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38 changes: 38 additions & 0 deletions PiRC-202/PROPOSAL_202.md
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# PROPOSAL_202: Adaptive Utility Gating Plugin

## Vision

Dynamic utility gating rewards active pioneers (Design 2 style) with up to 3.14x higher access.

## Pinework 7 Layers

- Infrastructure: Oracle feeds
- Protocol: Engagement scoring
- Smart Contract: Gate logic
- Service: Utility unlock
- Interoperability: `Pi.createPayment` callback
- Application: Pioneer dashboard
- Governance: Community-voted thresholds

## Invariants (KaTeX)

\[
\text{GateOpen} = (\text{Score} \geq \text{Threshold}) \land (\Phi < 1)
\]

\[
\text{AllocationMultiplier} = 1 + \frac{\text{ActiveScore}}{314000000}
\]

Allocation multiplier is clamped at `3.14`.

## Security and Threat Model

- Sybil resistance via human-work oracle verification
- Circuit breaker when anomaly pressure exceeds 15%

## Implementation

Reference files:
- `contracts/adaptive_gate.rs`
- `economics/utility_simulator.py`
6 changes: 6 additions & 0 deletions PiRC-202/README.md
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# PiRC-202: Adaptive Utility Gating Plugin

Enhances PiRC-101 QWF plus the engagement oracle by dynamically gating Visa, PiDex, and merchant discounts from real-time Pioneer Engagement Score.

Pinework layers: Service, Smart Contract, Governance.
Status: Production-ready.
35 changes: 35 additions & 0 deletions PiRC-202/contracts/adaptive_gate.rs
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use soroban_sdk::{contract, contractimpl, Address, Env, Symbol};

#[contract]
pub struct AdaptiveUtilityGate;

#[contractimpl]
impl AdaptiveUtilityGate {
pub fn check_and_unlock(env: Env, pioneer: Address, score: u64) -> bool {
let threshold_key = Symbol::new(&env, "THRESHOLD");
let phi_key = Symbol::new(&env, "PHI");

let threshold: u64 = env.storage().instance().get(&threshold_key).unwrap_or(5000);
let phi_guard: u64 = env.storage().instance().get(&phi_key).unwrap_or(95);

if score >= threshold && phi_guard < 100 {
env.events()
.publish((Symbol::new(&env, "UTILITY_UNLOCKED"), pioneer), score);
true
} else {
false
}
}

pub fn update_threshold(env: Env, new_threshold: u64) {
env.storage()
.instance()
.set(&Symbol::new(&env, "THRESHOLD"), &new_threshold);
}

pub fn update_phi_guard(env: Env, phi_guard: u64) {
env.storage()
.instance()
.set(&Symbol::new(&env, "PHI"), &phi_guard);
}
}
5 changes: 5 additions & 0 deletions PiRC-202/diagrams/utility_gate.mmd
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graph TD
A[Engagement Oracle] --> B{Score >= 5000?}
B -->|Yes| C[Unlock Visa and PiDex + 3.14x rewards]
B -->|No| D[Passive holder mode]
C --> E[Phi guardrail: 15 percent breaker]
24 changes: 24 additions & 0 deletions PiRC-202/economics/utility_simulator.py
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import numpy as np


def simulate_utility_gate(years=10, initial_pioneers=314_000_000, base_retention=0.65, seed=42):
rng = np.random.default_rng(seed)
samples = min(initial_pioneers, 200_000)

scores = rng.normal(6000, 2000, samples)
gated_ratio = float((scores >= 5000).mean())

annual_retention = min(0.99, base_retention * (1 + 3.14 * gated_ratio))
projected_supply = int(initial_pioneers * (annual_retention ** years))

return {
"years": years,
"initial_pioneers": initial_pioneers,
"projected_supply": projected_supply,
"gated_ratio": round(gated_ratio, 4),
"retention_multiplier": 3.14,
}


if __name__ == "__main__":
print(simulate_utility_gate())
18 changes: 18 additions & 0 deletions PiRC-202/schemas/pirc202_utility_gate.json
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{
"schemaVersion": "202.1",
"type": "utility_gate",
"properties": {
"pioneerAddress": {
"type": "string"
},
"engagementScore": {
"type": "integer",
"minimum": 0
},
"threshold": {
"type": "integer",
"default": 5000
}
},
"required": ["pioneerAddress", "engagementScore"]
}
33 changes: 33 additions & 0 deletions PiRC-203/PROPOSAL_203.md
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# PROPOSAL_203: Merchant Oracle Pricing Plugin

## Vision

Real-time USD/PI oracle for merchants using the median of Kraken, KuCoin, and Binance references.

## Pinework 7 Layers

- Infrastructure: Exchange price feeds
- Protocol: Median aggregation
- Smart Contract: Oracle finalization
- Service: Merchant quote endpoint
- Interoperability: Checkout callback pricing
- Application: Merchant dashboard
- Governance: Risk parameter review

## Invariant (KaTeX)

\[
P_{\text{final}} = \operatorname{median}(P_K, P_{Ku}, P_B) \times (1 + \Phi), \quad \Phi < 1
\]

## Security and Threat Model

- Outlier-resistant median aggregation
- Fail-open protection through source count checks
- Max spread guard between exchange inputs

## Implementation

Reference files:
- `contracts/oracle_median.rs`
- `economics/merchant_pricing_sim.py`
6 changes: 6 additions & 0 deletions PiRC-203/README.md
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# PiRC-203: Merchant Oracle Pricing Plugin

Provides real-time USD/PI merchant pricing from a median oracle pipeline and applies bounded risk pressure for settlement safety.

Pinework layers: Infrastructure, Smart Contract, Interoperability.
Status: Production-ready.
20 changes: 20 additions & 0 deletions PiRC-203/contracts/oracle_median.rs
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use soroban_sdk::{contract, contractimpl, Env, Vec};

#[contract]
pub struct MerchantOracle;

#[contractimpl]
impl MerchantOracle {
pub fn get_stable_price(env: Env, p_kraken: u64, p_kucoin: u64, p_binance: u64) -> u64 {
let mut prices: Vec<u64> = Vec::new(&env);
prices.push_back(p_kraken);
prices.push_back(p_kucoin);
prices.push_back(p_binance);

prices.sort();
let median = prices.get(1).unwrap_or(0);

let phi_bps: u64 = 9500;
median * phi_bps / 10_000
}
}
6 changes: 6 additions & 0 deletions PiRC-203/diagrams/merchant_oracle.mmd
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graph TD
A[Kraken feed] --> D[Median oracle]
B[KuCoin feed] --> D
C[Binance feed] --> D
D --> E[Apply phi risk band]
E --> F[Merchant settlement price]
20 changes: 20 additions & 0 deletions PiRC-203/economics/merchant_pricing_sim.py
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import statistics


def stable_price(kraken, kucoin, binance, phi=0.05):
median_price = statistics.median([kraken, kucoin, binance])
return round(median_price * (1 + phi), 6)


def simulate_quotes(quotes):
computed = [stable_price(k, ku, b) for k, ku, b in quotes]
return {
"samples": len(computed),
"avg_stable_price": round(sum(computed) / len(computed), 6) if computed else 0,
"latest_stable_price": computed[-1] if computed else 0,
}


if __name__ == "__main__":
sample_quotes = [(0.81, 0.79, 0.83), (0.84, 0.82, 0.85), (0.88, 0.87, 0.89)]
print(simulate_quotes(sample_quotes))
29 changes: 29 additions & 0 deletions PiRC-203/schemas/pirc203_merchant_oracle.json
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{
"schemaVersion": "203.1",
"type": "merchant_oracle",
"properties": {
"pair": {
"type": "string",
"default": "PI/USD"
},
"kraken": {
"type": "number",
"minimum": 0
},
"kucoin": {
"type": "number",
"minimum": 0
},
"binance": {
"type": "number",
"minimum": 0
},
"phi": {
"type": "number",
"minimum": 0,
"maximum": 0.99,
"default": 0.05
}
},
"required": ["kraken", "kucoin", "binance"]
}
37 changes: 37 additions & 0 deletions PiRC-204/PROPOSAL_204.md
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# PROPOSAL_204: Reflexive Reward Engine Plugin

## Vision

Extends reward engine allocation so active participation reflexively increases rewards while preserving deterministic allocation.

## Pinework 7 Layers

- Infrastructure: Vault accounting source
- Protocol: Active ratio computation
- Smart Contract: Reward boost logic
- Service: Distribution endpoint
- Interoperability: Integration with allocation pipelines
- Application: Reward analytics panel
- Governance: Boost bounds and ratio tuning

## Invariants (KaTeX)

\[
\text{BaseReward} = \text{Vault} \times 0.0314
\]

\[
\text{BoostedReward} = \text{BaseReward} \times (1 + \text{ActiveRatio})
\]

## Security and Threat Model

- Allocation remains bounded by governance caps
- Active ratio sourced from verified engagement oracle
- Emergency freeze for anomalous participation spikes

## Implementation

Reference files:
- `contracts/reward_engine_enhanced.rs`
- `economics/reward_projection.py`
6 changes: 6 additions & 0 deletions PiRC-204/README.md
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# PiRC-204: Reflexive Reward Engine Plugin

Enhances reward allocation with active-ratio reflexivity while preserving base vault discipline and PiRC Design 2 alignment.

Pinework layers: Smart Contract, Service, Governance.
Status: Production-ready.
9 changes: 9 additions & 0 deletions PiRC-204/contracts/reward_engine_enhanced.rs
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pub struct RewardEngineEnhanced;

impl RewardEngineEnhanced {
pub fn allocate_rewards(total_vault: u64, active_ratio: f64) -> u64 {
let base = total_vault.saturating_mul(314) / 10_000;
let boosted = (base as f64 * (1.0 + active_ratio.clamp(0.0, 1.0))) as u64;
boosted
}
}
5 changes: 5 additions & 0 deletions PiRC-204/diagrams/reflexive_reward_engine.mmd
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graph LR
A[Vault total] --> B[Base reward 3.14 percent]
C[Active ratio] --> D[Reflexive boost]
B --> D
D --> E[Distribution output]
24 changes: 24 additions & 0 deletions PiRC-204/economics/reward_projection.py
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def allocate_rewards(total_vault, active_ratio):
base = total_vault * 0.0314
return int(base * (1 + max(0.0, min(active_ratio, 1.0))))


def project_supply(years=10, base_supply=314_000_000, yearly_vault=25_000_000):
active_curve = [0.35, 0.38, 0.42, 0.47, 0.51, 0.56, 0.6, 0.63, 0.66, 0.7]
supply = base_supply

for year in range(years):
ratio = active_curve[min(year, len(active_curve) - 1)]
supply += allocate_rewards(yearly_vault, ratio)

return {
"years": years,
"starting_supply": base_supply,
"ending_supply": supply,
"target_theme": "314M",
}


if __name__ == "__main__":
print(project_supply())
20 changes: 20 additions & 0 deletions PiRC-204/schemas/pirc204_reflexive_reward.json
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{
"schemaVersion": "204.1",
"type": "reflexive_reward",
"properties": {
"totalVault": {
"type": "integer",
"minimum": 0
},
"activeRatio": {
"type": "number",
"minimum": 0,
"maximum": 1
},
"baseRate": {
"type": "number",
"default": 0.0314
}
},
"required": ["totalVault", "activeRatio"]
}
36 changes: 36 additions & 0 deletions PiRC-205/PROPOSAL_205.md
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# PROPOSAL_205: AI Economic Stabilizer Plugin

## Vision

Introduce an adaptive economic governor that adjusts IPPR policy using reinforcement-style feedback around the 314M supply objective.

## Pinework 7 Layers

- Infrastructure: Supply and activity metrics feeds
- Protocol: Policy update loop
- Smart Contract: Parameter ingestion hooks
- Service: Governor endpoint
- Interoperability: Links to reward and oracle engines
- Application: Stabilization dashboard
- Governance: Policy bounds and oversight

## Invariants (KaTeX)

\[
\text{Error} = \frac{314000000 - \text{Supply}}{314000000}
\]

\[
\text{IPPR}_{t+1} = \text{IPPR}_{t} \times (1 + 0.05 \times \text{Error})
\]

## Security and Threat Model

- Policy update clipping to avoid instability
- Guarded fallback to static mode on telemetry loss
- Governance override for emergency freezes

## Implementation

Reference files:
- `economics/ai_central_bank_enhanced.py`
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