"""Track inflation versus deflation regimes for Snowdrop tokens."""
from __future__ import annotations
from datetime import datetime, timedelta, timezone
from typing import Any
TOOL_META: dict[str, Any] = {
"name": "inflation_deflation_tracker",
"description": "Computes inflation rates and estimates deflation crossover dates.",
"inputSchema": {
"type": "object",
"properties": {
"supply_snapshots": {"type": "array", "items": {"type": "object"}},
"burn_rate_daily": {"type": "number"},
"mint_rate_daily": {"type": "number"},
},
"required": ["supply_snapshots", "burn_rate_daily", "mint_rate_daily"],
},
"outputSchema": {
"type": "object",
"properties": {
"status": {"type": "string"},
"data": {"type": "object"},
"timestamp": {"type": "string"},
},
},
}
def inflation_deflation_tracker(
supply_snapshots: list[dict[str, Any]],
burn_rate_daily: float,
mint_rate_daily: float,
**_: Any,
) -> dict[str, Any]:
"""Return inflation metrics and regime classification."""
try:
if not supply_snapshots:
raise ValueError("supply_snapshots required")
if burn_rate_daily < 0 or mint_rate_daily < 0:
raise ValueError("Rates must be non-negative")
ordered = sorted(supply_snapshots, key=lambda snap: snap["date"])
first = ordered[0]
last = ordered[-1]
start_supply = float(first.get("circulating_supply", 0))
end_supply = float(last.get("circulating_supply", 0))
if start_supply <= 0:
raise ValueError("Starting supply must be positive")
start_date = datetime.fromisoformat(first["date"].replace("Z", "+00:00"))
end_date = datetime.fromisoformat(last["date"].replace("Z", "+00:00"))
days = max((end_date - start_date).days, 1)
nominal_growth = (end_supply - start_supply) / start_supply
annualized = (1 + nominal_growth) ** (365 / days) - 1
annual_inflation_pct = round(annualized * 100, 4)
regime = "stable"
if mint_rate_daily > burn_rate_daily:
regime = "inflationary"
elif mint_rate_daily < burn_rate_daily:
regime = "deflationary"
deflation_crossover = _estimate_deflation_cross(
last,
burn_rate_daily,
mint_rate_daily,
)
data = {
"annual_inflation_pct": annual_inflation_pct,
"regime": regime,
"deflation_crossover_date": deflation_crossover,
}
return {
"status": "success",
"data": data,
"timestamp": datetime.now(timezone.utc).isoformat(),
}
except Exception as exc:
_log_lesson("inflation_deflation_tracker", str(exc))
return {
"status": "error",
"data": {"error": str(exc)},
"timestamp": datetime.now(timezone.utc).isoformat(),
}
def _estimate_deflation_cross(
last_snapshot: dict[str, Any],
burn_rate_daily: float,
mint_rate_daily: float,
) -> str | None:
last_date = datetime.fromisoformat(last_snapshot["date"].replace("Z", "+00:00"))
total_supply = float(last_snapshot.get("total_supply", last_snapshot.get("circulating_supply", 0)))
circulating = float(last_snapshot.get("circulating_supply", 0))
if burn_rate_daily <= mint_rate_daily:
return None
net_burn = burn_rate_daily - mint_rate_daily
buffer = max(total_supply - circulating, 0)
if net_burn == 0:
return None
days_to_cross = buffer / net_burn if net_burn else 0
crossover_date = last_date + timedelta(days=days_to_cross)
return crossover_date.isoformat()
def _log_lesson(skill_name: str, error: str) -> None:
with open("logs/lessons.md", "a", encoding="utf-8") as handle:
handle.write(f"- [{datetime.now(timezone.utc).isoformat()}] {skill_name}: {error}\n")
