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PyTorch Classification for Variable-Length 1D Arrays

100 / 100 · Low risk

Fine to try.

By ECNU-ICALK/AutoSkill (GitHub) · other · 613 stars · scanned at commit 94c47ca

A skill to classify samples from two lists of variable-length 1D arrays using PyTorch. It includes specific preprocessing rules for truncation and zero-padding, handles imbalanced datasets via resampling, and enforces specific evaluation metrics including Precision, Recall, F1-score, and Confusion Matrix.

Works with any agent that supports SKILL.md skills.

What this skill can do

We found nothing in the files we read that matches our rules. That does not prove the skill is safe: see the limits of static scanning.

Install

Paste this into your terminal. It downloads exactly the version we scanned, not whatever is newest.

if [ -e ~/.agents/skills/'pytorch-classification-for-variable-length-1d-arrays' ] || [ -L ~/.agents/skills/'pytorch-classification-for-variable-length-1d-arrays' ]; then echo 'A skill folder named pytorch-classification-for-variable-length-1d-arrays already exists — not replacing it' >&2; false; else d=$(mktemp -d) && git clone --quiet --filter=blob:none --no-checkout 'https://github.com/ECNU-ICALK/AutoSkill' "$d" && git -C "$d" checkout --quiet '94c47ca488d4ba4117d20272e66d49b9877e68cf' -- 'SkillBank/ConvSkill/english_gpt3.5_8_GLM4.7/pytorch-classification-for-variable-length-1d-arrays' && mkdir -p ~/.agents/skills && cp -R "$d"/'SkillBank/ConvSkill/english_gpt3.5_8_GLM4.7/pytorch-classification-for-variable-length-1d-arrays' ~/.agents/skills/'pytorch-classification-for-variable-length-1d-arrays' && rm -rf "$d"; fi

Codex reads ~/.agents/skills directly. For Claude Code, Cursor, Copilot, Gemini CLI, Antigravity or OpenCode, also link it. For Claude Code: ln -s ~/.agents/skills/'pytorch-classification-for-variable-length-1d-arrays' ~/.claude/skills/'pytorch-classification-for-variable-length-1d-arrays' (other agents: ~/.cursor/skills, ~/.copilot/skills, ~/.gemini/skills, ~/.gemini/config/skills, ~/.config/opencode/skills). Or install through the finder skill, which does both.

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