limits and cost ceilings are defined
• Webhooks include verification and dedupe
• Monitoring covers coverage, cost, errors, latency, and CRM writes

Common Pitfalls

1. Looping over contacts without idempotency. Retries create duplicates. Fix: idempotency keys and upserts.
2. Calling all providers every time. Costs explode. Fix: waterfall by stop condition.
3. Overwriting rep-owned fields. Enrichment corrupts active deals. Fix: field ownership rules.
4. Silent failures. Missing data looks like no match. Fix: explicit error states and dead-letter queue.
5. No freshness rule. Old data overwrites newer CRM data. Fix: compare timestamps and source priority.
6. Polling huge jobs. Polling wastes compute and API calls. Fix: signed webhooks with retry handling.

Execution Artifacts

• references/framework-notes.md — named frameworks, citation anchors, and operating assumptions
• templates/output-template.md — copy-paste deliverable structure for the user
• scripts/check-output.py — local checklist validator for required sections This skill includes lightweight artifacts the agent can load on demand: Use the artifacts when the user asks for an implementation-ready deliverable, a repeatable workflow, or a quality check rather than generic advice.

Related Skills

• waterfall-enrichment — multi-provider enrichment design
• data-enrichment-strategy — source selection and data quality
• crm-integration — CRM writes and lifecycle fields
• campaign-analytics — measuring enrichment impact on pipeline