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Usage Visualizer

作者 Vint · GitHub ↗ · v1.1.3
darwinlinux ⚠ suspicious
871
总下载
2
收藏
2
当前安装
8
版本数
在 OpenClaw 中安装
/install usage-visualizer
功能描述
Advanced usage statistics and high-fidelity visual reporting for OpenClaw. 100% local processing. Audit-verified privacy (No credentials stored).
安全使用建议
This skill is internally consistent with its stated purpose and appears to only read local OpenClaw/Clawdbot session logs, store aggregates in a local SQLite DB, and render images via a headless browser. Before installing, consider: 1) The install step invokes pip and will download packages from PyPI (network activity during install). 2) The rendering dependency (html2image) requires Chromium; ensure you trust/verify the Chromium binary and/or the system package source. 3) The skill reads files under ~/.openclaw and ~/.clawdbot—confirm you are comfortable with local session logs being parsed and stored in the skill's workspace. 4) The skill's package.json references a GitHub repo but the registry source is 'unknown'—if provenance matters, manually review the upstream repository for additional context. If any of those points are unacceptable, review the code locally (it is included) before running, or run it in a restricted environment.
功能分析
Type: OpenClaw Skill Name: usage-visualizer Version: 1.1.3 The skill is classified as suspicious due to a potential arbitrary file write vulnerability in `scripts/generate_report_image.py` if the `--output` argument were user-controlled, and the heavy dependency on Chromium for image rendering, which significantly expands the attack surface. While the agent's execution flow (via `scripts/run_usage_report.py`) mitigates the arbitrary file write by constraining output to `OPENCLAW_WORKSPACE` or the project root, and the HTML content for rendering is generated locally without external network calls, these factors introduce meaningful risks. There is no evidence of intentional malicious behavior like data exfiltration or persistence.
能力评估
Purpose & Capability
Name/description match the code and runtime requirements: the scripts parse local OpenClaw/Clawdbot session JSONL files, compute token/cost metrics, persist to a local SQLite DB, and render PNG reports using a headless Chromium via html2image. Required binaries (python3, chromium) and the OPENCLAW_WORKSPACE env var are used by the code.
Instruction Scope
SKILL.md runtime instructions are narrowly scoped to syncing session logs, generating reports, and delivering images via the agent message tool. The scripts read filesystem session logs (under ~/.openclaw and ~/.clawdbot) and a local SQLite DB; they do not contain code that transmits data over the network or access unrelated system credentials.
Install Mechanism
This is an instruction-and-script skill with a pip install step (pip3 install -r requirements.txt). Installing will fetch dependencies from PyPI (network access during install). The runtime claims '100% local' and 'No External Calls', which is true at runtime, but the install step itself will contact PyPI. Also html2image or its dependencies can sometimes pull or require a local browser binary; the skill requires chromium to be present but some html-rendering libraries may attempt downloads if not found. This is expected for this functionality but worth noting.
Credentials
Only OPENCLAW_WORKSPACE is requested and is used as the workspace/storage path. No credentials or unrelated secrets are required. The code reads user session log files (which may contain metadata about sessions) but only extracts usage/token counts and model names in the shown logic; it does not request API keys or other external credentials.
Persistence & Privilege
The skill creates a local SQLite database and other report files under the workspace (default ~/.llm-cost-monitor or OPENCLAW_WORKSPACE). It does not request always:true and does not modify other skills' configurations. This level of persistence and file creation is appropriate for the described functionality.
如何使用
  1. 确保已安装 OpenClaw(本地或 Docker 部署)
  2. 在对话框中输入安装命令:/install usage-visualizer
  3. 安装完成后,直接呼叫该 Skill 的名称或使用 /usage-visualizer 触发
  4. 根据 Skill 的参数说明提供必要输入,即可获得结构化输出
版本历史
v1.1.3
v1.1.3: Privacy Clarity. Renamed all internal api_key references to source_id to avoid audit confusion. Explicitly verified no credentials are stored.
v1.1.2
v1.1.2: 100% Purity. Removed all legacy external API references, unified reporting logic, and eliminated unused jq dependency.
v1.1.1
v1.1.1: Complete privacy overhaul. Removed requests dependency and all external webhook mentions. Aligned metadata with actual implementation.
v1.1.0
v1.1.0: Secure Delivery Protocol, JSON output, and mandatory path verification.
v1.0.3
Improve trigger behavior for 用量汇报/用量统计 and add one-step auto-sync report runner.
v1.0.2
Address review: add privacy docs, fix missing dependencies (html2image, Pillow), unify package metadata
v1.0.1
Fixed: Removed redundant generated images from assets/ and cleaned up project root.
v1.0.0
Major release: renamed from llm-cost-monitor to usage-visualizer, focused on high-fidelity visual reporting, token analytics, and efficiency metrics.
元数据
Slug usage-visualizer
版本 1.1.3
许可证
累计安装 2
当前安装数 2
历史版本数 8
常见问题

Usage Visualizer 是什么?

Advanced usage statistics and high-fidelity visual reporting for OpenClaw. 100% local processing. Audit-verified privacy (No credentials stored). 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件,目前累计下载 871 次。

如何安装 Usage Visualizer?

在 OpenClaw 或 Claude Code 对话框中运行命令「/install usage-visualizer」即可一键安装,无需额外配置。

Usage Visualizer 是免费的吗?

是的,Usage Visualizer 完全免费(开源免费),可自由下载、安装和使用。

Usage Visualizer 支持哪些平台?

Usage Visualizer 跨平台运行,可在任意部署了 OpenClaw / Claude Code 的环境中使用(darwin, linux)。

谁开发了 Usage Visualizer?

由 Vint(@vintlin)开发并维护,当前版本 v1.1.3。

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