"""Model SAFE conversions into priced rounds."""
from __future__ import annotations
from datetime import datetime, timezone
from typing import Any
TOOL_META: dict[str, Any] = {
"name": "safe_note_converter",
"description": "Calculates SAFE conversion price, shares, and founder dilution.",
"inputSchema": {
"type": "object",
"properties": {
"safe_amt": {"type": "number"},
"valuation_cap": {"type": "number"},
"discount_pct": {"type": "number", "default": 20.0},
"mfn": {"type": "boolean", "default": False},
"next_round_pre_money": {"type": "number"},
"next_round_pps": {"type": "number"},
"pre_money_safe": {"type": "boolean", "default": False},
},
"required": [
"safe_amt",
"valuation_cap",
"next_round_pre_money",
"next_round_pps",
],
},
"outputSchema": {
"type": "object",
"properties": {
"status": {"type": "string"},
"data": {"type": "object"},
"timestamp": {"type": "string"},
},
},
}
def safe_note_converter(
safe_amt: float,
valuation_cap: float,
discount_pct: float | None = 20.0,
mfn: bool = False,
next_round_pre_money: float = 0,
next_round_pps: float = 0,
pre_money_safe: bool = False,
**_: Any,
) -> dict[str, Any]:
"""Return SAFE conversion economics."""
try:
if safe_amt <= 0 or valuation_cap <= 0 or next_round_pps <= 0:
raise ValueError("SAFE amount, valuation cap, and PPS must be positive")
discount_pct = discount_pct or 0
cap_price = valuation_cap / max(next_round_pre_money / next_round_pps, 1e-6)
discount_price = next_round_pps * (1 - discount_pct / 100)
conversion_price = min(cap_price, discount_price)
method_used = "cap" if conversion_price == cap_price else "discount"
shares = int(safe_amt / max(conversion_price, 1e-6))
effective_valuation = shares * next_round_pps
dilution = safe_amt / (next_round_pre_money + safe_amt) * 100 if pre_money_safe else safe_amt / (next_round_pre_money + safe_amt) * 100
ownership_pct = shares * next_round_pps / max(next_round_pre_money + safe_amt, 1e-6) * 100
if mfn:
method_used += "_mfn"
data = {
"conversion_price": round(conversion_price, 4),
"shares_issued": shares,
"effective_valuation": round(effective_valuation, 2),
"method_used": method_used,
"dilution_to_founders_pct": round(dilution, 4),
"ownership_pct": round(ownership_pct, 4),
}
return {
"status": "success",
"data": data,
"timestamp": datetime.now(timezone.utc).isoformat(),
}
except Exception as exc:
_log_lesson("safe_note_converter", str(exc))
return {
"status": "error",
"data": {"error": str(exc)},
"timestamp": datetime.now(timezone.utc).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")
