How does the advisor calculate the recommended model?

It uses a weighted composite scoring formula that evaluates task complexity, tool usage intensity, context window requirements, message volume, autonomy level, and data sensitivity.

Can I use this for free models only?

Yes, the tool identifies high-quality free models like Qwen3 and Llama 3.3, though it will provide warnings if a free model is unsuitable for high-frequency or production tasks.

What files does the advisor need to perform an audit?

The skill scans your OpenClaw agent directories for configuration and instruction files, specifically SOUL.md, AGENTS.md, IDENTITY.md, and openclaw.json.

Does it support the latest 2026 AI models?

Yes, the advisor is pre-configured with the latest model data and pricing from early 2026, including models like Claude 4.6, GPT-5.4, and Gemini 3.1.

OpenClaw Model Advisor

Name: OpenClaw Model Advisor
Author: TheophilusChinomona

byTheophilusChinomona

0•

Ciencia de Datos y ML

Audits OpenClaw agents to recommend the most cost-effective and capable OpenRouter models based on specific task requirements.

The OpenClaw Model Advisor is a specialized skill for Claude Code designed to optimize your OpenClaw self-hosted AI gateway. It systematically analyzes your agents across six key dimensions—complexity, tool intensity, context window needs, response volume, autonomy level, and data sensitivity—to match them with the perfect OpenRouter model. Whether you are looking for free testing models or high-performance premium tiers, this tool provides detailed audit reports and ready-to-paste JSON configuration snippets to streamline your AI infrastructure management.

Características Principales

01Smart override rules for high-sensitivity data and autonomous heartbeat agents

02Tiered OpenRouter model recommendations spanning Free, Budget, Mid, and Premium tiers

03Multi-dimensional agent auditing using a 6-point requirement scoring system

040 GitHub stars

05Automated generation of ready-to-paste openclaw.json configuration snippets

06Comprehensive cost estimation and comparative model analysis reports

Casos de Uso

01Finding cheaper model alternatives for high-volume automated background agents

02Auditing an entire OpenClaw workspace to ensure model-task alignment and cost efficiency

03Selecting the most reliable tool-calling models for complex agentic workflows

Características Principales

01Smart override rules for high-sensitivity data and autonomous heartbeat agents

02Tiered OpenRouter model recommendations spanning Free, Budget, Mid, and Premium tiers

03Multi-dimensional agent auditing using a 6-point requirement scoring system

040 GitHub stars

05Automated generation of ready-to-paste openclaw.json configuration snippets

06Comprehensive cost estimation and comparative model analysis reports

Casos de Uso

01Finding cheaper model alternatives for high-volume automated background agents

02Auditing an entire OpenClaw workspace to ensure model-task alignment and cost efficiency

03Selecting the most reliable tool-calling models for complex agentic workflows