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Install in OpenClaw
/install model-usage-stats
Description
模型消耗统计技能，用于统计和展示不同会话、不同模型的 token 使用量、成本统计和消耗报告，通过飞书消息卡片进行可视化展示。当用户请求查看模型消耗、token 统计、成本分析或消耗报告时使用。
Usage Guidance
This skill appears internally consistent and low-risk, but verify two operational details before enabling: (1) Confirm what data the platform 'session_status'/'sessions_list' APIs expose (they may include full conversation text); if they include sensitive content, restrict who can invoke the skill or filter/redact fields before reporting. (2) Confirm how the 'message' tool posts to Feishu (which Feishu account/app is used) and that no unintended data is shared externally. Also check that the model pricing numbers match your billing rates if you rely on the cost calculations. If you want extra safety, allow this skill only for manual/user-invoked reports (disable autonomous invocation where possible) and review generated card previews before sending to external channels.
Capability Analysis
Type: OpenClaw Skill
Name: model-usage-stats
Version: 1.0.0
The skill bundle 'model-usage-stats' is designed to track and report LLM token usage and costs. It provides instructions for an AI agent to use standard OpenClaw tools (session_status, sessions_list, message) to aggregate session data and format it into Feishu message cards. There is no evidence of data exfiltration, malicious execution, or harmful prompt injection.
Capability Assessment
Purpose & Capability
Name/description match the runtime instructions: the SKILL.md only describes collecting session usage (via session_status, sessions_list, sessions_history), computing token/cost metrics, and sending formatted Feishu cards. No unrelated credentials, binaries, or installs are requested.
Instruction Scope
Instructions are scoped to reading session data and producing reports sent through the platform 'message' tool (Feishu cards). This is appropriate, but it assumes the 'session_*' tools supply accurate token details and that the 'message' tool is authorized to post to Feishu; verify those tool permissions and what session data they expose (conversation contents may be included).
Install Mechanism
No install spec and no code files — instruction-only skill. Nothing will be downloaded or written to disk by this skill itself.
Credentials
The skill declares no environment variables, credentials, or config paths. That is proportionate for a reporting skill that relies on platform-provided session and messaging tools.
Persistence & Privilege
always is false and the skill is user-invocable (normal). It does not request persistent/enforced presence or modify other skills. Note: the platform default allows autonomous invocation, but that is not unique to this skill and always:false reduces continuous privilege.
How to Use
- Make sure OpenClaw is installed (local or Docker)
- Run the install command in chat:
/install model-usage-stats - After installation, invoke the skill by name or use
/model-usage-stats - Provide required inputs per the skill's parameter spec and get structured output
Version History
v1.0.0
- Initial release of the "model-usage-stats" skill.
- Provides token usage, cost statistics, and consumption reports by session and model.
- Visualizes data with Feishu (Lark) message cards (tables, summaries, charts).
- Supports queries for current session usage, historical session stats, model breakdowns, and exportable reports.
- Includes sample message templates, typical use cases, and reference pricing for supported models.
Metadata
Frequently Asked Questions
What is 模型消耗统计?
模型消耗统计技能，用于统计和展示不同会话、不同模型的 token 使用量、成本统计和消耗报告，通过飞书消息卡片进行可视化展示。当用户请求查看模型消耗、token 统计、成本分析或消耗报告时使用。 It is an AI Agent Skill for Claude Code / OpenClaw, with 101 downloads so far.
How do I install 模型消耗统计?
Run "/install model-usage-stats" in the OpenClaw or Claude Code chat to install it in one step — no extra setup required.
Is 模型消耗统计 free?
Yes, 模型消耗统计 is completely free, licensed under MIT-0. You can download, install and use it at no cost.
Which platforms does 模型消耗统计 support?
模型消耗统计 is cross-platform and runs anywhere OpenClaw / Claude Code is available (cross-platform).
Who created 模型消耗统计?
It is built and maintained by luxiang79 (@luxiang79); the current version is v1.0.0.
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