Scikit Learn
zLanqing/codex-claude-academic-skills
Machine learning in Python with scikit-learn. An agent skill from zLanqing/codex-claude-academic-skills.
Generate an Abaqus FEA training dataset for surrogate / ML models.
Install Abaqus Lhs Batch Dataset
$ npx skills add theneoai/awesome-skills --skill abaqus-lhs-batch-dataset -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install theneoai/awesome-skills abaqus-lhs-batch-dataset --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/theneoai/awesome-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset .claude/skills/abaqus-lhs-batch-dataset && rm -rf skills-srcUse ~/.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/
Install the "abaqus-lhs-batch-dataset" agent skill from https://github.com/theneoai/awesome-skills/tree/main/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset into .claude/skills/abaqus-lhs-batch-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abaqus-lhs-batch-dataset", 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 install https://github.com/theneoai/awesome-skills/tree/main/skills/tools/engineering-simulation/abaqus-lhs-batch-datasetType 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.
$ npx skills add theneoai/awesome-skills --skill abaqus-lhs-batch-dataset -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install theneoai/awesome-skills abaqus-lhs-batch-dataset --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/theneoai/awesome-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset .agents/skills/abaqus-lhs-batch-dataset && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "abaqus-lhs-batch-dataset" agent skill from https://github.com/theneoai/awesome-skills/tree/main/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset into .agents/skills/abaqus-lhs-batch-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abaqus-lhs-batch-dataset", 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.
$ npx skills add theneoai/awesome-skills --skill abaqus-lhs-batch-dataset -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install theneoai/awesome-skills abaqus-lhs-batch-dataset --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/theneoai/awesome-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset .cursor/skills/abaqus-lhs-batch-dataset && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "abaqus-lhs-batch-dataset" agent skill from https://github.com/theneoai/awesome-skills/tree/main/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset into .cursor/skills/abaqus-lhs-batch-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abaqus-lhs-batch-dataset", 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 https://github.com/theneoai/awesome-skills.git --path skills/tools/engineering-simulation/abaqus-lhs-batch-dataset--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add theneoai/awesome-skills --skill abaqus-lhs-batch-dataset -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install theneoai/awesome-skills abaqus-lhs-batch-dataset --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/theneoai/awesome-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset .gemini/skills/abaqus-lhs-batch-dataset && rm -rf skills-srcUse ~/.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/
Install the "abaqus-lhs-batch-dataset" agent skill from https://github.com/theneoai/awesome-skills/tree/main/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset into .gemini/skills/abaqus-lhs-batch-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abaqus-lhs-batch-dataset", 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.
$ gh skill install theneoai/awesome-skills abaqus-lhs-batch-datasetInstalls 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).
$ npx skills add theneoai/awesome-skills --skill abaqus-lhs-batch-dataset -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/theneoai/awesome-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset .github/skills/abaqus-lhs-batch-dataset && rm -rf skills-srcUse ~/.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/
Install the "abaqus-lhs-batch-dataset" agent skill from https://github.com/theneoai/awesome-skills/tree/main/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset into .github/skills/abaqus-lhs-batch-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abaqus-lhs-batch-dataset", 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.
$ npx skills add theneoai/awesome-skills --skill abaqus-lhs-batch-dataset -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install theneoai/awesome-skills abaqus-lhs-batch-dataset --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/theneoai/awesome-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset .opencode/skills/abaqus-lhs-batch-dataset && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "abaqus-lhs-batch-dataset" agent skill from https://github.com/theneoai/awesome-skills/tree/main/skills/tools/engineering-simulation/abaqus-lhs-batch-dataset into .opencode/skills/abaqus-lhs-batch-dataset/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "abaqus-lhs-batch-dataset", 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
abaqus-lhs-batch-dataset- GitHub stars
- 185
- Token cost
- ~2.9k tokens
- SKILL.md length
- 1,022 words
- Files
- 3 (incl. references)
- Skills in repo
- 11
- Repo updated
- First seen
- Licence
- Custom licence
At a glance
Generate an Abaqus FEA training dataset for surrogate / ML models.
- Works in 11 steps: Read the template, validate → Generate the design matrix → Per-sample case execution → …
- The user wants to build a training set for a surrogate model
- SKILL.md covers When to Use This Skill, Core Pattern, Required Inputs and Sampling Strategies, plus 5 more sections
- Runs Python scripts from its folder; calls python
What it does
Abaqus Lhs Batch Dataset is an agent skill from theneoai/awesome-skills. Generate an Abaqus FEA training dataset for surrogate / ML models. Latin Hypercube Sampling (or sparse-pattern sampling) over a parameterized design vector, one case folder per sample, batch-submit Abaqus jobs via subprocess, recover from crashes, and write a unified dataset index. Use when the user wants to "build a training set for a surrogate model", "sweep design parameters in Abaqus", "run N FEA simulations", or "sample a design space".
Its SKILL.md is about 2.9k tokens, which your agent loads only when the skill is triggered. The skill folder holds 3 other files, including reference files (for example `references/batch_runner.py` and `references/sampling.py`).
It sits in Data & Analytics, covering Machine learning. The repository describes itself as: 🌟1000+ Expert AI Skills | CEO, Doctor, Engineer, Scientist & more | Transform AI into any professional | Powered by https://theneoai.github.io/skill-writer/.
When your agent uses it
- The user wants to build a training set for a surrogate model
- Sweep design parameters in Abaqus
- Run N FEA simulations
- Sample a design space
Example prompts
- “build a training set for a surrogate model”
- “sweep design parameters in Abaqus”
- “run N FEA simulations”
- “/abaqus-lhs-batch-dataset”
Requirements
- Python 3
- Pre-approved tools (allowed-tools): Read, Write, Edit, Glob, Grep, Bash
Workflow steps
11 steps, taken from the step headings in SKILL.md.
- Read the template, validate
- Generate the design matrix
- Per-sample case execution
- Resume / retry support
- Report
- Working directory MUST be the case dir
- Abaqus must be on PATH
- CPU contention
- Disk usage
- Failure modes (in order of frequency)
- Reproducibility
What it can do on your machine
Read from SKILL.md and the folder at commit 61fe4f2. It shows what the files ask for, not the result of running them.
Tool permissions
Pre-approves these tools, so the agent can use them without asking each time:
ReadWriteEditGlobGrepBash
From allowed-tools in the SKILL.md frontmatter.
Runs code
Ships script files (Python), which the agent can run.
Shell commands in SKILL.md call:
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.
Context cost
Abaqus Lhs Batch Dataset loads about 2.9k tokens when it runs, and up to ~7.6k if it reads all its reference files. Until then it costs about 118 tokens; SKILL.md has 1,022 words of instructions outside code blocks.
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: notes
The automated check noted patterns worth knowing about, such as sudo or a known installer.
- NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
allowed-tools: Read, Write, Edit, Glob, Grep, Bash
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
Its licence (Custom licence) doesn't allow us to republish the file, so here is its outline and opening line. It has 1,022 words (~2,907 tokens).
“End-to-end workflow for producing FEA training datasets from a parameterized Abaqus model. Designed for surrogate model training (Ridge, MLP, Gaussian Process, etc.) where you need hundreds to thousands of FEA samples covering a design space.”
- name
- abaqus-lhs-batch-dataset
- allowed-tools
- Read, Write, Edit, Glob, Grep, Bash
- difficulty
- intermediate
- category
- engineering-simulation
- tags
- abaqus, fea, finite-element, simulation, machine-learning, surrogate-model, latin-hypercube, dataset-generation
- platforms
- claude, openclaw, opencode, cursor, codex, cline
- quality
- community
Files
SKILL.md and 2 other files (references) in skills/tools/engineering-simulation/abaqus-lhs-batch-dataset of theneoai/awesome-skills.
- SKILL.md
- references/batch_runner.py
- references/sampling.py
Open the folder on GitHubat commit 61fe4f2
Compare with similar skills
Abaqus Lhs Batch Dataset 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.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Abaqus Lhs Batch Dataset this skilltheneoai/awesome-skills | 185 | — | ~2.9k | Automated safety check: Notes | Custom licence | |
| Scikit LearnzLanqing/codex-claude-academic-skills | 4.7k | 16 repos | ~3.9k | Automated safety check: Pass | BSD-3-Clause | |
| Agentic Kaggle WorkflowFrankS-IntelLab/agentic-kaggle-skill | 188 | — | ~4k | Automated safety check: Pass | MIT | |
| Senior Data ScientistRaidriar7170/hermes-skilleval | 125 | 5 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Geomlitalo-goncalves/geoML | 109 | — | ~4.9k | Automated safety check: Pass | GPL-3.0 | |
| QuantMind Training Config Generatorqusong0627/QuantMind | 1.7k | — | ~1.5k | Automated safety check: Pass | AGPL-3.0 |
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Geoml
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Turns a plain-language model training request into a validated QuantMind training config file that can be imported from the Model Training page.
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Related
Categories
Questions about Abaqus Lhs Batch Dataset
What does Abaqus Lhs Batch Dataset do?
Generate an Abaqus FEA training dataset for surrogate / ML models. Abaqus Lhs Batch Dataset is an agent skill from theneoai/awesome-skills. Generate an Abaqus FEA training dataset for surrogate / ML models.
When should I use Abaqus Lhs Batch Dataset?
Abaqus Lhs Batch Dataset fits situations like: the user wants to build a training set for a surrogate model; sweep design parameters in Abaqus; run N FEA simulations; sample a design space.
How do I install Abaqus Lhs Batch Dataset in Claude Code?
Run `npx skills add theneoai/awesome-skills --skill abaqus-lhs-batch-dataset -a claude-code`. Or copy the skill folder (skills/tools/engineering-simulation/abaqus-lhs-batch-dataset in theneoai/awesome-skills) into .claude/skills/abaqus-lhs-batch-dataset in your project. Claude Code loads it when a task matches its description.
How do I install Abaqus Lhs Batch Dataset in Codex?
Run `npx skills add theneoai/awesome-skills --skill abaqus-lhs-batch-dataset -a codex`. Or copy the skill folder (skills/tools/engineering-simulation/abaqus-lhs-batch-dataset in theneoai/awesome-skills) into .agents/skills/abaqus-lhs-batch-dataset in your project. Codex loads it when a task matches its description.
Can I use Abaqus Lhs Batch Dataset 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 theneoai/awesome-skills --skill abaqus-lhs-batch-dataset -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/abaqus-lhs-batch-dataset, .gemini/skills/abaqus-lhs-batch-dataset, .github/skills/abaqus-lhs-batch-dataset and .opencode/skills/abaqus-lhs-batch-dataset in your project.
What does Abaqus Lhs Batch Dataset need to run?
Going by SKILL.md and its folder, Abaqus Lhs Batch Dataset needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3. Its frontmatter pre-approves these tools: Read, Write, Edit, Glob, Grep, Bash.
Does Abaqus Lhs Batch Dataset 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 Abaqus Lhs Batch Dataset safe to install?
Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.
What licence does Abaqus Lhs Batch Dataset use?
Abaqus Lhs Batch Dataset has a licence file (the repository's licence) that doesn't match a standard licence. Read it on GitHub before reusing the skill.
How many tokens does Abaqus Lhs Batch Dataset use?
About 2.9k tokens (SKILL.md is roughly 12k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 4.7k tokens, read only when the agent opens those files.
What are the alternatives to Abaqus Lhs Batch Dataset?
Skills that share tags, products or a category with Abaqus Lhs Batch Dataset: Scikit Learn (zLanqing/codex-claude-academic-skills, 4.7k stars), Agentic Kaggle Workflow (FrankS-IntelLab/agentic-kaggle-skill, 188 stars), Senior Data Scientist (Raidriar7170/hermes-skilleval, 125 stars) and Geoml (italo-goncalves/geoML, 109 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Abaqus Lhs Batch Dataset?
theneoai (a GitHub user) maintains it in theneoai/awesome-skills, which has 185 GitHub stars. The repository holds 11 skills in this directory. The repository was last updated on May 15, 2026.
Source: theneoai/awesome-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.