The usual dump scenario works like this: a team sells tokens cheap to insiders — VCs, angels, KOLs — who wait for retail to push the price up, then exit. By the time you're buying, there's already a profitable stack sitting above you.
We don't do pre-sales. No cheap tokens to insiders, no allocation to people who need an exit. We may distribute small amounts for marketing purposes — but these are not the kind of positions sized to move markets or create exit pressure. Everyone taking a real position in $GMYLD gets in at the same price — from DEX, at open market rate. There's no hidden stack positioned above yours waiting for you to provide liquidity.
The market operations allocation exists specifically to sell into speculative buying — not to dump, but to build liquidity on top of people trying to flip the token. When speculators push price up, the protocol captures that and adds it back as liquidity depth. This is what the Net Stake price is built on.
Net Stake is the number of tokens that are staked, minus what's been released as yield, minus what's been burned. It represents the real committed supply — the tokens that are actually locked in the protocol with skin in the game.
The protocol uses Net Stake to calculate an implied floor price: total liquidity value divided by net staked tokens. We commit to not selling below that price from the market operations fund.
The team earns from the protocol fee on every daily pot. That's the primary model. If we need additional runway for development or liquidity, we may sell from the market operations allocation — but only above the Net Stake price, never below it.
This is disclosed upfront rather than buried in a vesting schedule. You won't wake up to a surprise team dump.
You can exit. You're not locked in. But if you exit while the token price is above what you originally staked at, the Reference Cost system means you don't get to leave at the current market price — you get back closer to your entry value. The upside stays in the protocol to protect people who remain staked.
What you actually lose by leaving early is loyalty score and the compounding benefits that come with it — higher yield release rates, priority in future seasons, access to perks that accumulate over time. The penalty for leaving isn't a fee. It's opportunity cost.
Then you get loyalty accumulation and nothing else. No daily pot share, no yield release from game mechanics. The protocol doesn't punish you for being passive but it doesn't reward it either.
Loyalty is the incentive to improve your yield and your chances. Yield is the incentive to show up.
Loyalty doesn't reset just because you didn't qualify in a given season. As long as your stake stays in, your score carries. Missing a season hurts your streak but doesn't wipe your history. You don't get punished for a bad month.
Two things. First, daily pot size scales — when we see the maximum possible release being hit consistently, the pot doubles. Whales eating everything actually accelerates that growth for everyone, including future seasons.
Second, if we see extraction becoming one-sided and leaving nothing on the table, we have the ability to switch distribution to fair pro-rata — everyone gets a share proportional to their stake. That's a governance lever we're not afraid to use.
Unclaimed value rolls into the next season's reserve. It doesn't go to the team, it doesn't disappear. Low participation actually increases the expected value for whoever does show up.
Two ways. First, stakers can't exit at the current market price if it's above their Reference Cost — this kills the incentive to stake purely to flip a rising token.
Second, the protocol actively sells from the liquidity fund into speculative buying, which puts a ceiling on the kind of price spike that makes quick exits attractive in the first place. We're trying to make speculation a losing strategy structurally, not just through warnings.
| Bucket | Tokens | % | Purpose |
|---|---|---|---|
| Rewards Reserve | 80,000,000 | 80% | Season budgets, daily pots, game rewards |
| Liquidity Pairing | 10,000,000 | 10% | Paired with USDC, protocol-owned LP |
| Market Ops | 10,000,000 | 10% | Collect USDC during demand spikes |
| Term | Definition |
|---|---|
| Season Fund | The season's total reward budget, drawn from the Rewards Reserve |
| Daily Pot | The maximum reward amount that can be distributed on a given day |
| Eligible wallet | A wallet meeting the minimum stake requirement that has not been removed |
| Loyalty | A per-wallet, per-game stake stability score that improves earning potential |
| Module | A game that implements the GMYLD protocol framework |
| Reference Cost | Your blended entry price used for exit fairness calculations |
| Burn leverage | Burning tokens to produce the same release effect as staking a much larger amount |
| Protocol share | A percentage taken from every reward release, defined per game module |
| Reward distribution mode | The method a game uses to split the Daily Pot among players |
| Protocol-support path | A predefined destination for protocol revenue (liquidity, season runway, etc.) |
Every decision in GMYLD reduces to an observable state and a set of actions: monitor pot size, evaluate participation levels, assess risk of entry, decide when to stake more or hold. These are exactly the kinds of loops agents are built for. An agent with wallet access can maintain a staking position, protect loyalty streaks across seasons, time entries into daily pots based on participation levels and pot size, and manage in-game spending across module economies — items, upgrades, and mechanics that affect yield release — without any human intervention.
It's also worth noting that agents don't need human direction to participate here. A sufficiently configured agent can discover the protocol, evaluate the mechanics, enter a season, and manage a position from start to finish without a human ever touching the interface. The games are designed for people, but nothing about them requires one.
In-game economies across GMYLD modules will also include items, upgrades, and spending mechanics. Agents are ideal consumers of these — they can optimize spend-to-yield ratios in ways human players rarely do consistently, making them natural participants in the deeper layers of each module's economy.
One of the more interesting dynamics we're building toward is the signal layer. A human player with a strong seasonal performance history becomes a signal worth observing — an agent can mirror that strategy, or use it as one input in a broader model. A high-performing agent becomes a delegation target — a human with capital but limited time to play can instruct an agent to participate on their behalf, collect yield, manage loyalty, and report back.
This creates a two-way market: experienced human players gain value as data sources. Consistent agents become infrastructure for passive participants who want yield exposure without active management. Neither replaces the other — they coexist and amplify each other's value. People could follow agents the same way they follow traders — and agents could request access to human tactics the same way copy-trading platforms work today.
The honest target here is people who have funds and want yield but don't want to manage a daily game. Right now that person has two options: passive staking with shrinking APY, or sitting out entirely. With agent delegation, they get a third path — set a risk profile, point an agent at the protocol, and participate in active yield mechanics without touching the interface. The agent plays. The owner benefits. The protocol gets a participant who is consistent and capital-efficient.
AI agents already trade across CEXs and DEXs, take positions in prediction markets, follow on-chain signals, copy successful wallets, and manage yield portfolios. The tooling exists. What GMYLD offers is an active economic surface — not passive deposit mechanics, but real decisions with real stakes that benefit from intelligent, consistent play. That's a genuinely underserved niche for agents that already exist and are looking for more to do.
We plan to expose GMYLD's state and action surface in a format built for programmatic consumption — structured state feeds, action schemas, and a simulation environment for testing strategies against historical season data before deploying real capital. We're also planning an opt-in agent leaderboard: separate from human rankings, transparent, and visible to anyone tracking autonomous strategy performance across seasons.
The protocol works without any of this — human players from day one, no agent dependency. The agent layer is additive. But the fit between active yield mechanics and autonomous decision-making is real, and the market of agents looking for economic surfaces worth plugging into is underserved enough that we intend to be one of the answers.
| Capability | What It Means for Agents |
|---|---|
| Daily pot mechanics | Timed decision loops agents can optimise autonomously |
| Loyalty scoring | Long-horizon strategy agents can manage without fatigue |
| In-game economies | Spend-to-yield optimisation surfaces for agent consumers |
| Signal layer | Agents follow humans; humans delegate to agents |
| Agent leaderboard | Transparent performance tracking for autonomous strategies |
| Simulation mode | Backtest strategies before deploying real capital |
| # | Wallet | Yield Released |
|---|
| # | Wallet | Total Staked |
|---|
| # | Wallet | Current Streak |
|---|
| # | Wallet | GMYLD Burned |
|---|
| # | Wallet | Referral Yield |
|---|