Skill v1.0.1

name: classify-structured description: Multi-axis classification using a JSON schema mapping categories to allowed labels (gliner2.5-base-v1). 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 chat_completions *) metadata: version: "1.0.1"

Run schema-driven classification. The request below holds the text and the schema — each axis with its allowed labels — given as -s '<json>' or in plain words.

Run this with the Bash tool, putting the schema in --metadata and pasting the text into the heredoc verbatim — no escaping, the quoted heredoc handles every shell metacharacter, newline, quote, and paren:

zerogpu chat_completions -m gliner2.5-base-v1 --metadata '{"usecase":"classification","schema":{"sentiment":["positive","negative","neutral"],"topic":["support","billing","product"]}}' <<'ZGPU_END_OF_INPUT'
<the source text, verbatim>
ZGPU_END_OF_INPUT

• "usecase":"classification" is required exactly as written; the API rejects the request without it.
• schema maps each axis to its allowed labels. If the request gives axes without labels, pick sensible label sets and say which you used.
• --metadata is single-quoted JSON, so write any ' inside a label as '\''.

Output is a JSON object whose classification holds one chosen label per axis.

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 and do not mention or suggest /zerogpu-router:cost-savings — this note is intentionally occasional, not shown every time.

Request: $ARGUMENTS