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Guide for updating model pricing in Splitrail. Use when adding new AI model costs or updating existing pricing data.

Piebald-AI By Piebald-AI schedule Updated 1/1/2026

name: pricing description: Guide for updating model pricing in Splitrail. Use when adding new AI model costs or updating existing pricing data.

Pricing Model Updates

Token pricing is defined in src/models.rs using compile-time phf (perfect hash function) maps for fast lookups.

Adding a New Model

  1. Add a ModelInfo entry to MODEL_INDEX (line 65 in src/models.rs) with:
    • pricing: Use PricingStructure::Flat { input_per_1m, output_per_1m } for flat-rate models, or PricingStructure::Tiered for tiered pricing
    • caching: Use the appropriate CachingSupport variant (None, OpenAI, Anthropic, or Google)
    • is_estimated: Set to true if pricing is not officially published
  2. If the model has aliases (date suffixes, etc.), add entries to MODEL_ALIASES mapping to the canonical model name

See existing entries in src/models.rs for the pattern.

Price Calculation

Use models::calculate_total_cost() when an analyzer doesn't provide cost data.

Common Pricing Sources

Install via CLI
npx skills add https://github.com/Piebald-AI/splitrail --skill pricing
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