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Julia's OpenClaw Token Optimizer
作者
Aaron Daley
· GitHub ↗
· v1.0.0
· MIT-0
31
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0
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0
当前安装
1
版本数
在 OpenClaw 中安装
/install julia-openclaw-token-optimizer
功能描述
Automation skill for Julia's OpenClaw Token Optimizer.
使用说明 (SKILL.md)
name: julia-openclaw-token-optimizer description: Julia's OpenClaw Token Optimizer: Scans LLM prices, benchmarks models, patches config for cheapest optimal. Use for cost optimization, model rotation.
Usage
- session_status → current model/cost.
- web_search 'current LLM pricing [provider] input/output per million tokens'.
- gateway config.schema.lookup 'agents.defaults.modelSelection'.
- Benchmark: spawn subagent with test prompts on cheap models.
- Recommend: Cost/speed/quality matrix.
- gateway config.patch {modelSelection: {primary: 'best-cheap-model'}}.
References: providers.md for price APIs.
Optimization Rules
- Prefer fast/cheap for simple tasks.
- Quality for creative/complex.
- Rotate on rate limits.
Example: 'Optimize my config for cheap reasoning' → Search prices, patch.
安全使用建议
Review this skill before installing if you do not want an agent to edit your default model configuration. If you use it, ask it to provide pricing sources, benchmark results, the proposed config diff, expected cost/quality tradeoffs, and rollback steps before any patch is applied.
功能分析
Type: OpenClaw Skill
Name: julia-openclaw-token-optimizer
Version: 1.0.0
The skill is designed to optimize LLM costs by searching for pricing data and updating OpenClaw configurations. While it utilizes the 'gateway config.patch' capability to modify system settings, this behavior is explicitly documented and aligned with its stated purpose in SKILL.md and clawhub.json. No evidence of data exfiltration, malicious prompt injection, or unauthorized access was found.
能力评估
Purpose & Capability
The stated purpose of scanning LLM prices, benchmarking models, and optimizing token cost is coherent with the instructions, but it includes changing the agent's model-selection configuration.
Instruction Scope
The workflow makes config patching the final step after price search and recommendation, without explicitly requiring user confirmation, showing a diff, limiting benchmark cost, or documenting rollback.
Install Mechanism
This is an instruction-only skill with no install spec, binaries, environment variables, or code files; the static scanner had nothing executable to analyze.
Credentials
Changing agents.defaults.modelSelection can alter future agent behavior beyond the immediate optimization task, and spawning subagents may incur model usage cost unless bounded.
Persistence & Privilege
The skill uses persistent configuration-write authority, but the metadata declares no required config paths or capability tags.
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 julia-openclaw-token-optimizer - 安装完成后，直接呼叫该 Skill 的名称或使用
/julia-openclaw-token-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
v1.0.0 Initial: Price scan, model benchmark, config auto-patch. Free.
元数据
常见问题
Julia's OpenClaw Token Optimizer 是什么？
Automation skill for Julia's OpenClaw Token Optimizer. 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 31 次。
如何安装 Julia's OpenClaw Token Optimizer？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install julia-openclaw-token-optimizer」即可一键安装，无需额外配置。
Julia's OpenClaw Token Optimizer 是免费的吗？
是的，Julia's OpenClaw Token Optimizer 完全免费，采用 MIT-0 许可证，可自由下载、安装和使用。
Julia's OpenClaw Token Optimizer 支持哪些平台？
Julia's OpenClaw Token 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 Julia's OpenClaw Token Optimizer？
由 Aaron Daley（@aaronmda）开发并维护，当前版本 v1.0.0。
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