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@nedyrov: statistics and cleanliness index

Boring channel Nedyrov

Lifehacks about AI automation. Связь тут @Alek_support_bot

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Grade D some metrics deviate cleanliness index
data from 2026-11-06
Subscribers
3,305
Median views
5,560
ERR
168.2%
Posts sampled
40
Niche Computer science
Post language Russian
Channel age 2 years

Data from 2026-11-06 — fresh.

Assessment summary

Personal blog about AI automation: the author walks through his own setups with neural networks, vibe coding, bug bounty and also talks about trips along the way — long texts with screenshots of dashboards and interfaces, all in Russian; the channel is two years old.

Posts get more views than there are subscribers: ERR 168% versus 40.7% for similar catalog channels, and this holds across half the feed, not one viral post. Reactions are low — 0.36% of views versus 0.49% for most similar channels, about 11% of recent message numbers are missing, and the last post was 6 days ago, so how many people will see an ad is hard to say in advance.

About the channel

Personal blog by the author about AI automation: he shows his own setups with neural networks, vibe coding, bug bounty and also talks about trips around California. Format — long text breakdowns with screenshots of dashboards, interfaces and stats, all in Russian. The channel is two years and two months old.

In the catalog, channels about neural networks for business sit nearby: @neuralforbusiness, @ai_to_business and @n2d2ai — all are larger, and a post is seen by a larger share of subscribers than for each of them. With @by_miracles and @it_business_idea the channel is comparable in size, and the share of subscribers who see a post is also higher.

What it publishes:

  • AI model breakdowns: price and result comparisons, for example a model for $0.13 versus Claude for $8.
  • His own pipelines: how to build an investor database on LinkedIn or filter YouTube through Gemini.
  • Bug bounty and agents: reports on runs of a fleet of AI agents with stats screenshots.
  • Trips and personal: notes from a cruise around California, vacation plans.

Posts come out more often in the evening and on weekdays, about 0.7 posts per day, with pauses. By subscribers the channel is in the bottom third of the “Computer technology” niche. They write with long texts, breakdowns and screenshots; there were no ads in the sample.

By subscribers, it ranks #86 of 102 channels in the Computer science niche of the catalog.

What to pay attention to

More views than subscribers: ERR ≈ 168%

Median views are noticeably higher than the subscriber count — across half the posts, not just one viral post. This happens when posts spread beyond the channel through reposts, chats or external traffic, but the other metrics do not support this idea.

What grade D means

The index is clearly lowered: one or more metrics fall outside usual values. The “How the assessment was produced” section shows which ones.

Compared with similar channels

Compared with 15 Computer science catalog channels whose metrics look normal. They are a similar size: 1,273 to 9,261 subscribers.

ERR (reach) higher than 15 of 15
@nedyrov 168.2%
similar channels median 40.7%
Reactions per 100 views lower than 11 of 15
@nedyrov 0.36
similar channels median 0.49

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

Scroll horizontally to see the full charts.

Views by post

The latest 40 posts with views, from Sep 5 to Oct 31. The dashed line is the median (5,560).

05.4K11KSep 5: 6,644 viewsSep 5: 7,076 viewsSep 7: 9,368 viewsSep 8: 8,800 viewsSep 8: 10,098 viewsSep 9: 10,754 viewsSep 14: 7,699 viewsSep 14: 8,290 viewsSep 14: 8,707 viewsSep 18: 7,905 viewsSep 22: 6,085 viewsSep 22: 6,648 viewsSep 22: 7,368 viewsSep 26: 4,442 viewsSep 26: 4,274 viewsSep 28: 2,987 viewsSep 28: 3,728 viewsSep 28: 3,435 viewsSep 29: 3,099 viewsSep 29: 4,227 viewsSep 29: 4,324 viewsSep 29: 6,209 viewsSep 29: 7,344 viewsOct 6: 3,806 viewsOct 6: 4,465 viewsOct 6: 5,540 viewsOct 7: 6,956 viewsOct 8: 5,528 viewsOct 10: 4,084 viewsOct 10: 4,640 viewsOct 11: 5,197 viewsOct 11: 4,610 viewsOct 11: 5,175 viewsOct 11: 5,419 viewsOct 14: 5,580 viewsOct 17: 4,898 viewsOct 17: 5,800 viewsOct 20: 8,756 viewsOct 26: 6,945 viewsOct 31: 3,959 views Sep 5Oct 31
  • post views
  • median 5,560

Maximum: 10,754 views. Data as of Nov 6.

What scoring found in the view pattern

More views than subscribers: ERR ≈ 168%

Median views are noticeably higher than the subscriber count — across half the posts, not just one viral post. This happens when posts spread beyond the channel through reposts, chats or external traffic, but the other metrics do not support this idea.

What could not be calculated

View build-up not assessed: there were no posts newer than one day.

Cleanliness-index history

3 checks for this channel.

050100Sep 19: index 50, grade DSep 19Oct 6: index 50, grade DOct 6Nov 6: index 50, grade DNov 6

Advertising outlook

Advertising placement: questionable.

Some of the channel's metrics deviate, so it is hard to say in advance how many people will see an ad.

About 4,000–5,269 people will see your post in the first 48 hours.

Few recent posts, so this is a rough forecast.

Reach of advertising posts

Too few advertising posts to compare: 1.

Without an ad label: 1 post.

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 @nedyrov

What does the 50/100 purity index for @nedyrov mean?

This is grade D, the “there are deviations” level: some metrics stand out from the usual picture. The higher the index, the fewer deviations.

Why does the channel have more views than subscribers?

Median views are 5,560 with 3,305 subscribers, ERR about 168%. Where these views come from is not visible from the check data.

Should I advertise here?

Placement is marked as questionable. The reason is a 50/100 purity index with deviations in metrics, so it is hard to say in advance how many people will see an ad.

How the assessment was produced

Data source
Public Telegram data: posts, views, reactions, and channel metadata.
Date or snapshot
2026-11-06
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 @nedyrov assessment dated 2026-11-06 uses 40 recent public posts. At that snapshot the channel had 3,305 subscribers, median post views were 5,560, ERR was 168.2%, and the cleanliness index was 50/100.
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/obsessed_with_ai.