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pina-workflow

Orchestrates a complete session from problem definition through trained solver. This is the entry point for solving differential equations or physics problems with neural networks. Use when the user has a vague open-ended request like "I have a differential equation", "I want to solve a PDE", "I have a physics problem", "I need to model a system", "help me solve an ODE", "I want to use neural networks for my equations", "I have some data and equations", or "let's build physics-informed neural networks". Also triggers on mentions of specific equations (Navier-Stokes, Burgers, Poisson, heat equation, wave equation, etc.) or when the user describes a physical system they want to simulate. This skill will guide the user through the full workflow step by step, loading the right sub-skills at the right time.

Informations de source

Dépôt
PINA-org/PINA
Dernière activité de la source
17 juillet 2026 à 08:56
Langue détectée de SKILL.md
anglais
Étoiles
797
Forks
113

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Lisez SKILL.md et les fichiers associés affichés par SkillsMP avant de décider de l'installer.

Affichage de SKILL.md

SKILL.md
Instructions source · Aperçu en lecture seule
name
pina-workflow
description
Orchestrates a complete session from problem definition through trained solver. This is the entry point for solving differential equations or physics problems with neural networks. Use when the user has a vague open-ended request like "I have a differential equation", "I want to solve a PDE", "I have a physics problem", "I need to model a system", "help me solve an ODE", "I want to use neural networks for my equations", "I have some data and equations", or "let's build physics-informed neural networks". Also triggers on mentions of specific equations (Navier-Stokes, Burgers, Poisson, heat equation, wave equation, etc.) or when the user describes a physical system they want to simulate. This skill will guide the user through the full workflow step by step, loading the right sub-skills at the right time.
license
MIT
compatibility
opencode, codex, claude
metadata
{"audience":"users","workflow":"pina-workflow"}
# PINA Workflow — End-to-End Agentic Session > [!IMPORTANT] > Read [RULES.md](../RULES.md) before using this skill — it applies to all skills. Orchestrates a full PINA session. Does **not** duplicate sub-skill content — each stage below requires actually reading the referenced file(s) in full, not acting from memory, summary, or a prior pass over this conversation. ## Hard rule for every stage Before doing anything in a stage: 1. Read every file path listed for that stage, in full, with the `view` tool. 2. If a stage lists multiple sub-skills, read **all** of them — the list is mandatory, not illustrative. 3. Do not advance to the next stage until the current stage's checklist (below) is satisfied. 4. If you already read a file earlier in this session and the file hasn't changed, you may skip re-reading it — but only if you can state which stage/turn you read it in. If in doubt, re-read. ## Pipeline ``` Stage 1 — Problem definition → create-problem ├── Domain creation → define-domains ├── Equation definition → define-equations └── Condition binding → condition-setup Stage 2 — Model selection → select-model Stage 3 — Solver selection → select-solver Stage 4 — Trainer configuration → select-trainer ``` ## Stage 1 — Problem definition **Read `../create-problem/SKILL.md` in full now.** create-problem itself delegates to three sub-skills. Read all three in full, in this order, following whatever instructions create-problem gives for sequencing: - `../define-domains/SKILL.md` - `../define-equations/SKILL.md` - `../condition-setup/SKILL.md` **Exception:** if the user already has a working `problem` object, skip directly to Stage 2 — do not read Stage 1 files. **Stage 1 checklist (must all be true before moving on):** - [ ] create-problem read in full - [ ] define-domains read in full, domains defined - [ ] define-equations read in full, equations defined - [ ] condition-setup read in full, conditions bound - [ ] a `problem` object exists ## Stage 2 — Model selection **Read `../select-model/SKILL.md` in full now.** Input/output dimensions are known from the Stage 1 `problem` object — use them, don't re-derive or guess. **Stage 2 checklist:** - [ ] select-model read in full - [ ] model instantiated with correct input/output dims ## Stage 3 — Solver selection **Read `../select-solver/SKILL.md` in full now.** Check the condition types from the `problem` object (set in Stage 1) — they drive which solver is valid. Do not pick a solver without checking this. **Stage 3 checklist:** - [ ] select-solver read in full - [ ] condition types checked against solver requirements - [ ] solver instantiated ## Stage 4 — Trainer configuration **Read `../select-trainer/SKILL.md` in full now.** Verify all domains are discretised before configuring the trainer — if not, go back to define-domains, don't silently proceed. **Stage 4 checklist:** - [ ] select-trainer read in full - [ ] all domains confirmed discretised - [ ] trainer configured ## Stage 5 — Train The user runs `trainer.train()`. Offer to inspect results afterwards (forward pass, loss curves, discovered unknown parameters for inverse problems).
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