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@GitHubRadar: statistics and cleanliness index

GitHub Radar

Реклама (впн не берем): @duft88 @whoisdan Размещение в канале платное, просьба писать только по сотрудничеству! Канал на Telega.in: https://telega.in/c/GitHubRadar РКН: https://clck.ru/3UKdMN

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Grade A+ metrics look normal cleanliness index
data from 2026-10-04
Subscribers
27,400
Median views
5,936
ERR
21.7%
Posts sampled
40
Niche Computer science
Post language Russian
Channel age 1 year

Data from 2026-10-04 — 4 days old.

Assessment summary

The channel publishes brief overviews of useful open-source projects, libraries, and utilities for developers.

The audience is noticeably more engaged than most peers: ERR is 21.7% versus 10.0% for similar catalog channels, and views grow synchronously with the subscriber base. At a pace of more than 6 posts per day, publications quickly get pushed up the feed, so most of the reach is generated in the first few hours after release.

What grade A+ means

The metrics agree with each other: views and reactions are distributed as usual, and almost no signals lower the index.

Compared with similar channels

Compared with 29 Computer science catalog channels whose metrics look normal. They are a similar size: 11,340 to 81,995 subscribers.

ERR (reach) higher than 23 of 29
@GitHubRadar 21.7%
similar channels median 10%
Reactions per 100 views lower than 14 of 27
@GitHubRadar 0.36
similar channels median 0.38

This is not a niche norm: only catalog channels are included. A high ERR is not always a plus: if the other metrics do not support it, the index goes down.

Dynamics and anomalies

Views by post

The latest 40 posts with views, from Sep 27 to Oct 4. The dashed line is the median (5,936).

03.3K6.6KSep 27: 6,431 viewsSep 27: 6,437 viewsSep 28: 6,624 viewsSep 28: 6,397 viewsSep 28: 6,538 viewsSep 28: 6,343 viewsSep 28: 6,269 viewsSep 28: 6,141 viewsSep 29: 6,129 viewsSep 29: 6,167 viewsSep 29: 6,150 viewsSep 29: 6,291 viewsSep 29: 6,263 viewsSep 29: 6,368 viewsSep 30: 6,258 viewsSep 30: 6,245 viewsSep 30: 6,038 viewsSep 30: 5,995 viewsSep 30: 5,790 viewsOct 1: 5,782 viewsOct 1: 5,911 viewsOct 1: 5,880 viewsOct 1: 5,962 viewsOct 1: 6,123 viewsOct 1: 5,896 viewsOct 1: 5,718 viewsOct 2: 5,633 viewsOct 2: 5,504 viewsOct 2: 5,229 viewsOct 2: 5,172 viewsOct 2: 5,221 viewsOct 2: 5,076 viewsOct 3: 4,712 viewsOct 3: 4,591 viewsOct 3: 4,498 viewsOct 3: 4,361 viewsOct 3: 3,939 viewsOct 3: 3,483 viewsOct 4: 3,111 viewsOct 4: 1,751 views Sep 27Oct 4
  • post views
  • 5 posts newer than one day and still gaining views
  • median 5,936

Maximum: 6,624 views. Data as of Oct 4.

What could not be calculated

View build-up not assessed: the channel posts often, and every post is newer than a week.

Cleanliness-index history

3 checks for this channel.

050100Jun 14: index 99, grade A+Jun 14Sep 8: index 50, grade DSep 8Oct 4: index 99, grade A+Oct 4

Advertising outlook

Advertising placement: reasonable.

About 3,711–4,894 people will see your post in the first 48 hours.

Reach of advertising posts

Too few advertising posts to compare: 2. 1 more are too fresh.

Without an ad label: 2 posts.

Buy advertising

Telegram ads are sold on these marketplaces — they have channel catalogs, prices, and checkout.

We don't sell ads. This channel may not be listed there.

Where to buy advertising

Affiliate links: we get a commission. It never affects the channel's score.

Questions about @GitHubRadar

Are there any anomalies in @GitHubRadar's metrics?

The channel's Integrity Index is 99 out of 100 (grade A+, "metrics normal" level). No suspicious findings were detected, the view variation is natural, and reach is steadily growing alongside the audience.

What return and reach can be expected from a publication?

Median views remain at 5.9 thousand with an ERR of 21.7%, which is more than double the median of similar channels in the catalog (10.0%).

Is advertising in this channel justified?

Advertising placement is considered justified. The primary practical limitation is the high posting frequency (about 6 per day), so for ads, it is critical to arrange the time interval before the next post in advance.

How the assessment was produced

Data source
Public Telegram data: posts, views, reactions, and channel metadata.
Date or snapshot
2026-10-04
Sample
The latest 40 public posts available at check time.
Calculation method
TG Inspector calculates metrics from the saved snapshot and combines independent signals into a deterministic 0–100 cleanliness index.
Factual result
The @GitHubRadar assessment dated 2026-10-04 uses 40 recent public posts. At that snapshot the channel had 27,400 subscribers, median post views were 5,936, ERR was 21.7%, and the cleanliness index was 99/100.
Limitations
This is a probabilistic assessment based on public data: it describes metrics, not the owner's actions, and is not a real-time measurement.

Full methodology and interpretation rules

This automated assessment is probabilistic: it describes the channel's public metrics, not its owner's actions. The index and grade are calculated from public data and are not changed on request. Channel owners can request removal of the page — t.me/TGinspector_ru.