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AI agent for community moderators

Moderator Decision Consistency Agent

Fewer unexplained differences in moderation outcomes and clearer guidelines

Quality controlAnalysisCustomer support
See how it worksGet access
Moderator Decision Consistency Agent: what goes in, what the agent does and what you get

What it does

One moderator removes a heated post and warns the author, another leaves a similar one, and members notice and complain about fairness. Each week this agent reads recent moderation decisions with their reasons, groups similar cases by violation type, severity and context, and finds cases where the outcomes differ. It checks each against the community guidelines to see if the difference is justified, for example a repeat offender or a clear difference in context. For the ones that are not, it selects clear examples for a calibration meeting and suggests wording for unclear guidelines. After the meeting, it checks whether outcomes in the following weeks have become more consistent. The lead approves any guideline update. Edge case: two decisions that differ because one author had prior warnings are marked as consistent.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueApprovedYes, continueNoNo 1 STARTS WHEN Weekly review begins 2 USES A TOOL Read the week's decisions, reasons and memberhistories 3 DOES Group similar cases by violation type, severity andcontext 4 DOES Find groups with different outcomes 5 CHECKS THE RESULT Is each difference explained by guidelines or memberhistory? If not: List the unexplained pair and read the guidelinetext again. Back to step 3. 6 DOES Pick clear example cases for the calibration meeting 7 DOES Suggest clearer wording for guidelines that causeddoubt 8 YOU APPROVE Lead approves examples and guideline updates 9 USES A TOOL Read the decisions of the following weeks for thesame case types 10 CHECKS THE RESULT Have outcomes become more consistent? If not: Revisit the guideline wording and pick newexamples. Back to step 3. 11 RESULT Consistency report
Read the steps as a list
  1. Weekly review begins
  2. Read the week's decisions, reasons and member histories
  3. Group similar cases by violation type, severity and context
  4. Find groups with different outcomes
  5. Is each difference explained by guidelines or member history?If not: List the unexplained pair and read the guideline text again. Back to step 3.
  6. Pick clear example cases for the calibration meeting
  7. Suggest clearer wording for guidelines that caused doubt
  8. Lead approves examples and guideline updatesThe agent waits here for your OK.
  9. Read the decisions of the following weeks for the same case types
  10. Have outcomes become more consistent?If not: Revisit the guideline wording and pick new examples. Back to step 3.
  11. Consistency report

How it decides

It treats two cases as similar when violation type and severity match, and the outcome as inconsistent when no guideline or history explains the difference.

  • Group cases only if violation type and severity match
  • Count prior warnings as a valid reason for a different outcome
  • Bring at most 5 examples to a calibration meeting
  • Do not name moderators in the report unless the lead asks

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Violation categories
  • Number of examples per meeting (default 5)
  • Review day
  • Whether moderators are named
  • Guideline source

What keeps you in control

It always asks you first

  • Lead approves the examples and every guideline change

Hard limits

  • Never change a moderation decision itself
  • Treat the report as a tool for calibration, not discipline

It stops when

  • Done: Differences are explained or addressed in calibration
  • Stop: Too few cases to compare, so the agent waits for the next week

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensIn one week, 9 hostile-tone posts get 4 removals, 3 warnings and 2 no-actions. Two of the no-actions involve authors with no history and the same wording as removed posts. The agent picks 3 examples and suggests clarifying the line 'hostile tone toward members'. The lead approves. Next week, 7 similar cases get 6 consistent outcomes.

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