shikamaru

Provably correct day-count and accrued-interest calculations. A small, dependency-light TypeScript library and an MCP server, so an AI agent can get the exact number instead of guessing.

Why

LLMs are unreliable at date and money math: they pick the wrong day-count convention and miscompute accrued interest. shikamaru does it deterministically and proves it against published reference values. Do not let a model guess your interest accrual.

What it does (v1)

• Day-count fraction between two dates under six market conventions: 30/360, 30E/360, 30E/360 ISDA, ACT/360, ACT/365F, ACT/ACT ISDA.
• Simple accrued interest: notional x rate x day-count fraction.
• Exposed both as a library and as an MCP server (tools: day_count_fraction, accrued_interest, list_conventions).

Holiday calendars, business-day adjustment, schedules, and ACT/ACT ICMA arrive in v2.

Install

npm install @jayofemi/shikamaru

Library usage

import { dayCountFraction, accruedInterest } from "@jayofemi/shikamaru";

dayCountFraction("2003-11-01", "2004-05-01", "ACT/ACT ISDA"); // 0.4977...
accruedInterest({
	notional: 1_000_000,
	rate: 0.05,
	start: "2024-01-01",
	end: "2024-04-01",
	convention: "ACT/365F",
});

Dates are strict ISO YYYY-MM-DD. Rate is an annual decimal (0.05 = 5%).

MCP server

From source (local dev):

npm install
npm run build
node dist/server.js

Once published, an MCP client can launch it directly:

npx @jayofemi/shikamaru

Point any MCP client (Claude Desktop, an IDE, etc.) at that command over stdio.

Verify the MCP server

The standard way to test shikamaru's server is the official MCP Inspector. The unit tests cover the library; the Inspector covers the server layer they do not touch.

npm run build
npx @modelcontextprotocol/inspector node dist/server.js

It opens a local UI, connects over stdio, lists the tools, and lets you call them. Sanity check: day_count_fraction with start 2003-11-01, end 2004-05-01, convention ACT/ACT ISDA returns about 0.4977.

Correctness

Conventions follow the ISDA 2006 definitions. The test suite checks published reference vectors (ISDA worked examples, the OpenGamma conventions guide), property checks, and a differential battery against QuantLib, the de-facto reference.

To (re)generate the QuantLib battery (needs Python + pip):

pip install QuantLib
npm run vectors

This writes test/vectors/quantlib.json (commit it). npm test then checks shikamaru against every QuantLib value. CI regenerates the battery from QuantLib (setup-python + pip) and runs it on every push, so drift is caught. The proof is the product.

Develop

npm install
npm run build
npm test

License

MIT. Copyright (c) 2026 Jay Ofemi.