Design AutoMod rules that moderators can trust
Choose clear triggers, safe actions and useful logs for automation that supports human moderation.
Written and reviewed by the Sunatia editorial team.
Automate repetitive evidence, not difficult judgment
Automation is strongest when the pattern is objective: excessive mentions, repeated messages, known scam domains or posting faster than a reasonable limit. Context-heavy behavior such as sarcasm, conflict or misinformation still needs human review.
For each proposed rule, ask whether two reasonable moderators would agree on the trigger. If not, use the rule to flag content rather than punish automatically.
Match the action to confidence
Low-confidence detection should notify staff or hold a message for review. Medium-confidence detection can delete content and warn the member. High-confidence, high-impact attacks may justify a temporary timeout.
Permanent bans should rarely be the first automated action. Temporary measures stop immediate harm while preserving a path for review and correction.
Practical checklist
- Explain the triggered rule to the affected member.
- Include message, channel and trigger context in the staff log.
- Set an owner and review date for every automation rule.
Build exceptions narrowly
Broad exemptions create hidden attack paths. Exempt a trusted announcement bot from a link rule rather than exempting every account with a popular role. Review exceptions whenever permissions change.
Test rules in a private channel with realistic messages, including punctuation variations, languages used by the community and mobile formatting.
Treat false positives as incidents
When a legitimate message is blocked, record why the rule matched and how the action affected the member. Repeated false positives damage trust even when moderators reverse them quickly.
Use logs to compare prevented abuse with incorrect actions. Disable rules that cannot be made reliable; automation should reduce moderation risk, not merely increase the number of actions.