Model Switcher

Automatically switch between different AI models based on task complexity. Supports all available models in your OpenClaw setup. Triggers when detecting comp...

Security Scan

The skill's requests and instructions are consistent with its stated purpose (auto-switching models based on task complexity); no disproportionate permissions, installs, or secret access are requested.

Purpose & Capability

Name/description (auto-switching between fast vs powerful models) match the SKILL.md's detection rules and explicit session_status calls to change models. There are no unrelated environment variables, binaries, or installs requested.

Instruction Scope

Instructions are narrowly scoped to detecting keywords and calling the session_status tool to change models. Minor issues: trigger keywords are only provided in Chinese (may miss other languages), and the implementation examples use short model identifiers ("kiro-cli", "haiku", "default") that do not exactly match the full model strings listed earlier (e.g., "custom-kiro-cli-vipdump-eu-org/claude-haiku-4-5"), which is an operational inconsistency but not a security problem. The doc also leaves behavioral choices (how often to switch, batching) to agent discretion; this is functional scope rather than a covert action.

Install Mechanism

Instruction-only skill with no install spec and no code files. Nothing is written to disk or downloaded by an installer, which minimizes install-time risk.

Credentials

No environment variables, credentials, or config paths are requested. The skill does reference custom model names (hosted models) — users should be aware that switching uses whatever models are available in their environment, but the skill itself doesn't request secrets or unrelated credentials.

Persistence & Privilege

always is false and autonomous invocation is allowed (the platform default). The skill does not request persistent system presence or access to other skills' configs. Autonomous invocation combined with no credential access is low risk.

Assessment

This skill appears to do what it says: detect complexity and call session_status to switch models. Before installing, confirm that your agent platform provides a session_status tool and determine the exact model identifiers it expects (the SKILL.md shows both full model names and shorter tokens — update them to match your environment). Consider adding trigger keywords in other languages if you need that coverage, and set sensible rate-limiting or batching to avoid frequent unnecessary switches. Also verify you trust the custom model endpoints listed (they appear to be custom-hosted model names) since switching will route requests to those models managed by whoever controls them.

Automatically detect task complexity and switch to the appropriate model.

Model Configuration

Based on your setup:

• Fast model (haiku): custom-kiro-cli-vipdump-eu-org/claude-haiku-4-5 - For simple, quick tasks
• Powerful model (sonnet): custom-kiro-cli-vipdump-eu-org/claude-sonnet-4-5 - For complex analysis

Trigger Keywords (Chinese)

Switch to sonnet when message contains:

• 分析、深入分析、详细分析
• 重构、代码重构
• 架构、系统架构、设计架构
• 设计、系统设计
• 优化、性能优化
• 复杂、复杂问题
• 调试、深度调试
• 评估、技术评估

Workflow

1. Check current model using session_status
2. Detect keywords in user message
3. Switch if needed:
   • Complex task detected + currently on haiku → switch to sonnet
   • Simple task + currently on sonnet → optionally switch back to haiku
4. Inform user briefly about the switch

Implementation

Use session_status tool with model parameter:

// Switch to sonnet for complex tasks
session_status({ model: "kiro-cli" })

// Switch back to haiku for simple tasks
session_status({ model: "haiku" })

// Reset to default
session_status({ model: "default" })

Example Detection Logic

User message: "帮我分析一下这个系统的架构"
→ Contains: "分析", "架构"
→ Action: Switch to sonnet if not already on it
→ Response: "🔄 切换到 sonnet 模型来处理这个复杂任务..."

Notes

• Be smart about switching - don't switch for every message
• Batch related complex tasks on sonnet before switching back
• Inform user only on actual switches, not when already on correct model
• Consider context: if already discussing complex topic, stay on sonnet