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auto_arrange

Auto-arrange Power BI report page into a structured grid: header textboxes at top, slicer filter bar, KPI cards, then data visuals in balanced rows. Call after placing visuals roughly to snap them into a consistent layout.

Instructions

Auto-arrange a page into a clean professional grid in ONE call: header textboxes full-width at top, then a slicer filter-bar, then a KPI-card row, then the data visuals (charts/tables) in a balanced grid that fills the page - consistent margins, gutters and alignment. Add visuals roughly, then call this to snap them into a designed layout. Decorative shapes/images stay put.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
gutterNogap between visuals px
marginNoouter margin px
pageNameYes
kpiHeightNoKPI card height px
maxPerRowNomax data visuals per row (1-4)
canvasWidthNocanvas width (default = page width)
canvasHeightNocanvas height (default = page height)
headerHeightNoheader textbox height px
slicerHeightNoslicer height px
reportSessionIdYes
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations, the description carries the transparency burden. It discloses the rearrangement algorithm (header full-width, slicer bar, KPI row, balanced grid) and the safety guarantee that 'Decorative shapes/images stay put.' It does not mention potential side effects like resizing or overwriting manual formatting, but provides substantial behavioral insight.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness5/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is three sentences, front-loads the core purpose, and every sentence earns its place: the first explains the layout, the second gives the workflow, and the third provides an important exception. It is concise and structured effectively.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness4/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a complex layout tool with 10 parameters and no output schema, the description covers the main usage context, workflow, and a key behavioral caveat. It does not explain how the tool identifies KPI cards vs data visuals, which is a minor gap, but overall it is sufficiently complete.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is high (80%), so the baseline is 3. The description adds contextual meaning by mapping 'header textboxes' to headerHeight, 'slicer filter-bar' to slicerHeight, and 'KPI-card row' to kpiHeight, but does not detail parameter syntax or further clarify semantics beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb+resource with a detailed outcome: 'Auto-arrange a page into a clean professional grid in ONE call' and describes the exact layout pattern (header, slicer, KPI row, data visuals). This clearly distinguishes it from sibling tools like align_visuals or tidy_slicer_layout.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

It provides a clear when-to-use instruction: 'Add visuals roughly, then call this to snap them into a designed layout.' However, it does not explicitly name alternatives or state when NOT to use it, so it stops short of a full usage guideline.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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