RMFU Desk
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Case studies

Deployment narratives

Anonymized composites: how groups retire fragmented bookmark bars and anchor a morning loop before adding modules. For analytical depth on desk operations and platform design, see Insights.

Three-minute mental model

RMFU is one surface for reading (brief + pulse), remembering (library + drills), and stress-testing (risk, macro, scenarios). Sign in to reach your tenant desk; this public site is the story, not the datastore.

Open the full guided tour → (recommended instead of this short blurb).

Use Open desk when you already have access — you will authenticate at the gate like any other protected route.

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Live calculators vs. marketing

After sign-in, /tools hosts shareable one-page calculators (NPV, payback, Kelly, and more). This public tools hub explains what exists for crawlers and prospects.

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Why drills matter

Bookmarks decay. RMFU uses short, spaced repetitions so vocabulary and frameworks stay retrievable when you are in front of a committee or a live tape — not only when you are reading alone.

Nudge inputs

Edit fields, then Apply & refresh (or use ↻ on the card). Same payload as the public demo API.

Last response JSON

app/engines/tools/service.py

Leading lines of the real module (marketing excerpt).

"""Operator pocket tools — small pure functions used by /tools.

Each function returns a dict with the inputs echoed back, the result, and a
short interpretation sentence (in casual exec tone).
"""
from __future__ import annotations

from dataclasses import dataclass
import math
from typing import Iterable


# -------- IRR / NPV ---------------------------------------------------------

def npv(rate: float, cashflows: list[float]) -> float:
    return sum(cf / ((1 + rate) ** t) for t, cf in enumerate(cashflows))


def npv_rate_sensitivity(rate: float, cashflows: list[float], bump: float = 0.01) -> dict:
    """±bump hurdle NPV and approximate $ / 1% change in NPV (last period scale)."""
    base = npv(rate, cashflows)
    up = npv(rate + bump, cashflows)