Track consumption
Review total, input, output, and cached input tokens for the date range you choose.
Find usage drivers
Break token usage down by model, workflow, step, or agent depending on the dashboard you are viewing.
Investigate runs
Open high-usage executions from dashboards or lists to inspect run-level and step-level token counts.
Compare periods
Use previous-period context to see whether token consumption is rising or falling for the same length of time.
Overview
Token usage analytics are available in the places where you monitor workflow activity:- The Project Dashboard shows project-wide LLM usage across all workflows in the project.
- A Workflow Dashboard narrows the same kind of analysis to one workflow.
- The Executions list helps you sort runs by token usage.
- Workflow run details show the token totals behind a specific run and its steps.
Where token usage appears
Project Dashboard
The Project Dashboard is the best starting point for project-wide LLM usage. It aggregates token usage across the selected date range and includes:- Total Tokens: all provider-reported LLM tokens used by the project during the selected period.
- Input Tokens: tokens sent to LLMs as prompts, instructions, context, and tool-related input.
- Output Tokens: tokens generated by LLMs in responses.
- Cached Input: the portion of input tokens served from cache when cache data is available. This is a subset of Input Tokens, not an additional amount on top of them.
- LLM Calls: the number of LLM requests represented in the selected period.
- Previous-period comparisons: context for how the selected period compares with the immediately preceding period of the same length.
- Token trends: usage over time based on the selected date range and grouping.
- Token Usage Breakdown: usage grouped by Model, Workflow, or Agent.
- Heaviest Executions: a leaderboard of runs with the highest total token usage in the selected period.
- Which workflows are responsible for most token usage this week?
- Did usage rise compared with the previous period?
- Are specific models or agents driving the increase?
- Which executions should I inspect first?
Workflow Dashboard
A Workflow Dashboard focuses token analytics on one workflow. Use it after you identify a workflow that needs closer review from the Project Dashboard. Workflow-scoped analytics include token KPI cards, token trends for the selected date range, and breakdowns by Model, Step, and Agent. This helps you distinguish whether usage comes from a specific model choice, a step in the workflow, or an agent assigned to the workflow.Executions list
The Executions list includes a sortable Tokens column. The column shows output token usage for each run, which makes it useful for finding runs that produced unusually large LLM responses. Sort by Tokens when you want to move from dashboard-level trends to the specific runs behind them.Workflow run details
Workflow run details show token usage for a single execution. The run summary includes output token usage, with expandable details for:- Input Tokens
- Cached Input
- Output Tokens
- Total Tokens
- LLM Calls
Choose a date range
Dashboard analytics follow the selected Date Range. Available presets include:- Today
- Last 7 Days
- Last 30 Days
- Last 90 Days
- This Month
- Day for daily changes and short ranges.
- Week for medium-term usage patterns.
- Month for longer ranges and month-to-month review.
Selecting Last 7 Days from the Date Range control uses the same date window as the default Last 7 Days dashboard view. This keeps analytics consistent when you compare initial dashboard data with the same preset selected later.
Understand token metrics
| Metric | What it means | How to use it |
|---|---|---|
| Total Tokens | The combined token usage reported for LLM calls in the selected scope. | Use it as the headline consumption number for a project, workflow, model, agent, step, or run. |
| Input Tokens | Tokens sent to LLMs as instructions, context, and prompts. | Watch for large context windows or workflows that send more information than needed. |
| Output Tokens | Tokens generated by LLMs in responses. | Use it to find runs or steps where agents produced long answers, summaries, or code changes. |
| Cached Input | The portion of Input Tokens served from cache when cache data is available. It is a subset of Input Tokens, not an amount added on top of them. | Compare with Input Tokens to understand how often repeated context is reused. |
| LLM Calls | The number of LLM requests included in the selected scope. | Use it to distinguish frequent small calls from fewer large calls. |
Break down token usage
Use the Token Usage Breakdown panel to identify what contributes most to consumption.By Model
Group by Model to compare token usage across LLM models. This view is useful when you want to confirm whether a high-capacity model is responsible for a spike or whether usage is spread across several models. When model rows include System or Custom labels, use them to distinguish Overcut-provided model options from models configured by your workspace.By Workflow
Group by Workflow on the Project Dashboard to see which workflows use the most tokens across the selected date range. Start here when you are reviewing project-level usage or looking for candidates to optimize.By Agent
Group by Agent to understand which agent roles are associated with the most token usage. This can highlight agents that need tighter instructions, narrower context, or a workflow design review.By Step
Use the Workflow Dashboard to break a single workflow down by Step. This is the most direct way to find where token-heavy work happens inside one automation.Investigate high-usage runs
Use this workflow when a dashboard shows unexpected token usage:Choose the right date range
Select the preset that matches the period you want to review. Use Group By on the Project Dashboard when you need a daily, weekly, or monthly trend.
Review Project Dashboard KPIs
Compare Total Tokens, Input Tokens, Output Tokens, Cached Input, and LLM Calls with the previous period.
Find the main driver
Use Token Usage Breakdown to group by Model, Workflow, or Agent. Sort your attention toward rows with the highest Total values.
Open a heavy execution
Use Heaviest Executions or sort the Executions list by Tokens to open a run that contributed to the spike.
Related documentation
- Workflows: Understand workflow structure, triggers, actions, and monitoring.
- Workflow Execution Control: Learn how Overcut manages queued and running workflows.
- LLM Models: Review model configuration and defaults.
- Workflow Builder: Configure workflow metadata, steps, and model settings.