Labeler: nsfwlabeler1.bsky.social (did:plc:czkszof2pfy3ke23vulzdjii)

Generated by labelwatch

Overview | Census

This is a labeler service. It publishes labels about posts and accounts on the Bluesky network.

Insufficient volume: no events observed in the last 7 days.

0

Events (7d)

0/0

Targets/Events

0

Anomalies

Activity (7d)

Silent volume Warming up

Observed <24h · 122 scans · Warmup

Warming up

Baselines forming — behavior axes not yet available.

Labeler

nsfwlabeler1.bsky.social
did:plc:czkszof2pfy3ke23vulzdjii

Classification

Declared declared

Reachability

unknown

Auditability

medium

Class

third_party

First seen

10 Jul 2026, 11:20 PM UTC

Last seen

11 Jul 2026, 2:26 AM UTC

Events (24h)

0

Events (7d)

0 Silent volume

Targets (7d)

0

Subjects (7d)

0

Alerts

0

Links

Open on Bluesky · PLC directory

Why classified this way

Reason: declared+not_probed

Classifier version: v1

Classified at: 2026-07-11T02:26:28.006941Z

Evidence surfaces

declared_record: true (2026-07-11T02:26:28.006941Z)

declared_record: true (2026-07-10T23:26:09.338990Z)

declared_record: true (2026-07-10T23:20:32.015968Z)

Probe history

No probe history recorded yet.

Alerts timeline

id	rule_id	ts

Methods and caveats

What is a labeler? A third-party service that publishes tags (labels) about Bluesky posts or accounts. Clients choose which labelers to subscribe to and how to interpret labels (ignore / warn / hide).
This site observes labeler behavior only. No content analysis, no user profiling, no moderation actions.
Rules detect geometric patterns (rate anomalies, target distribution, churn). Thresholds are configurable.
Every alert includes a receipted hash over rule_id, config, inputs, and evidence for reproducibility.
Sparklines show hourly event counts over 7 days. Badges summarize which rules fired in the period.
Observation surface: label events from com.atproto.label.queryLabels and labeler declarations from com.atproto.sync.listReposByCollection. Does not observe content, profiles, or social graph.
Classification is based on structured evidence from multiple surfaces (registry declaration, DID document, endpoint probing, observed label activity). Each labeler page includes a "Why classified this way" expander with full evidence.