> For the complete documentation index, see [llms.txt](https://docs.labii.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://docs.labii.com/widgets/dashboard-widgets/reports.md). # Reports Transform workspace data into actionable insights with comprehensive visualization, analysis, and monitoring tools for organization-wide reporting ## Overview The Reports dashboard widgets category provides comprehensive tools for visualizing, analyzing, and monitoring laboratory data across your entire workspace. These widgets enable laboratory administrators and managers to track productivity trends, analyze data distribution patterns, create dynamic visualizations from table records, monitor system usage, and ensure data integrity. From high-level executive summaries showing record creation patterns across projects and personnel, to detailed data-driven charts exploring relationships within your datasets, to metrics views displaying counts across multiple dimensions, and audit tools verifying data quality—these widgets transform raw laboratory data into strategic insights. By embedding powerful reporting capabilities at the dashboard level, these tools support data-driven decision-making, resource planning, compliance monitoring, and organizational performance assessment. ## Widgets * [Record Summary](/widgets/dashboard-widgets/reports/record-summary.md) - Visualize and analyze workspace-wide record creation patterns with customizable aggregation across projects, tables, personnel, and time periods * [Data Driven Charts](/widgets/dashboard-widgets/reports/data-driven-charts.md) - Create dynamic visualizations from table data with categorical and numeric chart types for exploring data relationships and trends * [Metrics](/widgets/dashboard-widgets/reports/metrics.md) - Display record counts and metrics across multiple filter dimensions for quick pattern identification and analysis * [Audit](broken://pages/j9wFdtn3TVUpubD03Jxk) - Monitor and evaluate data integrity, storage usage, and record quality to ensure compliance and maintain system health --- # Agent Instructions This documentation is published with GitBook. GitBook is the documentation platform designed so that both humans and AI agents can read, navigate, and reason over technical content effectively. Learn more at gitbook.com. ## Querying This Documentation If you need additional information that is not directly available in this page, you can query the documentation by asking a question. Perform an HTTP GET request on the following URL with the `ask` and `goal` query parameters: ``` GET https://docs.labii.com/widgets/dashboard-widgets/reports.md?ask=&goal= ``` `ask` is the immediate question: it should be specific, self-contained, and written in natural language. `goal` is what the user is ultimately trying to achieve, the reason they need the answer. Sharing it helps GitBook give you a better, more relevant answer. A goal is most helpful when it describes the outcome the user wants rather than restating the question. For example, with `ask=how do I create an API token`, a goal like `automate deployments from our CI pipeline` lets GitBook tailor the answer to that use case. The response will contain a direct answer to the question and relevant excerpts and sources from the documentation. Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.