pbi_set_conditional_format

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

Beyond the annotations (which only indicate non-read-only and non-idempotent), the description discloses that applying a second gradient to the same property overwrites the previous rule ('dos degradados sobre la misma propiedad no se suman, se pisan'). It also explains the default behavior for missing min/max values and the requirement for target_column to be projected, adding valuable operational context.

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

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

The description is well-structured: a short introductory sentence, a compact bullet-style explanation of each parameter, and a critical caveat about rule replacement. Every sentence contributes substantive information, and there is no redundant filler.

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

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

For a 13-parameter tool with no schema descriptions and no annotation assistance, this description covers usage context, parameter semantics, and side effects thoroughly. The presence of an output schema means the description does not need to explain return values, making the content sufficiently complete for an agent to select and invoke the tool correctly.

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

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

With 0% schema description coverage, the description compensates thoroughly by explaining nearly every meaningful parameter: field's table/measure syntax, target_column's role and prerequisite, target's possible values, mid_color's effect, numeric anchors, and null_strategy options. This is essential for correct invocation and far exceeds what the bare schema offers.

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

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

The description states 'Colorea un visual segun el valor de un campo (degradado)', which clearly identifies the tool as applying gradient-based conditional formatting. The analogies (heat map, traffic light scale) definitively clarify the purpose and distinguish it from other visual formatting tools like pbi_set_visual_title or pbi_set_color_from_field.

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

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

The description gives clear context: it is meant for gradient coloring based on field values and even warns that existing rules on the same target are replaced, which is critical for usage. However, it does not explicitly name alternatives for simpler static coloring or other formatting approaches, so it lacks explicit exclusions.

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