Cost Estimation¶
pytest-skill-engineering estimates the USD cost of each LLM call based on token counts and model pricing data. Costs appear in reports, eval leaderboards, and AI insights analysis.
How It Works¶
Cost estimation uses pricing.toml files. If no pricing is found, the cost is $0.00 and the model is flagged as missing. AI insights are automatically warned when any model lacks pricing, so cost-based recommendations are skipped.
pricing.toml Configuration¶
Create a pricing.toml file in your project root (or any parent directory) to add pricing for your models:
# Per-million-token pricing.
[models]
"gpt-5-mini" = { input = 0.15, output = 0.60 }
"gpt-4.1-mini" = { input = 0.30, output = 1.20 }
"claude-sonnet-4" = { input = 3.00, output = 15.00 }
Format¶
| Field | Type | Description |
|---|---|---|
input |
float | Cost per 1 million input tokens (USD) |
output |
float | Cost per 1 million output tokens (USD) |
Lookup Behavior¶
pricing.tomlis searched upward from the working directory- The first file found is used
- The file is loaded once and cached for the test session
Missing Pricing¶
When a model has no pricing:
- Cost is reported as
$0.00 - The model is tracked internally
- AI insights receive a warning: "Incomplete Pricing Data — do not use cost as a ranking factor"
- The AI analysis focuses on pass rate, tool usage, and response quality instead