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SwitchBoard
作者
gigabit-eth
· GitHub ↗
· v1.0.2
714
总下载
2
收藏
5
当前安装
3
版本数
在 OpenClaw 中安装
/install router
功能描述
Cost-optimize AI agent operations by routing tasks to appropriate models based on complexity. Use this skill when: (1) deciding which model to use for a task...
安全使用建议
This skill appears coherent and does what it says: pick cost-appropriate OpenRouter models. Before installing: (1) confirm you trust the skill source (homepage/repo in metadata point to a third-party project — verify ownership if you need provenance), (2) only store your OPENROUTER_API_KEY in ~/.openclaw/openclaw.json with strict permissions (600) as suggested, (3) avoid routing sensitive secrets/PII to free or unmoderated models (the skill already warns about this), (4) remember this skill will cause the agent to call openrouter.ai endpoints at runtime, so review OpenRouter’s privacy/policy for any chosen model, and (5) because the package is instruction-only there is no bundled executable, but the agent will act on its routing rules — if you want stricter control, limit the skill to manual invocation rather than autonomous agent flows.
功能分析
Type: OpenClaw Skill
Name: router
Version: 1.0.2
The OpenClaw AgentSkills bundle is benign. It transparently declares its purpose of cost-optimizing AI agent operations by routing tasks to different models via the OpenRouter API. The `SKILL.md` provides clear instructions to the agent for model selection without any malicious prompt injection attempts. All required API keys (`OPENROUTER_API_KEY`) and network endpoints (`https://openrouter.ai/api/*`) are explicitly declared in `manifest.json` and `skill.json`. The skill contains no custom executable code, binaries, or external dependencies, and responsibly warns users about potential privacy implications of third-party models it might route to.
能力评估
Purpose & Capability
Name/description (model routing, cost optimization) align with requested artifacts: an OpenRouter API key, model catalog files, and routing logic in SKILL.md. The large references/openrouter-models.* files are consistent with a routing/reference skill.
Instruction Scope
SKILL.md is instruction-only and tells the agent to read/store the OpenRouter key in ~/.openclaw/openclaw.json and to route tasks based on complexity. Instructions remain within routing scope and explicitly warn not to send secrets to unmoderated/free models. Note: it will direct runtime calls to openrouter.ai if used, and the skill relies on model metadata in the included reference files.
Install Mechanism
No install spec or code is provided (instruction-only), so nothing is downloaded or installed by the skill itself. This minimizes disk-write/exec risk.
Credentials
Only one credential is declared (OPENROUTER_API_KEY) and its use is justified by the skill's purpose. The manifest documents the config path (~/.openclaw/openclaw.json) and recommended file perms (600). No unrelated secrets or multiple credentials are requested.
Persistence & Privilege
The skill is not always-enabled and is user-invocable. It does not request elevated persistence or modify other skills; declared persistence is limited to the user's OpenClaw config file for the API key.
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 router - 安装完成后，直接呼叫该 Skill 的名称或使用
/router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
v1.0.2
- Added manifest.json and skill.json files for improved metadata and compatibility.
- Updated documentation to include a privacy note about model logging and a warning not to route sensitive data through free/unmoderated models.
- No changes to routing logic or classification guidance.
v1.0.1
- Added: OpenRouter API KEY Prequisite
- Tighter documentation integration
- Optimized control flow logic
v1.0.0
Initial release: introduces a structured approach for cost-efficient AI model selection by routing tasks based on complexity.
- Defines a three-tier model hierarchy (Routine, Moderate, Complex) linked to cost ranges and suitable tasks.
- Provides classification rules, example model assignments, and decision algorithms for task-to-model routing.
- Outlines best practices and anti-patterns for main sessions, sub-agents, and automated tasks.
- Includes integration examples for common agent frameworks.
- Details the cost impact and recommended usage splits for optimal budget management.
元数据
常见问题
SwitchBoard 是什么？
Cost-optimize AI agent operations by routing tasks to appropriate models based on complexity. Use this skill when: (1) deciding which model to use for a task... 它是一个面向 Claude Code / OpenClaw 的 AI Agent Skill 插件，目前累计下载 714 次。
如何安装 SwitchBoard？
在 OpenClaw 或 Claude Code 对话框中运行命令「/install router」即可一键安装，无需额外配置。
SwitchBoard 是免费的吗？
是的，SwitchBoard 完全免费（开源免费），可自由下载、安装和使用。
SwitchBoard 支持哪些平台？
SwitchBoard 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 SwitchBoard？
由 gigabit-eth（@gigabit-eth）开发并维护，当前版本 v1.0.2。
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