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model-switchboard型号总机

Agent Skill

model-switchboard 用于查找、检索和筛选相关信息,适合在 OpenClaw 中需要根据关键词、任务场景或来源线索快速定位候选结果时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

11,310

周安装

462

GitHub Stars

公开资料未说明

下载量

3,622
OpenClaw

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

MIT-0

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:model-switchboard(型号总机)
来源仓库:https://github.com/frank-bot07/model-switchboard
安装命令:
openclaw skills install model-switchboard
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 OpenClaw 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

ClawHubOpenClaw
openclaw skills install model-switchboard

简介

通过验证角色、自动加载备份、阻止不安全的更改以及通过 CLI 或 Canvas UI 进行管理,安全地配置 OpenClaw AI 模型。

SKILL.md

Model Switchboard v3.0 — Safe AI Model Configuration for OpenClaw

HARD RULE: NEVER edit openclaw.json model fields directly. Always use this skill's commands. No exceptions. Ever.

Why This Exists

Editing openclaw.json directly for model changes is the #1 cause of OpenClaw gateway crashes. Wrong model type in wrong slot = instant death. No backup = hours rebuilding. This skill eliminates that entirely.

How It Works

  1. Validates model format and role compatibility before any change
  2. Auto-backs up config before every modification (30 rolling backups)
  3. Uses OpenClaw CLI (openclaw models set) — never raw JSON
  4. Blocks unsafe assignments (image-gen model as primary LLM = blocked)
  5. Instant rollback if anything goes wrong
  6. Canvas UI for visual model management

Quick Reference

SWITCHBOARD="$SKILL_DIR/scripts/switchboard.sh"

# View current setup
$SWITCHBOARD status

# Change models
$SWITCHBOARD set-primary "anthropic/claude-opus-4-6"
$SWITCHBOARD set-image "google/gemini-3-pro-preview"
$SWITCHBOARD add-fallback "openai/gpt-5.2"
$SWITCHBOARD remove-fallback "openai/gpt-5.2"
$SWITCHBOARD add-image-fallback "openai/gpt-5.1"

# Preview before applying
$SWITCHBOARD dry-run set-primary "openai/gpt-5.2"

# Discovery & recommendations
$SWITCHBOARD discover          # List all available models
$SWITCHBOARD recommend         # Get optimal suggestions

# Redundancy (3-deep failover)
$SWITCHBOARD redundancy        # Assess current redundancy
$SWITCHBOARD redundancy-deploy # Preview optimal config
$SWITCHBOARD redundancy-apply  # Apply optimal config
$SWITCHBOARD redundancy-apply 4  # Custom depth

# Backup & restore
$SWITCHBOARD backup            # Manual backup
$SWITCHBOARD list-backups      # Show all backups
$SWITCHBOARD restore latest    # Undo last change

# Import/Export (portable model configs)
$SWITCHBOARD export config.json
$SWITCHBOARD import config.json

# Cron model validation
$SWITCHBOARD validate-cron-models  # Check cron jobs use valid models

# Diagnostics
$SWITCHBOARD health            # Gateway + provider status
$SWITCHBOARD validate <model> <role>  # Test compatibility

Model Roles

RolePurposeConfig Key
PrimaryMain LLM for all conversationsagents.defaults.model.primary
FallbackOrdered backup LLMsagents.defaults.model.fallbacks
ImageVision/image processingagents.defaults.imageModel.primary
Image FallbackBackup vision modelsagents.defaults.imageModel.fallbacks
HeartbeatLow-cost polling modelagents.defaults.heartbeat.model
CodingSub-agent code generationSpawn-time model param

Validation Rules

The validation engine (scripts/validate.py) enforces:

  • Format: Must be provider/model-name (e.g., anthropic/claude-opus-4-6)
  • Capability match: LLM roles require llm + tools capabilities
  • Image roles: Require vision capability
  • Hard blocks: Image-generation-only models (DALL-E, Stability) blocked from ALL LLM roles
  • Registry warnings: Unknown models get a caution warning but are allowed (for OpenRouter/new models)

Known Providers

  • anthropic — Claude family (Opus, Sonnet, Haiku)
  • openai — GPT family
  • openai-codex — Codex OAuth models
  • google — Gemini family
  • opencode — Zen proxy (routes to various models)
  • zai — GLM family
  • xai — Grok family
  • openrouter — Multi-provider gateway
  • groq, cerebras — Fast inference

Canvas UI

To show the visual dashboard:

# Get UI data
DATA=$($SWITCHBOARD ui)

# Present via canvas
# The UI reads window.__switchboardData JSON

The Canvas UI at ui/index.html shows:

  • Primary LLM and Image model with color coding
  • Fallback chains (ordered)
  • Provider auth status (green/red indicators)
  • Model allowlist
  • Config issues with severity levels
  • Backup count

For Agents: Operating Protocol

When a user asks to change model assignments:

  1. Read this SKILL.md first
  2. Show current status: $SWITCHBOARD status
  3. Preview the change: $SWITCHBOARD dry-run <action> <model>
  4. Confirm with user before applying
  5. Apply: $SWITCHBOARD <action> <model>
  6. Verify: Check gateway health after change

NEVER:

  • Edit openclaw.json directly for model fields
  • Skip the dry-run for primary model changes
  • Apply without user confirmation
  • Ignore validation failures

Troubleshooting

Gateway won't start:

$SWITCHBOARD restore latest
openclaw gateway restart
# Or: openclaw doctor --fix

"Model is not allowed" error: Model isn't in the allowlist. Add it or clear the list:

openclaw config set 'agents.defaults.models."provider/model"' '{"alias":"Name"}'
# Or clear: openclaw config unset agents.defaults.models

Unknown model warning: The model isn't in model-registry.json. Add it for future validation:

# Edit model-registry.json to add the model entry

File Structure

model-switchboard/
├── SKILL.md              # This file — agent instructions
├── README.md             # ClawHub publishing readme
├── model-registry.json   # Known model capabilities database
├── scripts/
│   ├── switchboard.sh    # Main CLI tool (bash)
│   └── validate.py       # Validation engine (python3, no deps)
└── ui/
    └── index.html        # Canvas dashboard (single-file, no deps)

适合场景

01

调用多模型

02

代码和文本生成

03

Agent 推理流程

04

OpenRouter 模型接入

能力概览

能力 1

统一调用多种 LLM

能力 2

支持 Claude、Gemini、Kimi 等模型

能力 3

适合聊天、代码和推理任务

能力 4

可作为 Agent 模型调用入口

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

OpenClaw

70.13%
按下载量换算2,540

安全审计

VirusTotal

通过

ClawScan

通过

Static analysis

未展示

权限和风险

执行命令

安装流程涉及命令执行,可能通过 openclaw skills install model-switchboard 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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