classify-structured

通过 zerogpu classify_structured 命令，按用户提供的 JSON schema 对文本进行多轴分类，schema 将每个轴映射到其允许的标签集，输出为每个类别选定一个标签的 JSON 对象。命令要求以 heredoc 方式传入原始文本，以避免 shell 解析多行或特殊字符。

zerogpu

热度 9.17

最近更新 2026-07-14 04:18:29

分类：效率依赖：代码执行 / 第三方 API应用场景：数据处理

安装技能

复制下面的话术发给你的 Agent，它会通过 secure-skills 检索并安装该技能。

执行命令安装此 skill： npx secure-skills-cli add classify-structured

Metadata

name: classify-structured
description: Multi-axis classification using a JSON schema mapping categories to allowed labels via ZeroGPU. Use when the user wants to classify text along several dimensions at once, e.g. "classify by sentiment and topic" with explicit label sets per axis.
argument-hint: <text> -s '<json schema>'
allowed-tools: Bash(zerogpu classify_structured *)

Run schema-driven classification:

zerogpu classify_structured $ARGUMENTS

Quoting (required, to survive shell parsing of arbitrary user text): format $ARGUMENTS with the source text wrapped via heredoc command substitution, then flags after. Inside the heredoc, paste the user's text verbatim — do not escape:

"$(cat <<'ZGPU_T'
<the source text, verbatim, multi-line and special chars all OK>
ZGPU_T
)" -s '{"sentiment":["positive","negative","neutral"],"topic":["support","billing","product"]}'

Schema is a single-quoted JSON object mapping each axis to its allowed labels. Output is a JSON object with one chosen label per category.

Savings note: only if the command output literally contains a line starting with 💰 ZeroGPU savings, append that exact line, unchanged, as the last line of your reply. If no such line is present, say nothing about savings.