A cost-saving routing system that automatically directs tasks to the most efficient Claude model tier based on task complexity.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install smart-model-switching
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install smart-model-switching using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is Smart Model Switching?
Smart Model Switching is a sophisticated task-routing protocol designed for AI agents using the Claude model family. By implementing a three-tier progression system (Haiku, Sonnet, and Opus), this skill ensures that simple tasks are handled by the most cost-effective model, while complex reasoning and architecture decisions are escalated to high-intelligence tiers only when necessary. This strategy is essential for developers using Openclaw Skills who want to maximize performance while minimizing operational expenses.
This skill eliminates the common waste associated with using high-powered models for trivial tasks like status checks or factual lookups. By applying a classification layer before execution, the system maintains high output quality and only utilizes premium compute resources when the complexity of the task genuinely warrants it, potentially saving users between 50% and 90% on total API expenditures.
Smart Model Switching Use Cases
- Reducing API overhead for routine status checks, session monitoring, and system heartbeats.
- Scaling complex coding projects by delegating boilerplate generation to Haiku and logic implementation to Sonnet.
- Managing expensive Opus usage exclusively for high-level architectural, security, and strategic decisions within Openclaw Skills.
- Automating factual lookups, unit conversions, and casual conversational interactions with minimal financial impact.
How Smart Model Switching Works
- The system performs an initial classification step to evaluate the complexity of the incoming prompt.
- Routine tasks such as greetings, simple file operations, or factual Q&A are immediately routed to the Haiku tier.
- The system applies the 30-second rule: if a human would need more than 30 seconds of focused thinking, the task is escalated to Sonnet.
- For specialized tasks involving multi-file refactoring, deep research, or database schema design, the workflow escalates to the Opus tier.
- Subagents are dynamically spawned with the appropriate model parameter to ensure the most efficient execution path.
Smart Model Switching Setup
To integrate Smart Model Switching into your workflow, you must configure your subagent spawning logic and cron payloads to specify the model tier. Use the following bash-style implementation logic for your Openclaw Skills environment:
# Example of triggering a simple status check
# model: "haiku"
# Example of triggering a complex refactor
# model: "sonnet" or "opus"
For JavaScript-based subagent management:
// Routine monitoring using the cheapest tier
sessions_spawn(task="Check backup status", model="haiku")
// Standard technical work
sessions_spawn(task="Build the REST API endpoint", model="sonnet")
Smart Model Switching Data Schema & Taxonomy
The skill organizes routing logic based on task complexity tiers and relative cost mapping. Data is categorized by the following technical specifications:
| Model Tier | Primary Function | Cost Multiple | Trigger Condition |
|---|---|---|---|
| Haiku | Basic Q&A / Ops | 1x (Baseline) | < 2 sentence answers |
| Sonnet | Standard Coding | 12x | Code > 10 lines, Analysis |
| Opus | Architecture / Strategy | 60x | Multi-file reasoning |
Metadata is processed through a decision tree that evaluates if a task requires architecture decisions, nuanced judgment, or standard multi-step reasoning.
Smart Model Switching Advanced Features
- Intelligent three-tier progression logic (Haiku → Sonnet → Opus) to prevent over-provisioning of AI resources.
- Dynamic subagent spawning with specific model overrides for high-precision workflows in Openclaw Skills.
- Pre-defined 'Never Haiku' list to automatically escalate complex tasks like multi-step analysis or long-form report writing.
- Automated cron job optimization using Haiku as the default heartbeat and monitoring model.
SKILL.md
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