Transparency

How the score works — and what it can’t tell you

A category full of black-box “checkers” owes creators an honest explanation. Here is exactly how Shadowban Checker reaches its estimate, and where that estimate stops.

Updated September 13, 2026

What data we read

Shadowban Checker reads only your own public video metrics through TikTok’s official API, with your permission: views, likes, comments, shares, captions and timestamps, plus basic profile info. It is read-only — no posting, no messages, no other accounts, no private data. We don’t sell your data or use it for advertising.

The signals we compute

We compare your recent videos against your own history and look for the patterns that limited reach tends to leave in the data:

  • Reach vs. baseline. A robust baseline (median-based, using a median/MAD approach) describes your normal range, so a single outlier post doesn’t distort it. A drop counts when it’s a drop for you.
  • Engagement-rate inversion. Engagement holding steady or rising while reach collapses suggests distribution is the issue, not the content.
  • Reach cliffs. A sudden step-down sustained across several posts is weighted more heavily than one quiet video.
  • Risky hashtags. Patterns in your own captions associated with reduced recommendation are flagged, not asserted as bans.

These combine into a single 0–100 visibility-risk score with the contributing signals shown alongside it.

What the score can’t tell you (the honest part)

  • It’s an estimate, not a verdict. TikTok never confirms a “shadowban,” so no tool can read one. Shadowban Checker measures outcomes (your reach and engagement) and infers backward.
  • Low views aren’t proof. TikTok says a video with few views may simply have weak engagement rather than being ineligible for the For You feed. We hedge accordingly.
  • We can’t see TikTok’s internal decisions. There is no API that reports “this account is limited.” Your own account status and analytics are the closest thing to a source of truth.
  • Reach naturally fluctuates. A trend across several posts is meaningful; a single video is noise.

Why we publish this

Many “checkers” hand you a confident yes/no and invent durations or banned-hashtag lists. We think a visibility tool for a compliance-sensitive topic should show its work and its limits. If you want the underlying background, read what a TikTok shadowban really is and our glossary.

FAQ

Frequently asked questions

How accurate is Shadowban Checker?

Shadowban Checker gives an evidence-based estimate of visibility risk from your own data — not a certainty. TikTok doesn’t publish or confirm a “shadowban,” so no tool can be “accurate” about an official status that doesn’t exist. We’re transparent that the score summarizes signals, and we hedge where TikTok has no official position.

Does a high score mean I’m definitely shadowbanned?

No. A high visibility-risk score means several signals in your own data point to limited distribution and it’s worth investigating — starting with your TikTok analytics and account status. It is not proof, and TikTok issues no such verdict.

What data does Shadowban Checker store and can I delete it?

Shadowban Checker reads your own public video stats read-only to compute your score. You can disconnect access anytime from your TikTok settings; see our privacy policy for details on data handling.

See your own signals

Run the read-only check and see exactly which signals fire.

Run a free visibility check

Sources

Every factual claim above is drawn from these primary sources. Where TikTok has no official statement, the text says so and stays hedged.