TulipaEnergyModel.jl: Instructions file for Codex

AGENTS.md

TulipaEnergyModel.jl AGENTS.md is an instructions file for Codex, OpenCode from TulipaEnergy/TulipaEnergyModel.jl. It costs 4,048 tokens per session, scanned A, original, Apache-2.0.

A project-specific instruction file for coding agents working on TulipaEnergyModel.jl, a Julia package for modeling and optimizing electric energy systems.

In plain words
What is it for?
Use it when an AI coding assistant needs guidance on the package structure, modeling pipeline, data handling, optimization solver, and contribution workflow.
Why use it?
It gives an agent the project's architecture, file layout, development rules, and performance requirements so its changes fit the existing codebase.

Instructions file for CodexOpenCode

Written for Codex and OpenCode: the file is AGENTS.md. Also seen: mentions Claude Code; mentions AGENTS.md.

This is TulipaEnergy/TulipaEnergyModel.jl's own configuration. It tells Codex and OpenCode how to work on TulipaEnergyModel.jl itself, so it is not a mod to install elsewhere. Copy it as a starting point and replace the rules that are about this project. Everything TulipaEnergyModel.jl configures →

Reuse

Borrowing it

Nothing to install: this file belongs to TulipaEnergy/TulipaEnergyModel.jl. 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/TulipaEnergy/TulipaEnergyModel.jl/main/AGENTS.md
Clone the repo
git clone --depth 1 https://github.com/TulipaEnergy/TulipaEnergyModel.jl

Made for: Codex, OpenCode.

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Per session 4,048 This file is loaded in full into every session.
When invoked 4,048 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.

ModelPer sessionOnce invoked
Fable 5.1 $0.04048 $0.04048
Opus 5 $0.02024 $0.02024
Sonnet 5 $0.00810 $0.00810
Haiku 4.5 $0.00405 $0.00405

Measured 5d ago against content hash 1b3507a666d6, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-09, from the pricing page.

Security

Grade A, and why

TulipaEnergyModel.jl 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 5d 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 · 349 lines

How it starts

The opening of the file, as written. The whole thing — 349 lines — stays where its author put it; the contents beside it link to each section on GitHub.

AGENTS.md

This file provides guidance to AI coding assistants working on TulipaEnergyModel.jl. It applies to any coding agent (for example, Copilot, Claude, or similar tools).

For full developer documentation, see docs/src/90-contributing/91-developer.md.

Architecture

Julia package for modeling and optimization of electric energy systems. Uses DuckDB for data handling, JuMP for optimization modeling, and HiGHS as the default solver. Part of the Tulipa ecosystem (TulipaIO, TulipaBuilder, TulipaClustering).

Source Structure

  • src/TulipaEnergyModel.jl — Main module; all using statements live here
  • src/structures.jl — Core types: EnergyProblem, TulipaVariable, TulipaConstraint, TulipaExpression
  • src/run-scenario.jl — High-level run_scenario entry point
  • src/create-model.jlcreate_model! / create_model
  • src/solve-model.jlsolve_model! / solve_model / save_solution!
  • src/objective.jl — Objective function construction
  • src/model-preparation.jl — Data massage before model creation
  • src/data-preparation.jlpopulate_with_defaults!
  • src/data-validation.jl — Input validation
  • src/io.jlcreate_internal_tables! / export_solution_to_csv_files
  • src/input-schemas.jl + src/input-schemas.json — Table schema definitions
  • src/solver-parameters.jl — Solver parameter handling
  • src/utils.jl — Utility functions
  • src/variables/ (7 files) — Variable creation (flows, investments, storage, etc.)
  • src/constraints/ (16 files) — Constraint creation (capacity, energy, transport, etc.)
  • src/expressions/ (3 files) — Expression creation (storage, intersection, multi-year)
  • src/rolling-horizon/ (4 files) — Rolling horizon implementation
  • src/sql/ (3 SQL files) — SQL templates for creating tables

Dynamic includes: The main module uses a loop to include all .jl files from variables/, constraints/, and expressions/ directories. New files added to these directories are automatically included.

Read the full file on GitHub · 349 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.

  1. 5d ago First seen · 349 lines · 4,048 tokens per session scan A 1b3507a666d6

Subscribe to this mod's changes

TulipaEnergyModel.jl AGENTS.md is an instructions file published in the GitHub repository TulipaEnergy/TulipaEnergyModel.jl (79 stars, last pushed yesterday), licensed Apache-2.0. It adds 4,048 tokens to every session, about $0.0202 per session on Opus 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 2026-09-04.

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