FI

firecrawl-reference-architecture

Build production-ready content ingestion pipelines with Firecrawl using scrape, crawl, and extract endpoints.

Install

mkdir -p .claude/skills/firecrawl-reference-architecture && curl -L -o skill.zip "https://agentskills.codes/api/skills/download/4122" && unzip -o skill.zip -d .claude/skills/firecrawl-reference-architecture && rm skill.zip

Installs to .claude/skills/firecrawl-reference-architecture

Activation

This is the description your AI agent reads to decide when to run this skill — the better it matches your request, the more reliably it fires.

Implement Firecrawl reference architecture with scrape/crawl/map/extract
72 charsno explicit “when” trigger
Intermediate

Key capabilities

  • →Design three-tier scraping and ingestion pipelines
  • →Implement on-demand scraping and scheduled crawls
  • →Perform site-wide URL discovery and mapping
  • →Process and deduplicate scraped markdown content
  • →Build RAG-ready knowledge bases

How it works

It defines a pipeline architecture using Firecrawl endpoints to map, crawl, and extract content, followed by a processing layer that cleans, hashes, and chunks data for storage.

Inputs & outputs

You give it
Base URL for crawling or mapping
You get back
Processed markdown chunks or structured JSON data

When to use firecrawl-reference-architecture

  • →Design new Firecrawl integrations
  • →Structure content ingestion for RAG
  • →Establish architectural standards for web scraping
  • →Build pipelines for AI knowledge bases

About this skill

Firecrawl Governed Ingestion Architecture

Overview

Create explicit trust boundaries from request intake through deletion. Keep source discovery, content retrieval, validation, and downstream publication independently retryable and auditable.

Prerequisites

  • The target repository or integration path and the requested operator outcome.
  • The source authorization, data classification, and environment policy.
  • Current Firecrawl documentation, credentials only when needed, and an owner for approvals.

Current Contract

Firecrawl v2 provides scrape, crawl, map, search, batch scrape, parse, JSON extraction, agentic, and browser surfaces with different async, credit, retention, and availability contracts. The SDK can auto-wait and paginate, while explicit start/status methods support durable orchestration. Provider webhooks supplement but do not replace reconciliation.

Authentication

For authenticated Cloud operations, inject FIRECRAWL_API_KEY from an approved secret manager. REST requests use Authorization: Bearer with the key. Never print, commit, transmit, or place a key in a URL. Keyless access is suitable only where the current documentation explicitly allows it and the workload accepts its limits; production workflows should make identity and team ownership explicit.

Instructions

  1. Define tenants, source authorization, freshness, scale, formats, data classification, SLO/RPO/RTO, retention, deletion, and cost constraints.
  2. Place authentication, tenant isolation, URL canonicalization, policy versioning, endpoint/format allowlists, budgets, and idempotency at the intake gateway.
  3. Separate discovery into map/search, retrieval into scrape/batch/crawl/parse, and model extraction into a validated stage. Use durable job records for asynchronous work.
  4. Persist normalized provenance and job/page state before downstream writes. Complete pagination and deduplicate by tenant, canonical source, version, and content hash.
  5. Run schema, origin-status, content-quality, malware/active-content, and prompt-injection gates before storage or agent context.
  6. Use an outbox or equivalent for indexing and publication; make retries idempotent and support tombstones across raw, normalized, embedding, cache, and search stores.
  7. Observe queue, job, origin, validation, freshness, spend, webhook, and deletion SLIs; test restore, reconciliation, cancellation, and regional/provider failure.

Tool Discipline

Use Read, Glob, and Grep to inspect code, configuration, tests, and evidence. Use Write/Edit only for approved implementation or documentation changes. Do not call Firecrawl, rotate keys, change account settings, scrape a target, or deploy merely because this skill was invoked.

Approval Boundaries

Require architecture and security/data approval before adding a new endpoint class, authenticated source, model extraction, long-term store, cross-region flow, or self-hosted provider.

Output

Return components and trust boundaries, sequence and state model, contracts, capacity and cost assumptions, security/privacy controls, failure and reconciliation paths, SLOs, tests, and phased rollout.

Error Handling

  • A stage lacks durable identity or idempotency: block asynchronous rollout.
  • Provider completion and stored counts diverge: reconcile pagination and downstream receipts before publication.
  • Deletion cannot propagate to derived stores: fail the data architecture review.

Examples

  • "Build a docs RAG pipeline" produces policy, acquisition, validation, outbox, index, and deletion stages.
  • "Call crawl directly from the browser" is replaced with a server-side governed gateway.

Resources

Read official Firecrawl evidence before relying on an endpoint, SDK method, plan limit, price, retention option, or self-hosted release.

When not to use it

  • →When real-time, sub-millisecond data access is required
  • →When site structure is too dynamic for map-based discovery

Prerequisites

FIRECRAWL_API_KEY environment variable

Limitations

  • →Crawl depth is limited by configuration
  • →Content deduplication relies on hash comparison

How it compares

This architecture standardizes content ingestion for AI applications compared to ad-hoc, unmanaged scraping scripts.

Compared to similar skills

firecrawl-reference-architecture side by side with the closest alternatives in the catalog.

SkillInstallsUpdatedSafetyDifficulty
firecrawl-reference-architecture (this skill)12moReviewIntermediate
mcp-builder1365moReviewAdvanced
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nodejs-best-practices288moNo flagsAdvanced

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