Bootcamp inactivity signals that surface risk early.
Keep education groups, bootcamps, and time-boxed cohorts active with transparent inactivity tracking. No message access. No privileged intents.
"We don't want to stress or lose anyone."
What you’re optimizing for
- Ensuring students are keeping up with the course material.
- Spotting drop-offs early so TAs can intervene.
Common pain points
- Silent students who are struggling but invisible.
- Manual attendance tracking via spreadsheets.
Standard Setup Preset
Select Education / Bootcamp / Course Cohort during /start.
Core Behavior
- Operating Mode
- Standard (Public warnings enabled)
- Timeline (Fast Paced)
-
Warning 7 days (~1w)Mark Inactive 14 days (~2w)Kick Eligible 28 days (~4w)
- Auto-kick
- Off
Signals & Actions
- Activity Signals (ON)
- Messages, reactions, voice, interactions, typing, threads, rsvps, cta_button.
- Engagement
- Polls (2 days), CTA Button ON.
-
@engaged (7d)
@top participant (21d)
(Rewards are muted by default to reduce noise)
Suggested Channels & Roles
Why CleanerBot fits this use case
In a 12-week bootcamp, missing 2 weeks is critical. CleanerBot provides the early warning system your teaching team needs to reach out before a student drops out completely.
Fast feedback loops for cohort health
Bootcamps and courses run on short cycles. Early signals are more important than late enforcement. CleanerBot is configured here for bootcamps and course cohorts that need bootcamp inactivity signals which surface risk early.
The education preset defaults are intentionally short, and it fully resets decay on activity. That combination is designed for teaching teams: you care most about quick detection and fast recovery, not slow decay math.
The target group analysis highlights that education spaces are sensitive to fairness and clarity. Keep the language supportive, focus on “getting back on track,” and let staff review edge cases instead of automating removals.
Teaching-team workflow
- Route items into an attendance review channel.
- Check flagged learners before live sessions.
- Treat warnings as nudges, not punishments.
Why the defaults fit
- Short warnings reduce silent dropouts.
- Reset-on-activity is easy to explain.
- Muted announcements reduce pressure.
Related reading: inactivity policy template, auto-kick guardrails.
Common Questions
Can I make it strict?
Yes. This preset is designed for fast-paced environments. The "Decay Reset" is enabled, meaning any valid activity fully resets the student's decay score to zero immediately.
What about instructors?
Simply add the @Instructor or @TA roles to the "Exempt Roles" list during setup or via /config.
Are quizzes supported?
Yes! The automated polls include quiz-style questions which are great for quick knowledge checks that also count as activity.
Can we separate multiple cohorts?
Yes. The cleanest approach is one server per cohort. If you must share a server, use cohort-specific roles and exemptions so alumni are not flagged during the active course cycle.
What is the right review cadence for teaching teams?
Two short reviews per week works well for most bootcamps and course cohorts. It is frequent enough to surface risk early without turning staff review into daily overhead.
Should we enable auto-kick during a live course?
Generally no. Use the review queue to trigger outreach first, then decide on removals case by case. If you ever move toward automation, align on safeguards in auto-kick guardrails.
Invite CleanerBot, run /start, and publish a short, transparent inactivity policy in your rules channel with the Inactivity Policy Template.
Moving away from Discord Prune? Read the Discord Prune vs CleanerBot Comparison.