Distribution is a chain of probabilities.

The published code rewards predicted actions with very different force—and punishes predicted negative feedback heavily. Here is what creators can responsibly infer from that.

August 13, 2026 · a389166 Independent educational project Based on open source

Published default weights

Like-farming is weak.

A like’s default weight is 0.5. Copy-link is 20.0. For the same change in predicted probability, that is a 40-fold difference.

View source on GitHub
These are probability weights—not points for observed likes, replies, or reports. Do not compare one action event to another.
Same probability delta · different contribution
Copy link
+20.0
Eligible mutual reply
+20.0
Quote
+5.0
Share via DM
+5.0
Follow author
+4.0
Favorite / like
+0.5
Block author
-31.2
Not interested
-43.2
Mute author
-58.8
Report
-234.0
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Evidence → implication

What the code can responsibly suggest.

Each recommendation keeps the published fact separate from interpretation. None is a guaranteed growth tactic.

01

Make something worth carrying elsewhere.

Published code fact

Copy-link has a 20.0 default weight; share via DM and quote each have 5.0; favorite has 0.5.

Open lines
Practical implication

Useful references, surprising evidence, reusable tools, and clear ideas are more aligned with the published hierarchy than asking for likes.

02

Create a real reason to discuss—not a reply trap.

Published code fact

Reply is 5.0. For an eligible mutual-follow original candidate, the 15.0 boost makes its effective reply weight 20.0.

Open lines
Practical implication

A specific question, defensible position, or useful unfinished edge can invite substance. Manufactured outrage also raises negative-feedback risk.

03

Give people a reason to follow the author.

Published code fact

Follow-author has a 4.0 default weight—8 times favorite’s 0.5 for the same predicted-probability change.

Open lines
Practical implication

A coherent body of work and a clear promise of future value matter more than a one-off like request.

04

Do not flood one slate with yourself.

Published code fact

Repeated-author multipliers begin 1, 0.625, 0.4375, 0.34375 under the published defaults.

Open lines
Practical implication

Closely clustered candidates from the same author can compete against a progressive discount. More posts do not translate linearly into more distribution.

05

Freshness is an eligibility gate, not a small decay.

Published code fact

The maximum post age constant is 48 hours; older candidates leave the published path before ranking.

Open lines
Practical implication

Evergreen quality can still be valuable to people, but this open For You candidate path does not keep scoring the same post indefinitely.

06

Protect against regret signals.

Published code fact

Report, mute, not-interested, and block carry default weights of -234, -58.8, -43.2, and -31.2.

Open lines
Practical implication

Misleading, repetitive, hostile, or bait-heavy work may win shallow reactions while increasing the probability of much heavier negative contributions.

Evidence boundary

What this guide refuses to invent.

Absence from this reviewed slice is not proof that a factor never matters anywhere. It is a reason not to present folklore as published code.

Hashtag recipes
No reviewed scorer rule here establishes an ideal hashtag count.
Magic posting times
The published path shows a 48-hour cutoff, not a universal best hour.
Premium multipliers
No Premium ranking multiplier is asserted by this reviewed snapshot.
Media always wins
Published media heads exist, but these files do not prove that every media post outranks text.

Before publishing

A code-derived quality check.

Would someone copy the link because the post remains useful outside the feed?
Is there a substantive reason to reply or quote—not only a bait prompt?
Does this make the author worth following for future work?
Could the framing cause regret, reports, mutes, blocks, or not-interested feedback?
Am I treating the simulator as an explanation rather than a reach prediction?