🧪 Skills

glm-plan-usage

查询 GLM 编码套餐使用统计,包括配额、模型使用和 MCP 工具使用情况 | Query GLM coding plan usage statistics, including quota, model usage, and MCP tool usage

v1.0.1
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Description


name: glm-plan-usage displayName: GLM Plan Usage version: 1.0.0 description: 查询 GLM 编码套餐使用统计,包括配额、模型使用和 MCP 工具使用情况 | Query GLM coding plan usage statistics, including quota, model usage, and MCP tool usage author: OpenClaw Community license: MIT tags:

  • glm
  • usage
  • monitoring
  • statistics
  • zhipu
  • chinese
  • english requirements:
  • curl
  • jq

GLM Plan Usage Skill

查询 GLM 编码套餐使用统计的 OpenClaw 技能。 OpenClaw skill for querying GLM coding plan usage statistics.

功能特性 / Features

  • 配额监控: 查看 Token 使用量(5小时)和 MCP 使用量(1个月) Quota Monitoring: View token usage (5-hour) and MCP usage (1-month)
  • 模型使用: 显示 24 小时内的 Token 数和调用次数 Model Usage: Display token count and call count within 24 hours
  • 工具使用: 跟踪 24 小时内的 MCP 工具使用情况 Tool Usage: Track MCP tool usage within 24 hours
  • 自动检测: 自动从 OpenClaw 配置中检测 GLM 编码套餐提供商 Auto Detection: Automatically detect GLM coding plan provider from OpenClaw configuration
  • 双语支持: 支持中文和英文输出 Bilingual Support: Support Chinese and English output

依赖要求 / Requirements

  • curl - HTTP 客户端(通常预装) | HTTP client (usually pre-installed)
  • jq - JSON 处理器 | JSON processor

如需安装 jq: To install jq:

sudo apt-get install jq  # Linux
brew install jq           # macOS

安装 / Installation

  1. 将此仓库克隆到本地: Clone this repository to local:
git clone https://github.com/OrientLuna/openclaw-glm-plan-usage.git
cd openclaw-glm-plan-usage
  1. 复制技能文件到 OpenClaw 技能目录: Copy skill files to OpenClaw skills directory:
cp -r . ~/.openclaw/skills/glm-plan-usage/
chmod +x ~/.openclaw/skills/glm-plan-usage/scripts/query-usage.sh
  1. 确保已配置 GLM 编码套餐提供商(见下方配置说明) Ensure GLM coding plan provider is configured (see Configuration below)

使用方法 / Usage

直接运行脚本 / Run Script Directly

bash ~/.openclaw/skills/glm-plan-usage/scripts/query-usage.sh

通过 OpenClaw 技能调用 / Via OpenClaw Skill

openclaw /glm-plan-usage:usage-query

语言切换 / Language Switching

脚本会自动检测语言环境。您也可以通过环境变量强制指定语言: The script automatically detects language environment. You can also force language via environment variable:

# 中文输出 / Chinese output
OPENCLAW_LANGUAGE=zh bash ~/.openclaw/skills/glm-plan-usage/scripts/query-usage.sh

# 英文输出 / English output
OPENCLAW_LANGUAGE=en bash ~/.openclaw/skills/glm-plan-usage/scripts/query-usage.sh

示例输出 / Sample Output

📊 GLM 编码套餐使用统计 / GLM Coding Plan Usage Statistics

提供商 / Provider: zhipu
统计时间 / Statistics Time: 2026-02-13 20:30:15

配额限制 / Quota Limits
---
  Token 使用 (5小时) / Token Usage (5-hour): 45.2%
  MCP 使用 (1个月) / MCP Usage (1-month):   12.3%  (15000/120000 秒 / sec) [LEVEL_4]

模型使用 (24小时) / Model Usage (24 hours)
---
  总 Token 数 / Total Tokens:  12,500,000
  总调用次数 / Total Calls:  1,234

工具使用 (24小时) / Tool Usage (24 hours)
---
  bash: 156 次 / times
  file-read: 89 次 / times
  web-search: 34 次 / times

配置说明 / Configuration

技能会自动读取 ~/.openclaw/openclaw.json 中的提供商配置。 The skill automatically reads provider configuration from ~/.openclaw/openclaw.json.

示例配置 / Sample Configuration

{
  "agents": {
    "defaults": {
      "model": {
        "primary": "zhipu/glm-4-flash"
      }
    }
  },
  "models": {
    "providers": {
      "zhipu": {
        "baseUrl": "https://open.bigmodel.cn/api/coding/paas/v4",
        "apiKey": "your-api-key-here"
      }
    }
  }
}

重要: baseUrl 必须包含 api/coding/paas/v4open.bigmodel.cn,技能才能识别其为 GLM 编码套餐提供商。 Important: baseUrl must contain api/coding/paas/v4 or open.bigmodel.cn for the skill to recognize it as a GLM coding plan provider.

提供商检测逻辑 / Provider Detection Logic

技能会检查以下条件来识别 GLM 编码套餐提供商: The skill checks the following conditions to identify GLM coding plan providers:

  1. baseUrl 包含 api/coding/paas/v4open.bigmodel.cn baseUrl contains api/coding/paas/v4 or open.bigmodel.cn
  2. 提供商名称包含 codingglm-codingzhipubigmodel Provider name contains coding, glm-coding, zhipu, or bigmodel

API 端点 / API Endpoints

技能查询三个监控端点: The skill queries three monitoring endpoints:

端点 Endpoint 用途 Purpose
/api/monitor/usage/quota/limit 配额百分比(5小时 Token,1个月 MCP) Quota percentage (5-hour token, 1-month MCP)
/api/monitor/usage/model-usage 24小时模型使用统计 24-hour model usage statistics
/api/monitor/usage/tool-usage 24小时 MCP 工具使用 24-hour MCP tool usage

详见 API 文档。 See API Documentation for details.

错误处理 / Error Handling

脚本为常见问题提供友好的错误提示: The script provides friendly error messages for common issues:

  • 缺少依赖工具(curl、jq) | Missing dependencies (curl, jq)
  • 缺少或无效的 OpenClaw 配置 | Missing or invalid OpenClaw configuration
  • 提供商未配置为 GLM 编码套餐 | Provider not configured as GLM coding plan
  • API 认证失败 | API authentication failed
  • 网络超时 | Network timeout

故障排除 / Troubleshooting

"缺少依赖工具,请安装: jq" / "Missing dependency, please install: jq"

使用包管理器安装 jq: Install jq using package manager:

sudo apt-get install jq  # Linux
brew install jq           # macOS

"未找到配置 GLM 编码套餐的提供商" / "No GLM coding plan provider configured"

确保提供商的 baseUrl 包含 api/coding/paas/v4。更新配置: Ensure the provider's baseUrl contains api/coding/paas/v4. Update configuration:

{
  "models": {
    "providers": {
      "your-provider": {
        "baseUrl": "https://open.bigmodel.cn/api/coding/paas/v4",
        "apiKey": "your-key"
      }
    }
  }
}

"认证失败,请检查 API 密钥配置" / "Authentication failed, please check API key"

验证 API 密钥是否正确: Verify API key is correct:

jq -r '.models.providers.zhipu.apiKey' ~/.openclaw/openclaw.json

贡献指南 / Contributing

欢迎贡献!请遵循以下步骤: Contributions welcome! Please follow these steps:

  1. Fork 本仓库 | Fork this repository
  2. 创建特性分支 (git checkout -b feature/amazing-feature) | Create feature branch
  3. 提交更改 (git commit -m 'Add some amazing feature') | Commit changes
  4. 推送到分支 (git push origin feature/amazing-feature) | Push to branch
  5. 开启 Pull Request | Open Pull Request

许可证 / License

MIT License - 详见 LICENSE 文件。 MIT License - See LICENSE file for details.

致谢 / Acknowledgments

  • 原始实现: zai-coding-plugins | Original implementation
  • 参考实现: opencode-glm-quota | Reference implementation
  • OpenClaw 集成: 本技能 | OpenClaw integration: This skill

相关资源 / Resources

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