> For the complete documentation index, see [llms.txt](https://docs.walnutai.ai/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.walnutai.ai/reports-and-analytics/reports.md).

# Reports

The **Reports** module in WalnutAI provides a centralized view of all test execution activity across your project. It captures and organizes execution results, logs, screenshots, performance data, and diagnostic details into a structured reporting interface.

Every time a test case or test suite is executed whether manually or through automation WalnutAI automatically generates a unique **Test Run ID** and records the complete execution history. This ensures full visibility, traceability, and accountability for every run.

The Reports module acts as the single source of truth for monitoring execution health and validating release readiness.

**Why Use Reports?**

The Reports module plays a critical role in quality monitoring and release validation:

* **Execution Visibility:** View the status of all test runs in one place.
* **Failure Investigation:** Access step-level logs, screenshots, and error details to quickly identify root causes.
* **Release Validation:** Review pass/fail trends before approving a build.
* **Trend Analysis:** Monitor stability over time and detect patterns in recurring failures.
* **Audit & Traceability:** Maintain a permanent execution history for compliance and tracking.

Reports enable teams to make informed, data-driven decisions by transforming raw execution data into clear and actionable insights.


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