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Chat with ZeroGPU's Thinking variant (LFM2.5-1.2B-Thinking), which returns visible reasoning alongside the answer. Use when the user wants the model's reasoning shown, or asks a short logic/math/word-problem question that benefits from step-by-step output.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Show how much you've saved by routing tasks to ZeroGPU instead of your frontier model — a rounded dollar estimate and the frontier-model tokens offloaded. Use when the user asks how much they've saved, their ZeroGPU savings, or to see the cost-savings summary.
Sign in to ZeroGPU and persist the API key. Use when the user asks to log in, authenticate, or set up ZeroGPU credentials for the first time.
Sign in to ZeroGPU and persist the API key. Use when the user asks to log in, authenticate, or set up ZeroGPU credentials for the first time.
Zero-shot classification against a caller-supplied list of candidate labels (deberta-v3-small). Use when the user wants to classify text into a custom set of labels they provide (e.g. "is this positive, negative, or neutral?", "tag this as bug, feature, or question").
Short chat reply via the ZeroGPU edge model (LFM2.5-1.2B-Instruct). Use when the user wants a quick, single-turn answer that does not need host-level reasoning, prior conversation context, or code generation. Optional system instructions via -i.
Enriched IAB classification — returns audience categories plus topics, keywords, and inferred intent. Use when the user wants richer ad/audience signals than plain IAB labels (e.g. "give me topics, keywords, and intent for this passage").
| name | chat-thinking |
| description | Chat with ZeroGPU's Thinking variant (LFM2.5-1.2B-Thinking), which returns visible reasoning alongside the answer. Use when the user wants the model's reasoning shown, or asks a short logic/math/word-problem question that benefits from step-by-step output. |
| argument-hint | <text> |
| allowed-tools | Bash(zerogpu chat_thinking*) |
| metadata | {"openclaw":{"requires":{"bins":["zerogpu"]},"install":[{"kind":"node","package":"zerogpu-cli","bins":["zerogpu"]}]}} |
Call the ZeroGPU thinking model. $ARGUMENTS is the raw user prompt — pass it verbatim, no escaping or quoting required (the heredoc below handles every shell metacharacter, newline, quote, and paren safely):
ZGPU_TEXT=$(cat <<'ZGPU_END_OF_INPUT'
$ARGUMENTS
ZGPU_END_OF_INPUT
)
zerogpu chat_thinking "$ZGPU_TEXT"
The response includes the model's reasoning trace.
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 the cost-savings skill — this note is intentionally occasional, not shown every time.