Agent Skills › zerogpu/zerogpu-router › chat-glm-5-3-flash

chat-glm-5-3-flash

GitHub

调用 glm-5.3-flash 模型进行代码编写、长文档处理及多步智能体任务。该模型支持百万级上下文,性价比高,适用于仓库级代码工作和复杂推理场景。

agents/claude/skills/chat-glm-5-3-flash/SKILL.md zerogpu/zerogpu-router

Trigger Scenarios

需要高效完成代码生成或重构任务 处理超长文档或需要长上下文记忆 执行多步骤的智能体自动化工作流

Install

npx skills add zerogpu/zerogpu-router --skill chat-glm-5-3-flash -g -y
More Options

Non-standard path

npx skills add https://github.com/zerogpu/zerogpu-router/tree/main/agents/claude/skills/chat-glm-5-3-flash -g -y

Use without installing

npx skills use zerogpu/zerogpu-router@chat-glm-5-3-flash

指定 Agent (Claude Code)

npx skills add zerogpu/zerogpu-router --skill chat-glm-5-3-flash -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-glm-5-3-flash",
    "description": "Chat with glm-5.3-flash, Z.ai's efficient open-weight model for coding and long-horizon agent tasks, whose hybrid sparse and linear attention holds a 1M-token context window with function calling and adjustable reasoning effort. Use for repo-scale code work, long documents, and multi-step agent runs. It is the cheapest of the three 1M-context models on the platform, about an eleventh of chat-glm on input and a tenth on output.",
    "allowed-tools": "Bash(zerogpu chat_completions *)",
    "argument-hint": "<text>"
}

Call glm-5.3-flash. $ARGUMENTS is the raw prompt — pass it verbatim, no escaping or quoting required (the heredoc below handles every shell metacharacter, newline, quote, and paren safely):

zerogpu chat_completions -m glm-5.3-flash <<'ZGPU_END_OF_INPUT'
$ARGUMENTS
ZGPU_END_OF_INPUT

At $0.10 / $0.35 per 1M input/output tokens this is the cheapest of the three 1M-context models on the platform — about an eleventh of /zerogpu-router:chat-glm on input and a tenth on output, and roughly two thirds of /zerogpu-router:chat-deepseek-v4-1-flash on both. Prefer it for coding and long-horizon agent work at repo scale; when the task wants DeepSeek's higher-effort reasoning, chat-deepseek-v4-1-flash is the pricier alternative.

Output is the assistant's answer as plain text — the model's reasoning trace comes back in a separate field and is not printed. 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 /zerogpu-router:cost-savings — this note is intentionally occasional, not shown every time.

Version History

  • 59e0f53 Current 2026-09-27 19:55

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Metadata

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Version
59e0f53
Hash
235a1a1b
Indexed
2026-09-27 19:55

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