AI coding

Tracking and reconciling AI model spend

• Measuring Token Spend from Context Files and Skills
• Proxying Reservations for Sub-Agents on an Agent Platform
• A Broker Log Schema That Joins Reservations to Spend
• A Budget Dashboard: Traces, Spend and Stop Reasons Joined
• A Check Cost Ledger: Tokens, Time and Spend in One Table
• A Rejected Count: Logging the Preflight to Provider Gap
• A Shadow-Run Log Schema: Fields for Comparing Model Outputs
• How to Log an Agent Run So You Can Tell Where It Went Over
• Joining Check Costs to Model Spend in a Single Ledger
• Joining Check Estimates to Model Spend in One Ledger
• Joining Check Verdicts to Their Token Spend in One Ledger Schema
• Joining Judge-Call Spend to Retrieval Spend in One Ledger
• Joining Model Logs to the Invoice: Reconciling Spend
• Joining Reservation Logs to Spend: A Combined Query
• Joining Retry Counts to Model Spend per Task
• Joining Task Logs to Model Spend
• Keeping Cost Formulas Current When Rates Change
• Measuring the Cost of Review in Agent Tokens and Engineer Minutes
• Pricing an Internal Agent Service Back to the Teams That Use It
• Reading a Task Log for Patterns
• Sampling an Agent Task Log with Strata and Weights
• Tracing a Single Agent Task Across Providers
• Validating Your Tokenizer Against Provider Usage Counts
• When an Agent Opens a Second Session to Finish a Task
• When to Automate the Task Log