Yao ChatGPT Crawler

Inputs

Questions, repeat count, target entity/type (person/company/product), browser profile, delay preset, optional output directory, and same-type competitors.

Use random 30s-1m by default; support 1-3m and 3-10m when requested.

Workflow

1. Read references/user-setup-and-usage.md, references/chatgpt-crawl-workflow.md, and references/report-contract.md as needed.
2. Run node scripts/preflight.mjs --profile <profile> before fresh crawling.
3. Stage 1: run scripts/chatgpt_batch_crawl.mjs with questions, repeat, profile, target entity/type, interval preset, and output dir.
4. Stage 2: run scripts/analyze_chatgpt_results.py. Follow the competitor-review rules in the workflow reference; a target-only alias file never disables inference.
5. Return crawl JSON, summary, structured Markdown/Excel, HTML report, optional semantic-review cache, and failed logs.

Honest Boundaries

• Reuses local ChatGPT web automation; does not bypass login, bot checks, or hidden data.
• Visible ChatGPT citations bound source analysis; probability metrics are repeated-sample estimates.
• Inferred competitors are heuristic. Review aliases before external use; use --semantic-review required when formal-report confidence demands it.
• The entity table is an audit surface; only rows entering the competitor matrix affect metrics.
• Preserve raw answers, reference titles, URLs, and logs so every conclusion can be audited.