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

Security Scan

The skill appears to do what it claims (query GLM plan usage) but its metadata and runtime behavior are inconsistent: it reads your OpenClaw config for an API key and sends it to open.bigmodel.cn while declaring no credentials required, and it hardcodes the API base URL rather than using the configured baseUrl.

Purpose & Capability

Skill name/description (query GLM coding plan usage) matches the provided script and docs. The included script queries quota/model/tool endpoints on the GLM monitoring API and formats the result; those operations are appropriate for the stated purpose.

Instruction Scope

Runtime instructions and the script are focused on reading ~/.openclaw/openclaw.json to detect a provider, extracting an API key, and calling three monitoring endpoints on open.bigmodel.cn. The script does not attempt to exfiltrate data to unrelated endpoints or read arbitrary system files, but it will access the user's OpenClaw config (which may contain multiple provider API keys).

Install Mechanism

No install spec is provided (instruction-only skill plus a bash script). Installation is typical (copy files into ~/.openclaw/skills and make script executable). No remote downloads or archives are performed by the skill itself.

Credentials

Registry metadata declares no required credentials, but the script expects and reads an API key from ~/.openclaw/openclaw.json and uses it in Authorization headers when calling the monitoring API. This is a meaningful mismatch: the skill requires access to a secret stored in the user's config, and that secret will be sent to open.bigmodel.cn. The script also reads the HOME environment (for the config path) and an optional OPENCLAW_LANGUAGE env var; those are reasonable but not declared.

Persistence & Privilege

The skill is user-invocable and not always-enabled. It does not request elevated OS privileges, does not modify other skills or system-wide configuration, and does not persist new credentials. Installing simply places files under the user's ~/.openclaw/skills folder.

What to consider before installing

This skill largely does what it claims, but review and be aware of two issues before installing: - The script reads your OpenClaw config (~/.openclaw/openclaw.json) and extracts an API key for the detected provider; that key is included in Authorization headers and sent to https://open.bigmodel.cn. Verify you are comfortable with that provider receiving the key and that the key in your config is scoped appropriately. - The registry metadata lists no required credentials, which is inaccurate. Expect the script to require a provider entry with baseUrl containing api/coding/paas/v4 and an apiKey in ~/.openclaw/openclaw.json. - The script hardcodes API_BASE to https://open.bigmodel.cn rather than using the provider's baseUrl value; if you use a proxy/custom endpoint this may not work. Inspect scripts/query-usage.sh yourself (or run it in a safe environment) to confirm behavior before installing. If you have other sensitive API keys in your OpenClaw config, consider removing/isolating them or creating a separate provider entry with a limited-scope key just for monitoring.

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

2. 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

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 ~/.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/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。 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

• OpenClaw 文档 | OpenClaw Documentation
• GLM 编码套餐 | GLM Coding Plan
• API 文档 | API Documentation
• 安装指南 | Installation Guide