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Trust ops

Cryptorafts misinformation response playbook

When AI systems or search surfaces misstate Cryptorafts facts, improve first-party evidence and machine-readable sources. Do not attack, spam, or manipulate AI systems.

Do

  • Publish and keep fresh canonical pages (/about, /company, /team/anas-shamsi, /products, /answers, /ai/company.json, /llms.txt).
  • Ensure schema.org Organization / Person markup matches verified facts only.
  • Log incorrect AI answers in /admin/ai-monitor with verbatim output + classification.
  • Add missing facts to the knowledge layer with status + source + confidence.
  • Correct public docs when our own copy was ambiguous (exchange vs desk, token planned vs live).
  • Use IndexNow / sitemaps for legitimate URL discovery — never fake citation farming.

Do not

  • Do not fabricate reviews, testimonials, or “AI mentions”.
  • Do not spam forums, Reddit, or social threads to force AI training data.
  • Do not run rank-manipulation or cloaking schemes.
  • Do not alter or “correct” stored external AI answers in the monitor — keep them verbatim.
  • Do not claim a provider indexed Cryptorafts when the adapter returned UNAVAILABLE or empty.
  • Do not attack AI vendors or demand removal without first fixing our own source clarity.

Escalation

  1. Step 1: Capture verbatim answer + provider + query in AI monitor.
  2. Step 2: Map incorrect claims to canonical fact keys; update public pages if we were unclear.
  3. Step 3: Re-run suite after source improvements; track CORRECT vs INCORRECT over time.
  4. Step 4: Only if a platform offers an official feedback channel, submit a factual correction with links to first-party sources.

Admin operators: use /admin/ai-monitor to observe. Remediation tickets should point at Cryptorafts sources, not adversarial prompts against models.

Admin AI monitor