Update AI model pricing data and aliases in Splitrail.
npx skills add https://github.com/Piebald-AI/splitrail --skill pricing-piebald-ai
Please help me install this Agent Skill. Skill: pricing Source: https://github.com/Piebald-AI/splitrail/tree/main/.claude/skills/pricing Command: npx skills add https://github.com/Piebald-AI/splitrail --skill pricing-piebald-ai
Update and maintain accurate AI model pricing data in Splitrail.
Update the pricing data for a new AI model directly in the repository.
High-intent search queries and answers about installing and using this skill.
Update AI model pricing data in Splitrail by modifying the MODEL_INDEX with pricing, caching, and is_estimated fields. This ensures accurate cost tracking when adding new models or adjusting existing prices.
Manage model aliases by updating the MODEL_ALIASES mapping in the repository. This ensures correct alias resolution during cross-model cost comparisons and when utilizing models::calculate_total_cost() for estimates.
Yes, you can validate AI model pricing data against source references when updating the repository. This validation ensures flat-rate and tiered pricing structures remain accurate before utilizing cost calculation utilities.
Handle tiered pricing structures by updating the MODEL_INDEX with appropriate pricing and caching data. This approach supports accurate cost estimates when using models::calculate_total_cost() for cross-model comparisons.
Use models::calculate_total_cost() when you need cost estimates for AI models, particularly during cross-model cost comparisons. This function relies on accurate pricing data maintained in the MODEL_INDEX.
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