> ## Documentation Index
> Fetch the complete documentation index at: https://help.dash.fi/llms.txt
> Use this file to discover all available pages before exploring further.

# Dashboard sections

> Tour of the AI Spend Agent dashboard — Overview, Usage, Anomalies, Violations, Action Plan, and Recovery.

The AI Spend Agent dashboard is organized into sections you navigate from the left rail. Each section answers a different question: how much are you spending, where is it going, what's wrong, what to do about it, and what's been recovered.

<Note>
  Every section reflects the last 30 days of data pulled from your connected providers. To pull fresh data on demand, use [Sync now and Refresh insights](/integrations/ai-tokens/connect-providers).
</Note>

## Overview

Overview is the headline view: how much your team is spending on AI and how that's trending.

* **30-day spend** — Total cost across Anthropic and OpenAI over the last 30 days.
* **Tokens (30d)** — Total tokens consumed, split between input and output.
* **Cache-read rate** — Share of input tokens served from a prompt cache, plus the raw read vs. written token counts. High cache-read rates mean you're paying less for repeated context.
* **Models tracked** — How many distinct models the agent has seen usage from.
* **Daily spend chart** — Per-day spend bars with a 7-day moving average line to smooth out day-to-day noise.

Overview is the fastest way to spot a spend spike or a sudden drop in cache efficiency.

## Usage

Usage decomposes the same 30 days by dimension. Each section shows a spend-mix donut alongside a ranked table.

* **Spend by model** — Every model that produced cost in the window, with input, output, cache-write and cache-read tokens per model plus each model's share of total spend.
* **Spend by provider** — The same breakdown grouped by Anthropic vs. OpenAI.

Use Usage when Overview surfaces a change and you need to attribute it: which model got more expensive, which provider is driving the shift, and whether cache usage moved along with it.

## Anomalies

Anomalies collect behavioral and efficiency findings the agent produced from your usage. Each row is one finding, tied to a specific rule (e.g. `spend_spike_anomaly`, `cache_efficiency_outlier`, `model_overkill`, `stale_key_active`).

Categories covered here:

* **Usage patterns** — Spend spikes, off-hours usage.
* **Governance** — Stale keys, untagged keys, workspace concentration, subscription-cheaper opportunities.
* **Cache efficiency** — Cache-write overspend, cache-read opportunities, cache-efficiency outliers.
* **Model efficiency** — Over-powered model choices, low-output request bursts, tokens-per-request outliers.

You can filter findings by **severity** (high / medium / low), **date range**, and **category**. Click any row to expand it — you'll see the human-readable explanation, the attribution (model, key, workspace, or user where available), and the pricing basis the agent used.

## Violations

Violations are the disputable findings: billing and pricing discrepancies where the provider's charge doesn't match what pricing says it should have been. These findings can back a refund claim in [Recovery](/integrations/ai-tokens/recovery).

Categories covered here:

* **Billing** — Billing discrepancies (point-in-time and windowed), rate & discount summaries.
* **Pricing data** — Stale pricing entries, unknown-model observations.

Violations use the same filters and expand-for-detail interaction as Anomalies. Each finding is categorized into either Anomalies or Violations — a single finding never appears in both.

## Action Plan

The Action Plan is your prioritized to-do list. It takes every finding — anomalies and violations — and ranks them by **estimated dollar impact**, biggest first.

At the top of the page you'll see the total identified opportunity: the sum of estimated impact across every open finding. Each item shows the finding title, its severity, the human explanation, and its individual impact. Work top-down to pick up the highest-value fixes first.

<Note>
  Refund claims aren't tracked on Action Plan. Anything that can be recovered as a refund lives in [Recovery](/integrations/ai-tokens/recovery) — Action Plan focuses on the optimization work you own.
</Note>

## Recovery

Recovery is the home for refund claims filed against billing violations. See [Recovery and refund claims](/integrations/ai-tokens/recovery) for the full walkthrough.