What is SolvingMicroDSOPs AGENTS.md?

Repository instructions for SolvingMicroDSOPs, a set of economics lecture notes and code about how households choose spending and saving under uncertainty.

Use them to navigate the LaTeX book, Python or Stata replication code, Jupyter notebook, figures, tables, and test suite.

They explain where the main document, equations, figures, replication code, notebook, and tests are located before an agent edits or builds the project.

How llorracc/SolvingMicroDSOPs configures Codex and OpenCode

Reuse

Borrowing it

Nothing to install: this file belongs to llorracc/SolvingMicroDSOPs. Take a copy, put it at the same path in your own repository, and replace the rules that are about this project with yours.

Copy the file

curl -O https://raw.githubusercontent.com/llorracc/SolvingMicroDSOPs/master/AGENTS.md

Clone the repo

git clone --depth 1 https://github.com/llorracc/SolvingMicroDSOPs

Made for: Codex, OpenCode.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

README.md

[![agentmods](https://agentmods.dev/badge/instructions/llorracc/solvingmicrodsops/agents-md/github.svg)](https://agentmods.dev/instructions/llorracc/solvingmicrodsops/agents-md)

Your own site

<a href="https://agentmods.dev/instructions/llorracc/solvingmicrodsops/agents-md"><img src="https://agentmods.dev/badge/instructions/llorracc/solvingmicrodsops/agents-md/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

Your own site · 80×15

<a href="https://agentmods.dev/instructions/llorracc/solvingmicrodsops/agents-md"><img src="https://agentmods.dev/badge/instructions/llorracc/solvingmicrodsops/agents-md.svg" alt="Reviewed on agentmods" width="80" height="20"></a>

Per session 783 This file is loaded in full into every session.

When invoked 783 The same file — it is already loaded in full.

Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.

Origin original No closer match found in the catalogue.

Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

Model	Per session	Once invoked
Fable 5.1	$0.00783	$0.00783
Opus 5.5	$0.00313	$0.00313
Sonnet 5.5	$0.00157	$0.00157
Haiku 4.5	$0.00078	$0.00078

Measured 2mo ago against content hash f272be187cb0, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

SolvingMicroDSOPs AGENTS.md scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2mo ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

AGENTS.md · 49 lines

How it starts

The opening of the file, as written. The whole thing — 49 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md — Orientation for AI-Assisted Work

This repository contains SolvingMicroDSOPs: LaTeX lecture notes plus replication code (Python, Stata) for numerical methods in consumption/saving problems under uncertainty. The main artifact is the book PDF built from root-level .tex files.

The document teaches how to solve consumption-saving problems efficiently, progressing from brute-force value function iteration through the transformation trick (inverse marginal value), the Endogenous Grid Method (EGM), and a modular stage architecture for composing complex periods. It concludes with structural estimation matching model predictions to Survey of Consumer Finances data.

Quick orientation

Path	Purpose
`SolvingMicroDSOPs.tex`	Main document entry
`_sectn-*.tex`	Section subfiles
`Equations/`	Equation fragments (included by main doc)
`Tables/`, `Figures/`	Tables and figures
`Code/Python/`, `Code/Stata/`	Replication code
`Code/Python/tests/`	Test suite (pytest)
`SolvingMicroDSOPs.ipynb`	Jupyter notebook implementing the methods
`prompts/`	Canonical prompts for AI-assisted work
`@resources/`, `@local/`	LaTeX search path and macros (needed for build)
`CONTRIBUTION.md`	What this document contributes, audience, HARK comparison
`ROADMAP.md`	How to read this — suggested reading paths
`Notation.md`	Glossary of all mathematical notation and macros
`FIGURES.md`	Figure regeneration manifest (Python vs. legacy)
`.github/workflows/ci.yml`	CI pipeline (tests, notebook, lint)

What this document contributes

See CONTRIBUTION.md for a concise statement of what the document covers, who it is for, and how it relates to HARK and standard textbooks.

Critical rules

Matsya: When the user says to "ask Matsya" (or equivalent), show the full output that Matsya produces—do not replace it with a summary you construct.
docs/ is a reference copy. Do not edit it. All edits use root-level files only.
Build: latexmk on root .tex (uses LuaLaTeX via .latexmkrc)
Code mirrors math: Python identifiers parallel LaTeX macros (e.g. DiscFac ↔ \DiscFac, vEndPrd ↔ \vEndPrd)
verbatimwrite pattern: Many equation files in Equations/ are generated at compile time by \begin{verbatimwrite} blocks inside _sectn-*.tex files. Always edit the equation in the section file, not the generated .tex fragment in Equations/.

Read the full file on GitHub · 49 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

2mo ago First seen · 49 lines · 783 tokens per session scan A f272be187cb0

Subscribe to this mod's changes

SolvingMicroDSOPs AGENTS.md is an instructions file published in the GitHub repository llorracc/SolvingMicroDSOPs (22 stars, last pushed 8mo ago), licensed Apache-2.0. It adds 783 tokens to every session, about $0.0031 per session on Opus 5.5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

Learning and teaching

SolvingMicroDSOPs AGENTS.md next to 6 instructions from other repositories
Mod	Type	Stars	Last push	Licence	Scan	Tokens	Works with
SolvingMicroDSOPs AGENTS.mdllorracc/SolvingMicroDSOPs	Instructions file	22	8mo ago	Apache-2.0	A	783	Codex, OpenCode
vscode buildNext.instructions.mdmicrosoft/vscode	Instructions file	195k	today	MIT	A	9,719	GitHub Copilot
vscode oss-third-party-notices.instructions.mdmicrosoft/vscode	Instructions file	195k	today	MIT	A	5,516	GitHub Copilot
next.js AGENTS.mdvercel/next.js	Instructions file	143k	today	MIT	A	7,461	Codex, OpenCode
langchain AGENTS.mdlangchain-ai/langchain	Instructions file	149k	today	MIT	A	4,680	Codex, OpenCode
vscode copilot-instructions.mdmicrosoft/vscode	Instructions file	195k	today	MIT	A	3,093	GitHub Copilot
vscode model-prompts.instructions.mdmicrosoft/vscode	Instructions file	195k	today	MIT	A	2,022	GitHub Copilot

SolvingMicroDSOPs: Instructions file for Codex