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name: abuse-prevention description: Abuse prevention - rate limiting, moderation, bad actors. Use when fighting abuse.

Abuse Prevention Guideline

Tech Stack

• Analytics: PostHog
• Database: Neon (Postgres)
• Workflows: Upstash Workflows + QStash

Non-Negotiables

• All enforcement actions must be auditable (who/when/why)
• Appeals process must exist for affected users
• Graduated response levels must be defined (warn → restrict → suspend → ban)

Context

Trust & safety is about protecting users — from each other and from malicious actors. Every platform eventually attracts abuse. The question is whether you're prepared for it or scrambling to react.

Consider: what would a bad actor try to do? How would we detect it? How would we respond? What about the false positives — innocent users caught by automated systems? A good T&S system is effective against abuse AND fair to legitimate users.

Driving Questions

• What would a motivated bad actor try to do on this platform?
• How would we detect coordinated abuse or bot networks?
• What happens when automated moderation gets it wrong?
• How do affected users appeal decisions, and is it fair?
• What abuse patterns exist that we haven't addressed?
• What would make users trust that we're protecting them?