Agent Skills › zerogpu/zerogpu-router › chat-gpt-5-4-nano

chat-gpt-5-4-nano

GitHub

调用 OpenAI GPT-5.4-nano 模型进行高吞吐量、低延迟的文本处理任务,如分类、提取和路由。适用于对成本和响应速度敏感的场景,支持函数调用和结构化输出。

agents/openclaw/plugin/skills/chat-gpt-5-4-nano/SKILL.md zerogpu/zerogpu-router

Trigger Scenarios

需要低成本快速推理 执行文本分类或信息提取 处理大规模并发请求 子智能体任务调度

Install

npx skills add zerogpu/zerogpu-router --skill chat-gpt-5-4-nano -g -y
More Options

Non-standard path

npx skills add https://github.com/zerogpu/zerogpu-router/tree/main/agents/openclaw/plugin/skills/chat-gpt-5-4-nano -g -y

Use without installing

npx skills use zerogpu/zerogpu-router@chat-gpt-5-4-nano

指定 Agent (Claude Code)

npx skills add zerogpu/zerogpu-router --skill chat-gpt-5-4-nano -a claude-code -g -y

安装 repo 全部 skill

npx skills add zerogpu/zerogpu-router --all -g -y

预览 repo 内 skill

npx skills add zerogpu/zerogpu-router --list

SKILL.md

Frontmatter
{
    "name": "chat-gpt-5-4-nano",
    "metadata": {
        "openclaw": {
            "install": [
                {
                    "bins": [
                        "zerogpu"
                    ],
                    "kind": "node",
                    "package": "zerogpu-cli"
                }
            ],
            "requires": {
                "bins": [
                    "zerogpu"
                ]
            }
        }
    },
    "description": "Chat with gpt-5.4-nano, the most cost-efficient model in OpenAI's GPT-5.4 family, built for high-volume and latency-sensitive workloads such as classification, extraction, routing, and sub-agent tasks, with function calling, structured outputs, and a 400K-token context window. Use when throughput and latency matter more than depth. Matches chat-gpt-5-6-luna on input price over a larger context.",
    "allowed-tools": "Bash(zerogpu chat_completions *)",
    "argument-hint": "<text> [-i <instructions>]"
}

Sends your input to ZeroGPU's hosted API for inference — this is not local processing. Don't pass secrets, credentials, or regulated data you aren't cleared to share with a third party. See the plugin README's "Data & privacy" section.

Call gpt-5.4-nano. Run this with the exec tool, pasting the user's prompt into the heredoc verbatim — no escaping or quoting required (the quoted heredoc handles every shell metacharacter, newline, quote, and paren safely):

zerogpu chat_completions -m gpt-5.4-nano <<'ZGPU_END_OF_INPUT'
<the user's prompt, verbatim>
ZGPU_END_OF_INPUT

If the user supplied system instructions, add -i '<instructions>' after the model flag, writing any ' inside them as '\''.

At $0.20 / $1.25 per 1M input/output tokens this matches chat-gpt-5-6-luna on input and costs marginally more on output, over a 400K-token window rather than 272K. It is twice chat-gpt-6-luna on input and two and a half times on output. For a prompt that fits in 131K tokens, chat is cheaper on both.

Output is the assistant's answer as plain text. Relay the answer as-is — do not rewrite or expand it.

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.

Version History

  • 605eceb Current 2026-11-02 19:14

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Version
605eceb
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2026-11-02 19:14

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