Skill: orientluna/openclaw-glm-plan-usage (version 1.0.1)

--- 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`: ```bash 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: ```bash git clone https://github.com/OrientLuna/openclaw-glm-plan-usage.git cd openclaw-glm-plan-usage ``` 2. 复制技能文件到 OpenClaw 技能目录： Copy skill files to OpenClaw skills directory: ```bash cp -r . ~/.openclaw/skills/glm-plan-usage/ chmod +x ~/.openclaw/skills/glm-plan-usage/scripts/query-usage.sh ``` 3. 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 bash ~/.openclaw/skills/glm-plan-usage/scripts/query-usage.sh ``` ### 通过 OpenClaw 技能调用 / Via OpenClaw Skill ```bash 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: ```bash # 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 ```json { "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/v4` 或 `open.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/v4` 或 `open.bigmodel.cn` `baseUrl` contains `api/coding/paas/v4` or `open.bigmodel.cn` 2. 提供商名称包含 `coding`、`glm-coding`、`zhipu` 或 `bigmodel` 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](references/api-endpoints.md)。 See [API Documentation](references/api-endpoints.md) 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: ```bash 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: ```json { "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: ```bash 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](LICENSE) 文件。 MIT License - See [LICENSE](LICENSE) file for details. ## 致谢 / Acknowledgments - 原始实现: [zai-coding-plugins](https://github.com/zai-org/zai-coding-plugins) | Original implementation - 参考实现: [opencode-glm-quota](https://github.com/guyinwonder168/opencode-glm-quota) | Reference implementation - OpenClaw 集成: 本技能 | OpenClaw integration: This skill ## 相关资源 / Resources - [OpenClaw 文档](https://openclaw.dev) | [OpenClaw Documentation](https://openclaw.dev) - [GLM 编码套餐](https://open.bigmodel.cn) | [GLM Coding Plan](https://open.bigmodel.cn) - [API 文档](references/api-endpoints.md) | [API Documentation](references/api-endpoints.md) - [安装指南](docs/INSTALLATION.md) | [Installation Guide](docs/INSTALLATION.md)


Security scan verdicts — ClawScan: clean | static analysis: suspicious | VirusTotal: clean | SkillSpector: suspicious (HIGH)