Simulation dossier TotoChain · year one plain-language read

One year of the chain, fast-forwarded.

Three documents describe a single test: simulate TotoChain's first twelve months — who joins, who gets rich, and where the tokens go — without waiting a real year. This page explains the test and what it found, in everyday language.

12
simulated months
9.68M
blocks produced
~43 min
to compute the year
30,209
users created by month 12

Almost every token is minted in the first months

share of cycle supply, by month

The supply schedule halves every month. Month 1 alone mints roughly half of an entire 13-month cycle, so by the end of year one the chain has already emitted about 98% of every TOTO it will ever make.

What you're looking at

Three documents, one experiment

The folder holds a design note, a raw run log, and a written forecast. Read together, they go from "here's what users can do" to "here's what actually happened when we ran it" to "here's what it means."

01 · The plan
user-activity-scenarios.md

Every move a user can make

An inventory: each button a user can press, every way tokens and reputation flow, five types of user (from lurkers to power users), and a menu of scenarios to simulate. It's the blueprint the test is built from.

02 · The run
year-one-numbers.md

The raw machine output

What the test actually printed, month by month: token supply, burns, user counts, handshakes, NFT submissions, and the richest accounts. Big honest tables of numbers, straight from the run.

03 · The meaning
year-one-projections.md

The plain-English forecast

A back-of-envelope projection that turns the run into a story: roughly how many users, how much money, where it pools, and eight headline takeaways for the team. Order-of-magnitude, not promises.

The test itself

What the simulation actually does

A single Rust test, bootstrap_max_simulation, plays the chain forward block by block. It runs in five stages: first the founding validators bootstrap the economy alone, then real users start arriving and living their lives on-chain.

1
Months 0–2

The 11 founders warm up the engine

Only the eleven launch validators exist. Each submits 10 NFTs a day and takes turns producing blocks. There are no ordinary users yet, so all the rewards pile up on the founders.

2
After the build-up

Mop-up with wildcards

One founder (init00) cashes in leftover NFT collections, using "wildcard" pieces to fill any gaps and turn incomplete sets into tokens.

3
One-time reset

Share the spendable money evenly

init00 splits its surplus spendable balance equally across all 11 founders. The locked-up portion stays where each one earned it — which is why, from here on, every validator's spendable balance is identical.

4
A quiet stretch

Idle, but still earning

Validators keep producing blocks and accumulating locked rewards while the chain waits for the user phase to begin.

5
Rest of the year

The public arrives

Every day, 20–200 new accounts appear. Each rolls dice for who referred them, whether they'll do identity "handshakes," whether they'll get an ID attestation, and how often (if ever) they'll create NFTs. This is the busy, realistic part of the year.

S0
Referrals

Users invite users, building a referral tree many layers deep — not just under validators.

S4a
Handshakes

Two people confirm each other; each completed handshake grants both a big reputation boost.

S4b
Attestations

An issuer vouches for a user's identity (Email, Gmail, Govt-ID) — each ID type is worth different reputation.

S3
NFT submissions

Users with enough reputation send NFTs to the reward pool, then try to reassemble and cash in collections.

S2
Voting

One proposal a week; eligible users vote. The result nudges their voting reputation up or down.

How the economy works

The rules of the money

TotoChain has two balances: ordinary spendable tokens and locked potential (a stake that pays fees and slowly burns away). Every block mints new tokens, every day burns some, and reputation decides who's allowed to play.

Minting: 20 / 80

Every block, fresh tokens are split. The block's author keeps 20% right away as locked potential. The other 80% is set aside to trickle down their referral tree to "descendants" over the coming blocks.

20% author80% to descendants

Burning: the lurker tax

Each day, every account loses about 1/28 (~3.6%) of its locked potential to the reward pool. Sit still for a year and roughly 99% of it evaporates. Only people actively earning keep meaningful balances.

The reputation gate

To submit NFTs you need 100,000 reputation. Two ways in: one handshake (worth ~1M) or one attestation (an Email check alone clears it). This gate is what separates active citizens from passive holders.

The forecast

What the first year looked like

The projection's eight headline takeaways, condensed. Green points to things that grow; ember points to things that shrink or drain.

People
~33,000 join · ~14,000 qualify

About a third of all sign-ups never touch the chain at all. Of those who do, roughly 42% earn enough reputation to fully participate.

Creators
~5.4% submit NFTs

Only about 1,800 people ever submit NFTs — around 860 a day. The daily cap of 100 per account is never close to being hit.

Emission
~98% of all TOTO

Because the supply schedule halves monthly, nearly the entire token supply that will ever exist is minted in year one — heavily front-loaded into the first weeks.

Wealth
Validators dominate

During the user-free months the founders capture nearly all the minted tokens. They finish the year as by far the wealthiest accounts on the chain.

Burn
~99% lost / year

Locked potential held by inactive accounts is almost entirely burned away within a year. The economics actively punish sitting still.

On-ramp
Attestations lead

In theory, ID attestations are the main route past the reputation gate — reaching about three times more people than handshakes. (See the caveat below: in the recorded run they didn't fire.)

Collectibles
~1M pieces · ~10K wildcards

NFT submissions create about a million fractional pieces and ten thousand wildcards — comfortably under the one-million wildcard ceiling, for now.

Governance
~−45 per vote

Voting is a slow reputation drain by design: a winning vote earns +10, a losing one costs −100. With coin-flip outcomes, the average voter ends the year slightly negative.

Reading the run log

Watching it month by month

Two forces pull against each other all year. New users keep arriving, while the locked tokens already on the chain keep burning down. These curves come straight from the recorded run.

Users keep climbing
Total accounts created, month 1 → 12
A founder's locked stake burns down
init00 locked potential, log scale, month 1 → 12

How to read the big table in year-one-numbers.md

MonthSupplyHow many new tokens were available to mint that month — halves each row.
Cum.mint / Cum.burnRunning totals of everything minted and everything burned so far.
Submits / fNFTsNFT submissions and the fractional pieces they produced.
LiveNWLive networks — the active collections in flight.
init00.bal / .lockedThe lead founder's total balance and the locked-potential slice of it (the part that burns).
Eager / WildcardClaimsCollections cashed in immediately vs. those completed later using wildcards.

Honest limits

Read the fine print

The forecast is a model, and the recorded run doesn't match it on every point. These gaps are worth knowing before quoting any number.

Attestations didn't fire in this run

The forecast leans on ID attestations as the main on-ramp. But in the recorded log, every attestation failed — 0 completed, more than 10,000 errors. So in practice the reputation gate was crossed only through handshakes. That's a real gap between the prediction and the run, and a good thing to chase down.

The NFT trade-and-cash-in loop stayed idle

The recorded run shows 0 trades and 0 unlocks; collections just piled up (over 3,600 waiting by month 12). The "second wave of wealth" from users reassembling and cashing in collections was never actually exercised.

Simulated time isn't production time

Production uses 28-day months and 3-second blocks. The fast test mode compresses time, which roughly triples the daily burn rate and reshapes emission — so timing-sensitive figures are illustrative, not exact.

Everything is order-of-magnitude

User inflow, referrer mix, handshake and attestation rates are all assumptions. Change them and the headline numbers move — the projection includes a sensitivity table showing exactly how much.