A specialized tool for fetching, unifying, and calculating standardized pricing ratios across multiple AI model providers and API platforms.
The fastest way to install a skill directly from the registry.
npx clawhub@latest install model-pricing-calculator
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
Copy this prompt to OpenClaw to install it automatically.
Help me install model-pricing-calculator using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Get the raw skill files in a ZIP archive.
The Model Pricing Calculator is a robust utility designed to solve the complexity of managing disparate pricing structures from various AI API aggregation platforms. By leveraging Openclaw Skills, this tool fetches raw pricing data and converts it into a unified system of model ratios, completion ratios, and group ratios based on a consistent base price of $0.002 per 1K tokens.
This skill ensures that developers can maintain a single source of truth for model costs, even when the same model is offered by different providers at varying price points. It handles the heavy lifting of reverse-calculating ratios from target prices and provides detailed snapshot comparisons to track pricing changes over time.
To get started with this component of Openclaw Skills, ensure you have Python installed and configure your provider URLs.
# 1. Update your platform URLs in references/pricing_urls.json
# 2. Run the calculation script to generate the first snapshot
python scripts/fetch_and_calculate.py
# 3. Filter for specific models or groups as needed
python scripts/fetch_and_calculate.py --models "gpt-4*,claude-*"
The skill organizes pricing data into a three-tier hierarchy to ensure granular control over costs:
| Component | Description | Calculation Logic |
|---|---|---|
| Model Ratio | Base cost multiplier for a specific model | InputPrice / 0.002 |
| Completion Ratio | Multiplier for output tokens vs input tokens | OutputPrice / InputPrice |
| Group Ratio | Platform-specific adjustment factor | Applied to final cost |
All data is persisted in data/latest_snapshot.json to allow for historical diffing and state management.
gpt-4*) to perform targeted updates.Loading
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