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在 OpenClaw 中安装
/install token-use-optimizer
功能描述
AI Agent 项目的 Token 消耗审计与系统性优化。提供四层诊断框架、六步优化 SOP、 自动化审计脚本。适用于任何使用 Rules + Memory + Knowledge + Skills 架构的 AI Agent 项目（如 CodeBuddy、Cursor、Windsurf 等）。 This ski...
安全使用建议
This skill appears coherent: it bundles a Python auditor and documentation that match its stated goal of auditing Rules/Memory/Knowledge token costs. Before installing or running:
- Inspect SKILL.md and scripts/token_audit.py yourself (or have a developer do so). The included script reads files under the target project and prints a report — it does not perform network calls in the provided code, but executing arbitrary scripts can be risky.
- Run the script on a copy of your project, not on a production workspace containing secrets. The tool will read repository files (including MEMORY.md) and may output their contents or character counts.
- Pay attention to the pre-scan 'system-prompt-override' flag: search SKILL.md for any lines that try to change system prompts or inject agent/system-level instructions. If you find such lines, do not run the skill until they are removed or explained.
- Execute the script in a restricted environment (non-root user, ephemeral container) the first time to confirm behavior.
- If you rely on enterprise security policy, have your security/dev team review the Python file for any unexpected file writes or subprocess/network usage (the provided code appears to use only local file reads and standard libs).
If you want higher confidence, provide the exact SKILL.md frontmatter and the full, untruncated portion of scripts/token_audit.py print/report output for a quick line-by-line check.
功能分析
Type: OpenClaw Skill
Name: token-use-optimizer
Version: 1.0.0
The bundle provides a legitimate utility for auditing and optimizing token consumption in AI agent projects. It includes a Python script (scripts/token_audit.py) that performs local file system scanning of rules, memory, and knowledge files to estimate token overhead, and comprehensive documentation (SKILL.md, references/) providing optimization strategies. No evidence of data exfiltration, malicious execution, or harmful prompt injection was found; the script uses only standard libraries and lacks any network or unauthorized persistence capabilities.
能力评估
Purpose & Capability
Name/description, included audit script (scripts/token_audit.py) and reference docs directly support token auditing and optimization for Rules/Memory/Knowledge architectures; no unrelated binaries, env vars, or external services are requested.
Instruction Scope
SKILL.md instructs the agent/operator to run the included Python audit script against a project root and to follow the provided SOP — this stays within the stated purpose (scanning repo files and producing a report). However, the pre-scan flagged a 'system-prompt-override' pattern in the SKILL.md content; while the visible instructions do not explicitly attempt to change system prompts or exfiltrate data, you should inspect the SKILL.md frontmatter and triggers for any lines that try to override agent/system prompts or execute unexpected actions.
Install Mechanism
No install spec — instruction-only with a bundled Python script. There are no downloads from external URLs and the script uses only standard library modules; risk from installation is low. Executing the included script will run local Python code (review before execution).
Credentials
The skill requests no environment variables, no credentials, and no config paths. The audit script reads local project files (e.g., .codebuddy/rules, knowledge directories, .codebuddy/MEMORY.md) which is appropriate for a token-audit tool.
Persistence & Privilege
Skill is not always-enabled and does not request persistent agent privileges. It does not modify other skill configs or system-wide settings in the provided code or instructions.
如何使用
- 确保已安装 OpenClaw（本地或 Docker 部署）
- 在对话框中输入安装命令：
/install token-use-optimizer - 安装完成后，直接呼叫该 Skill 的名称或使用
/token-use-optimizer触发 - 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
v1.0.0
- Major restructure: the skill is now a comprehensive Token Optimization auditor and SOP for AI Agent projects.
- Adds a four-layer diagnostic framework (Rules, Memory, Knowledge, Runtime Behavior) with ROI-focused steps.
- Includes an automated token audit script (`scripts/token_audit.py`) for baselining and structured reporting.
- Provides step-by-step optimization strategies and an actionable decision tree.
- Adds two detailed reference files: `references/optimization-strategies.md` (full playbook) and `references/real-world-cases.md` (real cases).
- README removed; all guidance and instructions consolidated into SKILL.md and references.
元数据
常见问题
token-use-optimizer 是什么？
AI Agent 项目的 Token 消耗审计与系统性优化。提供四层诊断框架、六步优化 SOP、 自动化审计脚本。适用于任何使用 Rules + Memory + Knowledge + Skills 架构的 AI Agent 项目（如 CodeBuddy、Cursor、Windsurf 等）。 This ski... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 110 次。
如何安装 token-use-optimizer？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install token-use-optimizer」即可一键安装，无需额外配置。
token-use-optimizer 是免费的吗？
是的，token-use-optimizer 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
token-use-optimizer 支持哪些平台？
token-use-optimizer 跨平台运行，可在任意部署了 OpenClaw / Claude Code 的环境中使用（cross-platform）。
谁开发了 token-use-optimizer？
由 Louis Qiu（@louisecxqiu-glitch）开发并维护，当前版本 v1.0.0。
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