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set_map_conditional_formatting

Apply measure-driven conditional coloring to map visuals. Set fill colors via discrete bands (min/max/color) or gradient scales (min/max/center) to encode data values.

Instructions

Set measure-driven conditional FILL on a filledMap/azureMap filled layer (dataPoint fillColor). Pass rules = JSON array of {min,max,color} bands for discrete CF, OR minColor+maxColor (and optional centerColor) for a gradient. target defaults to fill. Verify the render in Desktop.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
pageYespage name or displayName
rulesNoJSON array of {min,max,color} bands (discrete); omit for gradient
targetNofill (default)fill
visualYesfilled-map visual name
measureYesmeasure that drives the colour
maxColorNogradient high colour hex
minColorNogradient low colour hex (use with maxColor)
centerColorNogradient centre colour hex (3-stop)
measureTableYestable that owns the measure
reportSessionIdYes
Behavior3/5

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

No annotations are present, so the description must carry the full burden. It explains the mechanics (fill color, target default) and adds a verification tip, but it does not disclose whether existing formatting is overwritten, any side effects, or prerequisites beyond the visual type.

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 concise and well-structured: purpose sentence, usage mode sentence, target default, and verification tip. Every sentence earns its place with no redundancy.

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

Completeness3/5

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

Given the tool's complexity (10 params, no annotations, no output schema), the description covers the core mechanics well but omits important context such as error handling, interaction with existing formatting, and prerequisites beyond the visual type. It is adequate but not fully complete.

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

Parameters4/5

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

Schema coverage is high (90%), but the description adds value by clarifying the mutually exclusive alternatives (rules OR minColor+maxColor) and explicitly stating the target default. This goes beyond the schema descriptions.

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 clearly states the tool's action ('Set measure-driven conditional FILL') and specific resource ('filledMap/azureMap filled layer (dataPoint fillColor)'), distinguishing it from sibling conditional formatting tools like set_slicer_conditional_formatting or set_field_value_cf.

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?

The description provides clear context for when to use this tool (on filled map visuals) and explains the two modes (discrete rules vs gradient). However, it does not explicitly mention alternatives or when not to use it, but the context is sufficient.

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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