Scikit Learn
zLanqing/codex-claude-academic-skills
Machine learning in Python with scikit-learn. An agent skill from zLanqing/codex-claude-academic-skills.
Optimize data loading pipeline to prevent GPU starvation. An agent skill from aiming-lab/AutoResearchClaw.
Install Data Loading
$ npx skills add aiming-lab/AutoResearchClaw --skill data-loading -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install aiming-lab/AutoResearchClaw data-loading --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/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .claude/skills && cp -r skills-src/researchclaw/skills/builtin/tooling/data-loading .claude/skills/data-loading && 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 "data-loading" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/tooling/data-loading into .claude/skills/data-loading/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-loading", 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/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/tooling/data-loadingType 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 aiming-lab/AutoResearchClaw --skill data-loading -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install aiming-lab/AutoResearchClaw data-loading --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .agents/skills && cp -r skills-src/researchclaw/skills/builtin/tooling/data-loading .agents/skills/data-loading && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "data-loading" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/tooling/data-loading into .agents/skills/data-loading/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-loading", 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 aiming-lab/AutoResearchClaw --skill data-loading -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install aiming-lab/AutoResearchClaw data-loading --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/researchclaw/skills/builtin/tooling/data-loading .cursor/skills/data-loading && 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 "data-loading" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/tooling/data-loading into .cursor/skills/data-loading/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-loading", 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/aiming-lab/AutoResearchClaw.git --path researchclaw/skills/builtin/tooling/data-loading--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 aiming-lab/AutoResearchClaw --skill data-loading -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install aiming-lab/AutoResearchClaw data-loading --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/researchclaw/skills/builtin/tooling/data-loading .gemini/skills/data-loading && 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 "data-loading" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/tooling/data-loading into .gemini/skills/data-loading/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-loading", 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 aiming-lab/AutoResearchClaw data-loadingInstalls 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 aiming-lab/AutoResearchClaw --skill data-loading -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .github/skills && cp -r skills-src/researchclaw/skills/builtin/tooling/data-loading .github/skills/data-loading && 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 "data-loading" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/tooling/data-loading into .github/skills/data-loading/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-loading", 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 aiming-lab/AutoResearchClaw --skill data-loading -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install aiming-lab/AutoResearchClaw data-loading --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/aiming-lab/AutoResearchClaw.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/researchclaw/skills/builtin/tooling/data-loading .opencode/skills/data-loading && 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 "data-loading" agent skill from https://github.com/aiming-lab/AutoResearchClaw/tree/main/researchclaw/skills/builtin/tooling/data-loading into .opencode/skills/data-loading/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "data-loading", 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
data-loading- GitHub stars
- 15k
- Token cost
- ~210 tokens
- SKILL.md length
- 55 words
- Files
- 1
- Skills in repo
- 34
- Repo updated
- First seen
- Licence
- MIT
At a glance
Optimize data loading pipeline to prevent GPU starvation. An agent skill from aiming-lab/AutoResearchClaw.
- Works in 7 steps: Use num_workers = min(8, os.cpu_count())… → Enable pin_memory=True when using GPU → Use persistent_workers=True to avoid… → …
- Setting up DataLoader
- Instructions only: no scripts, shell commands, URLs or credentials in SKILL.md
- Data preprocessing
What it does
Data Loading is an agent skill from aiming-lab/AutoResearchClaw. Optimize data loading pipeline to prevent GPU starvation. Use when setting up DataLoader or data preprocessing.
Its SKILL.md is about 210 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Data & Analytics, covering Machine learning. The repository describes itself as: Fully autonomous & self-evolving research from idea to paper. Chat an Idea. Get a Paper. 🦞. The licence is MIT.
When your agent uses it
- Setting up DataLoader
- Data preprocessing
Example prompts
- “/data-loading”
Workflow steps
7 steps, taken from the first numbered list in SKILL.md.
- Use num_workers = min(8, os.cpu_count()) for DataLoader
- Enable pin_memory=True when using GPU
- Use persistent_workers=True to avoid re-spawning
- Pre-compute and cache transformations when possible
- For image data: use torchvision.transforms.v2 (faster)
- For large datasets: consider memory-mapped files or WebDataset
- Profile with torch.utils.bottleneck to find I/O bottlenecks
What it can do on your machine
Read from SKILL.md and the folder at commit be4ba47. 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.
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
Data Loading loads about 210 tokens when it runs. Until then it costs about 31 tokens; SKILL.md has 55 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 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 aiming-lab/AutoResearchClaw at commit be4ba47, republished under its MIT licence (© aiming-lab). 55 words, ~210 tokens.
Download SKILL.mdSave it as
.claude/skills/data-loading/SKILL.md (or your agent's skills folder).- name
- data-loading
- description
- Optimize data loading pipeline to prevent GPU starvation. Use when setting up DataLoader or data preprocessing.
- metadata.category
- tooling
- metadata.trigger-keywords
- data,loading,dataloader,dataset,preprocessing,augmentation
- metadata.applicable-stages
- 10
- metadata.priority
- 6
- metadata.version
- 1.0
- metadata.author
- researchclaw
- metadata.references
- PyTorch Data Loading Tutorial, pytorch.org
Efficient Data Loading Best Practice
- Use num_workers = min(8, os.cpu_count()) for DataLoader
- Enable pin_memory=True when using GPU
- Use persistent_workers=True to avoid re-spawning
- Pre-compute and cache transformations when possible
- For image data: use torchvision.transforms.v2 (faster)
- For large datasets: consider memory-mapped files or WebDataset
- Profile with torch.utils.bottleneck to find I/O bottlenecks
© aiming-lab, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Files
Just SKILL.md in researchclaw/skills/builtin/tooling/data-loading of aiming-lab/AutoResearchClaw.
Open the folder on GitHubat commit be4ba47
Compare with similar skills
Data Loading 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 |
|---|---|---|---|---|---|---|
| Data Loading this skillaiming-lab/AutoResearchClaw | 15k | — | ~210 | Automated safety check: Pass | MIT | |
| Scikit LearnzLanqing/codex-claude-academic-skills | 4.6k | 17 repos | ~3.9k | Automated safety check: Pass | BSD-3-Clause | |
| Senior Data ScientistRaidriar7170/hermes-skilleval | 125 | 6 repos | ~1.4k | Automated safety check: Pass | MIT | |
| Agentic Kaggle WorkflowFrankS-IntelLab/agentic-kaggle-skill | 188 | — | ~4k | Automated safety check: Pass | MIT | |
| Retention Analysisliangdabiao/claude-data-analysis-ultra-main | 290 | 1 repos | ~1.3k | Automated safety check: Notes | None | |
| Geomlitalo-goncalves/geoML | 108 | — | ~4.2k | Automated safety check: Pass | GPL-3.0 |
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More from aiming-lab/AutoResearchClaw
All 34 skills in this repoA-Evolve Agent Improvement
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Diagnoses where an agent failed across runs and turns the findings into new skills, system prompt patches and knowledge entries, using the A-Evolve loop.
Metabolic Study Planner
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Turns a broad metabolic modelling topic into a concrete, paper-shaped plan with organism, model, perturbations, metrics and figures before any FBA code is written.
MFA Pipeline Orchestrator
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Runs a metabolic flux analysis from model loading to phenotype prediction and figures by handing work to four sub-agents in sequence.
Qiskit 2.x Quantum ML Reference
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Reference patterns for writing qiskit 2.x code for variational quantum machine learning: feature maps, VQC training, VQE for chemistry, MPS circuits and noise models.
Genome-Scale Metabolic Model Builder
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Builds or loads a genome-scale metabolic model in COBRApy, sets its growth medium and objective, and exports it as a validated JSON file for flux analysis.
Biopython Bioinformatics
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Quick reference for Biopython work: sequence operations, SeqIO file parsing, BLAST searches, Entrez queries, phylogenetic trees and PDB structure analysis.
Related
Categories
Questions about Data Loading
What does Data Loading do?
Optimize data loading pipeline to prevent GPU starvation. An agent skill from aiming-lab/AutoResearchClaw. Data Loading is an agent skill from aiming-lab/AutoResearchClaw. Optimize data loading pipeline to prevent GPU starvation.
When should I use Data Loading?
Data Loading fits situations like: setting up DataLoader; data preprocessing.
How do I install Data Loading in Claude Code?
Run `npx skills add aiming-lab/AutoResearchClaw --skill data-loading -a claude-code`. Or copy the skill folder (researchclaw/skills/builtin/tooling/data-loading in aiming-lab/AutoResearchClaw) into .claude/skills/data-loading in your project. Claude Code loads it when a task matches its description.
How do I install Data Loading in Codex?
Run `npx skills add aiming-lab/AutoResearchClaw --skill data-loading -a codex`. Or copy the skill folder (researchclaw/skills/builtin/tooling/data-loading in aiming-lab/AutoResearchClaw) into .agents/skills/data-loading in your project. Codex loads it when a task matches its description.
Can I use Data Loading 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 aiming-lab/AutoResearchClaw --skill data-loading -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/data-loading, .gemini/skills/data-loading, .github/skills/data-loading and .opencode/skills/data-loading in your project.
What does Data Loading need to run?
SKILL.md names no scripts, command-line tools or credentials: Data Loading is instructions for the agent only.
Does Data Loading 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 Data Loading 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 Data Loading use?
Data Loading is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
How many tokens does Data Loading use?
About 210 tokens (SKILL.md is roughly 840 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 Data Loading?
Skills that share tags, products or a category with Data Loading: Scikit Learn (zLanqing/codex-claude-academic-skills, 4.6k stars), Senior Data Scientist (Raidriar7170/hermes-skilleval, 125 stars), Agentic Kaggle Workflow (FrankS-IntelLab/agentic-kaggle-skill, 188 stars) and Retention Analysis (liangdabiao/claude-data-analysis-ultra-main, 290 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
Who maintains Data Loading?
aiming-lab (a GitHub organization) maintains it in aiming-lab/AutoResearchClaw, which has 14,587 GitHub stars. The repository holds 34 skills in this directory. The repository was last updated on August 19, 2026.
Source: aiming-lab/AutoResearchClaw on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.