AI agent skill​#

An AI coding agent can read and edit code and run tests with the tools you make available. PlantSimEngine provides an optional skill with instructions and executable examples for implementing process models and assembling simulations. A skill is a folder of instructions and examples that your agent can read while working.

You choose the scientific question, assumptions, references, and validation evidence. The agent can help turn those choices into code and check that the declared models connect as intended.

Set up the skill for your package version​#

Find the skill shipped with the PlantSimEngine version you actually use:

using PlantSimEngine

package_root = pkgdir(PlantSimEngine)
skill_root = joinpath(package_root, "skills", "plantsimengine")
(Base.pathof(PlantSimEngine), Base.pkgversion(PlantSimEngine), skill_root)

Copy or link that complete directory into your coding agent's skill directory, following its installation instructions. Keep its SKILL.md, references, assets, and scripts together. Use the copy from your installed package rather than the latest main branch: different versions can describe different APIs.

The skill uses the Julia tools available in your agent's environment. It does not require a particular editor or connector.

Ask it to assemble existing models​#

Adapt this request to the packages, data, and scientific question you have:

Use the PlantSimEngine skill shipped with my loaded package. I want to compare two existing models for the same process. First identify available alternatives and explain their inputs, outputs, units, and assumptions. Show what data each needs and flag anything that is missing. Build the smallest simulation that can compare them with the same input data. Explain their connections, run the tests, and show the results. Keep any required physical conversion explicit.

Useful inputs to provide are the package names, the process of interest, your input data and its units, and the outputs you want to compare. The Loaded model catalog and Model compatibility and replacement show the corresponding manual workflow.

Ask it to implement an equation​#

Provide the equation or source paper, definitions of the variables, parameter values and units, and at least one expected result:

Use the PlantSimEngine skill shipped with my loaded package to implement the equation and variable definitions I provide. Check whether an existing process already represents this question. Keep the equation readable and declare each input and output, including its units and physical meaning. Test one calculation against my reference result, then use the model in a simulation of one object. If any assumption, physical conversion, parameter, or validation criterion is unspecified, identify it before choosing one. Show the code, test results, and remaining scientific questions.

The basic model tutorial follows this sequence without an agent. For an existing implementation, also use Port an existing model.

Review what the agent returns​#

Expect a concrete result you can inspect:

• the loaded package path and version;

• the selected process and hypotheses, with the evidence supplied for them;

• readable model code and scenario configuration;

• checks that the required inputs are available, their units and meanings match, and the models receive values from the intended sources;

• tests actually run, their results, and any remaining limitations.

PlantSimEngine's Authoring reports describe models and compare interfaces. Diagnostics explains inputs, connections, timing, and execution. The reports show which information comes from the model author, which was found by examining the code, and which is missing. These checks help find implementation and coupling errors; scientific validation still needs suitable observations or reference results.

Check the packaged examples​#

The skill includes a minimal model, alternative hypotheses, a physical conversion model, coupling examples, and their tests. You or your agent can check the copy supplied by the installed package with:

include(joinpath(
    pkgdir(PlantSimEngine), "skills", "plantsimengine",
    "scripts", "check-examples.jl",
))

Use Model repository layout and tests when you are ready to organize your own reusable model package.