Abaqus Output

CommunityPopular

Cai-aa

abaqus-output

Configure output requests - field outputs, history outputs. Use when user asks what results to save, output variables, reduce output file size, or history output.

Overview

Publisher	Cai-aa
Repository	`CAE-Agent-Hub`
Skill name	`abaqus-output`
Stars	1K
Forks	130
Bundled files	3
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
3 bundled files
Scripts, templates, and references the model can read while it works. Files are read-only and never executed.
Open source
Published by Cai-aa on GitHub. Read the source before you install it.

Installation

Install the Abaqus Output AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/Cai-aa/CAE-Agent-Hub/tree/main/Skill/abaqus/setup/abaqus-output
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/Cai-aa/CAE-Agent-Hub.git /tmp/CAE-Agent-Hub
mkdir -p .claude/skills
cp -r /tmp/CAE-Agent-Hub/Skill/abaqus/setup/abaqus-output .claude/skills/abaqus-output

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Abaqus Output in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Abaqus Output on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Abaqus Output is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Abaqus Output Skill

Configure what results to save from Abaqus analyses. Controls field outputs (full-field data for contour plots) and history outputs (time series at specific points).

When to Use This Skill

Route here when user mentions:

"What results should I save?" / "Output variables"
"Track displacement over time" / "History output"
"ODB file too large" / "Reduce output"
"Monitor a specific node"

Route elsewhere:

Extracting/reading results from ODB → /abaqus-odb
Running the analysis → /abaqus-job

Key Decisions

1. Field vs History Output

Type	Use For	Data Scope
Field Output	Contour plots, full-field visualization	All nodes/elements
History Output	Time series plots, monitoring	Specific points/regions

2. Common Output Variables

Variable	Description
S	Stress tensor (includes Mises)
U	Displacement
RF	Reaction forces
E	Total strain
PE, PEEQ	Plastic strain
V, A	Velocity, acceleration (dynamic)
NT, HFL	Temperature, heat flux (thermal)
CSTRESS, CDISP	Contact stress/displacement

3. Analysis-Specific Recommendations

Analysis Type	Essential Variables
Static	S, U, RF
Dynamic	S, U, V, A, RF, ENER
Thermal	NT, HFL, RFL
Contact	CSTRESS, CDISP, COPEN
Plastic	S, PE, PEEQ

4. Output Frequency

Scenario	Setting	Effect
Full detail	frequency=1	Every increment (large files)
Balanced	frequency=5-10	Every N increments
Space-saving	numIntervals=20	Fixed number of frames

What to Ask User

If unclear, ask:

What results do you need? Stress, displacement, reaction forces?
Track a specific point over time? → Need history output
Large model or long analysis? → May need reduced frequency

Workflow: Configuring Output

Step 1: Identify Needed Variables

Based on analysis type: Static needs S, U, RF minimum. Dynamic adds V, A, energy.

Step 2: Create Field Output Request

Required: Step name + variables tuple. Optional: frequency, region.

Step 3: Create History Output (if needed)

For time-series: Create node set at location, then HistoryOutputRequest with that region. Use component variables (U1, U2, U3).

Step 4: Manage File Size (large models)

Options: Reduce frequency, use numIntervals, limit variables, output to specific regions only.

Validation Checklist

Field output covers essential variables (S, U, RF)
History output region/set exists before referencing
Frequency appropriate for analysis length
Contact analysis has contact-specific outputs

Troubleshooting

Problem	Cause	Solution
"Variable not available"	Wrong element/analysis type	Check compatibility
ODB file too large	Too much output	Reduce frequency or variables
No history data	Bad region spec	Verify set exists

Code Patterns

For API syntax and code examples, see:

API Quick Reference
Common Patterns

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Abaqus Output AI skill do?

Configure output requests - field outputs, history outputs. Use when user asks what results to save, output variables, reduce output file size, or history output.

Why use Abaqus Output on TypingMind?

Because you install it once and use it with any model. Abaqus Output is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Abaqus Output in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Cai-aa/CAE-Agent-Hub/tree/main/Skill/abaqus/setup/abaqus-output. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Abaqus Output?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Abaqus Output?

As many as you like. As long as a model supports skills, you can use Abaqus Output with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Abaqus Output AI skill free?

Yes. It is published on GitHub by Cai-aa under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

Abaqus Output Skill

When to Use This Skill

Key Decisions

1. Field vs History Output

2. Common Output Variables

3. Analysis-Specific Recommendations

4. Output Frequency

What to Ask User

Workflow: Configuring Output

Step 1: Identify Needed Variables

Step 2: Create Field Output Request

Step 3: Create History Output (if needed)

Step 4: Manage File Size (large models)

Validation Checklist

Troubleshooting

Code Patterns

Bundled files

Frequently asked questions

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