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This repository documents a focused web-data workflow: turn a request such as "wireless headphones" into structured products, prices, availability, ratings, review counts, and seller details. The intended outcome is product research and price-monitoring workflows, not generic scraping for its own sake.
| Job to be done | Useful output |
|---|---|
| Qualify a target list | Public records with stable source links and timestamps |
| Enrich an existing workflow | Normalized fields that can be mapped into a CRM, sheet, or database |
| Give an AI agent fresh context | A narrow, validated result set rather than unbounded page content |
import requests
payload = {"query": "wireless headphones", "limit": 25}
# Use your CoreClaw project credentials and the product endpoint documented for your account.
response = requests.post("https://api.coreclaw.com/v1/data", json=payload, timeout=30)
response.raise_for_status()
records = response.json()Endpoint names, available fields, and authentication options can vary by product plan. Check the current CoreClaw documentation before production deployment.
Before moving a data workflow to production, validate these four questions:
Is this suitable for AI agents? Yes. Use focused, source-aware records as agent context, and add permissions, logs, and human review for consequential decisions.
Does this replace every self-managed data workflow? Not necessarily. Evaluate API and in-house approaches against the reliability, fields, cost, and compliance requirements of the specific job.
Explore these closely related implementation paths:
MIT License. Demo code is provided for legitimate development and evaluation.
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