Agent skill

Condition Setup

Set up conditions for PINA problems. An agent skill from PINA-org/PINA.

Install Condition Setup

skills CLI

$ npx skills add PINA-org/PINA --skill condition-setup -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI

$ gh skill install PINA-org/PINA condition-setup --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy

$ git clone --depth 1 https://github.com/PINA-org/PINA.git skills-src && mkdir -p .claude/skills && cp -r skills-src/.opencode/skills/condition-setup .claude/skills/condition-setup && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Paste into Claude Code

Install the "condition-setup" agent skill from https://github.com/PINA-org/PINA/tree/master/.opencode/skills/condition-setup into .claude/skills/condition-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "condition-setup", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/PINA-org/PINA/tree/master/.opencode/skills/condition-setup

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add PINA-org/PINA --skill condition-setup -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install PINA-org/PINA condition-setup --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/PINA-org/PINA.git skills-src && mkdir -p .agents/skills && cp -r skills-src/.opencode/skills/condition-setup .agents/skills/condition-setup && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "condition-setup" agent skill from https://github.com/PINA-org/PINA/tree/master/.opencode/skills/condition-setup into .agents/skills/condition-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "condition-setup", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add PINA-org/PINA --skill condition-setup -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install PINA-org/PINA condition-setup --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/PINA-org/PINA.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/.opencode/skills/condition-setup .cursor/skills/condition-setup && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "condition-setup" agent skill from https://github.com/PINA-org/PINA/tree/master/.opencode/skills/condition-setup into .cursor/skills/condition-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "condition-setup", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/PINA-org/PINA.git --path .opencode/skills/condition-setup

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add PINA-org/PINA --skill condition-setup -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install PINA-org/PINA condition-setup --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/PINA-org/PINA.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/.opencode/skills/condition-setup .gemini/skills/condition-setup && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "condition-setup" agent skill from https://github.com/PINA-org/PINA/tree/master/.opencode/skills/condition-setup into .gemini/skills/condition-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "condition-setup", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install PINA-org/PINA condition-setup

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add PINA-org/PINA --skill condition-setup -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/PINA-org/PINA.git skills-src && mkdir -p .github/skills && cp -r skills-src/.opencode/skills/condition-setup .github/skills/condition-setup && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "condition-setup" agent skill from https://github.com/PINA-org/PINA/tree/master/.opencode/skills/condition-setup into .github/skills/condition-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "condition-setup", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add PINA-org/PINA --skill condition-setup -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install PINA-org/PINA condition-setup --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/PINA-org/PINA.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/.opencode/skills/condition-setup .opencode/skills/condition-setup && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "condition-setup" agent skill from https://github.com/PINA-org/PINA/tree/master/.opencode/skills/condition-setup into .opencode/skills/condition-setup/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "condition-setup", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: condition-setup
GitHub stars: 797
Token cost: ~1k tokens
SKILL.md length: 281 words
Files: 1
Skills in repo: 10
Repo updated: Oct 6, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Set up conditions for PINA problems. An agent skill from PINA-org/PINA.

Works in 4 steps: Determine the condition type → Data types (data-driven only) → Build conditions → …
Tasks that involve Forecasting and time series
SKILL.md covers Step 1 — Determine the…, Step 2 — Data types…, Step 3 — Build conditions and Step 4 — Integrate with the…, plus 1 more section
Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md

What it does

Condition Setup is an agent skill from PINA-org/PINA. Set up conditions for PINA problems. Covers data types (LabelTensor, Graph, PyG Data), time series conditions, binding equations to domains, and data-driven input→target mapping.

Its SKILL.md is about 1k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts. Compatibility notes: opencode, codex, claude

It sits in Data & Analytics, covering Forecasting and time series and Deep learning. It works with PyTorch. The repository describes itself as: Physics-Informed Neural networks for Advanced modeling. The licence is MIT.

When your agent uses it

Tasks that involve Forecasting and time series
Tasks that involve Deep learning

Example prompts

“/condition-setup”

Requirements

Python 3
Compatibility (from SKILL.md): opencode, codex, claude

Workflow steps

4 steps, taken from the step headings in SKILL.md.

Determine the condition type
Data types (data-driven only)
Build conditions
Integrate with the problem class

What it can do on your machine

Read from SKILL.md and the folder at commit 0cd8afb. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
No scripts in the folder and no shell commands in SKILL.md (its code samples are python).
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Credentials
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Compatibility
opencode, codex, claude
From compatibility in the SKILL.md frontmatter.

Context cost

Condition Setup loads about 1k tokens when it runs. Until then it costs about 49 tokens; SKILL.md has 281 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~49
When it runs · the whole SKILL.md, loaded when a task matches: ~1k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from PINA-org/PINA at commit 0cd8afb, republished under its MIT licence (© PINA-org). 281 words, ~1,049 tokens.

Download SKILL.mdSave it as .claude/skills/condition-setup/SKILL.md (or your agent's skills folder).

name: condition-setup
description: Set up conditions for PINA problems. Covers data types (LabelTensor, Graph, PyG Data), time series conditions, binding equations to domains, and data-driven input→target mapping.
compatibility: opencode, codex, claude
license: MIT
metadata.audience: users
metadata.workflow: problem-creation

Set Up Conditions for a PINA Problem

[!IMPORTANT] Read RULES.md before using this skill — it applies to all skills. This is a sub-skill of create-problem. Load the entry-point skill first.

Use this skill to define Condition objects that bind data, equations, or time-series windows to the problem.

Step 1 — Determine the condition type

Three kinds of conditions exist in PINA:

Kind	When to use
Physics-on-domain	PDE/ODE residual on a sampled domain
Data-driven	Input→target mapping (supervised)
Time series	Rolling-window forecasting

Step 2 — Data types (data-driven only)

If the problem is data-driven, ask:

What data type are you using?

Available data types for Condition(input=..., target=...):

LabelTensor / torch.Tensor — standard tensor data (most common)
Graph — PINA's built-in graph structure (from pina import Graph)
Data — PyTorch Geometric Data object (from torch_geometric.data import Data)

All three types are accepted directly as input/target.

Step 3 — Build conditions

Physics-on-domain

Conditions map domain names (sampled later via discretise_domain) or explicit point tensors to equations:

python

from pina import Condition

# Option 1: reference a domain by name (sampled later)
conditions = {
    "boundary": Condition(domain="boundary", equation=FixedValue(0.0)),
    "interior": Condition(domain="D", equation=Equation(my_pde)),
}

# Option 2: provide explicit points
conditions = {
    "data_pde": Condition(input=points_tensor, equation=Equation(my_pde)),
}

Data-driven (supervised)

python

conditions = {
    "data": Condition(input=input_tensor, target=target_tensor),
}

Time series forecasting

If the user has time series data, ask whether they want standard supervised or time-series conditions:

python

from pina import Condition

# Standard supervised
Condition(input=ts_tensor, target=target_tensor)

# Time series (input is 3D: [batch, n_windows, features])
Condition(
    input=ts_tensor,
    n_windows=10,
    unroll_length=5,
    randomize=True,
)

# Graph time series
Condition(
    input=graph_ts_data,
    n_windows=10,
    unroll_length=5,
    key="some_key",
)

Parameters:

n_windows — number of rolling windows
unroll_length — prediction horizon per window
randomize — shuffle window order
key — key for graph time series data

Step 4 — Integrate with the problem class

Conditions become a class-level dict on the problem:

python

class MyProblem(SpatialProblem):
    output_variables = ["u"]
    spatial_domain = CartesianDomain({"x": [0, 1]})

    domains = {
        "D": spatial_domain,
        "boundary": spatial_domain.partial(),
    }

    conditions = {
        "boundary": Condition(domain="boundary", equation=FixedValue(0.0)),
        "D": Condition(domain="D", equation=Equation(my_pde)),
    }

Checklist

For data-driven: confirmed data type (LabelTensor, torch.Tensor, Graph, or PyG Data)
For data-driven: input_variables is a list[str] naming the inputs
For time series: n_windows, unroll_length, and optional key are set correctly
Each Condition uses valid keyword arguments:
- Condition(domain=..., equation=...) for physics-on-domain
- Condition(input=..., equation=...) for physics-on-points
- Condition(input=..., target=...) for data-driven
- Condition(input=..., n_windows=..., unroll_length=...) for time series
domains dict has an entry for every domain name used in conditions

Files

Just SKILL.md in .opencode/skills/condition-setup of PINA-org/PINA.

Open the folder on GitHubat commit 0cd8afb

Compare with similar skills

Condition Setup next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Condition Setup compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Condition Setup this skillPINA-org/PINA	797	—	~1k	Automated safety check: Pass	MIT	yesterday
Gitnexus Refresh On StaleML4ITS/TimeVQVAE	166	—	~264	Automated safety check: Pass	MIT	7 mo ago
Uv Pypi PublishML4ITS/TimeVQVAE	166	—	~178	Automated safety check: Pass	MIT	7 mo ago
Physicsnemo DiscoverNVIDIA/skills	3.5k	—	~1.8k	Automated safety check: Pass	Apache-2.0	today
ML EngineerRightNow-AI/openfang	18k	—	~987	Automated safety check: Pass	Apache-2.0	3 mo ago
ML Model Trainingsecondsky/claude-skills	227	1 repos	~1.7k	Automated safety check: Pass	MIT	10 days ago

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Questions about Condition Setup

What does Condition Setup do?

Set up conditions for PINA problems. An agent skill from PINA-org/PINA. Condition Setup is an agent skill from PINA-org/PINA. Set up conditions for PINA problems.

When should I use Condition Setup?

Condition Setup fits situations like: tasks that involve Forecasting and time series; tasks that involve Deep learning.

How do I install Condition Setup in Claude Code?

Run `npx skills add PINA-org/PINA --skill condition-setup -a claude-code`. Or copy the skill folder (.opencode/skills/condition-setup in PINA-org/PINA) into .claude/skills/condition-setup in your project. Claude Code loads it when a task matches its description.

How do I install Condition Setup in Codex?

Run `npx skills add PINA-org/PINA --skill condition-setup -a codex`. Or copy the skill folder (.opencode/skills/condition-setup in PINA-org/PINA) into .agents/skills/condition-setup in your project. Codex loads it when a task matches its description.

Can I use Condition Setup in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add PINA-org/PINA --skill condition-setup -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/condition-setup, .gemini/skills/condition-setup, .github/skills/condition-setup and .opencode/skills/condition-setup in your project.

What does Condition Setup need to run?

SKILL.md names no scripts, command-line tools or credentials: Condition Setup is instructions for the agent only. Our summary lists: Python 3. Compatibility (from SKILL.md): opencode, codex, claude.

Does Condition Setup access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Condition Setup safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Condition Setup use?

Condition Setup is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Condition Setup use?

About 1k tokens (SKILL.md is roughly 4.2k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Condition Setup?

Skills that share tags, products or a category with Condition Setup: Gitnexus Refresh On Stale (ML4ITS/TimeVQVAE, 166 stars), Uv Pypi Publish (ML4ITS/TimeVQVAE, 166 stars), Physicsnemo Discover (NVIDIA/skills, 3.5k stars) and ML Engineer (RightNow-AI/openfang, 18k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Condition Setup?

PINA-org (a GitHub organization) maintains it in PINA-org/PINA, which has 797 GitHub stars. The repository holds 10 skills in this directory. The repository was last updated on October 6, 2026.

Source: PINA-org/PINA on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.

Install Condition Setup

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

Workflow steps

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Compatibility

Context cost

Safety

SKILL.md

Set Up Conditions for a PINA Problem

Step 1 — Determine the condition type

Step 2 — Data types (data-driven only)

Step 3 — Build conditions

Physics-on-domain

Data-driven (supervised)

Time series forecasting

Step 4 — Integrate with the problem class

Checklist

Files

Compare with similar skills

Similar skills

More from PINA-org/PINA

Related

Questions about Condition Setup