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add_page_filter

Apply a page-level filter to all visuals in a Power BI report, using categorical value lists or comparison operators on columns and measures.

Instructions

Add a PAGE-level filter (filters every visual on that page). kind=categorical writes an 'is one of' values filter (pass values, comma-separated or a JSON array); any other kind writes a comparison/blank filter (op = gt|gte|lt|lte|eq|ne|isblank|isnotblank) on a column or measure (fieldKind=column|measure). valueType=int|decimal|string for the values.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
opNocomparison op: gt|gte|lt|lte|eq|ne|isblank|isnotblank
kindNocategorical (values list) | comparisoncategorical
pageYespage name or displayName
fieldYesfield (column or measure) to filter on
tableYestable that owns the filter field
valuesNocategorical values (comma-separated or JSON array); or a single comparison value
fieldKindNofor a comparison filter: column|measurecolumn
valueTypeNoint|decimal|stringstring
reportSessionIdYes
Behavior4/5

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

With no annotations, the description carries the full burden. It discloses the behavioral traits well: how the filter is constructed for categorical vs comparison modes, the operator list, the value formats (comma-separated or JSON array), and fieldKind/valueType options. It does not cover side effects like whether existing page filters are replaced or if filters are idempotent, but it gives a strong behavior overview for a mutation tool.

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

Conciseness4/5

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

The description is a single dense sentence with semicolons and parentheticals, but every clause adds value. It front-loads the purpose and then logically organizes the two modes. It's not the most concise, but it's appropriately sized for the tool's complexity and well-structured, earning a 4.

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 tool with 9 parameters and two distinct modes, the description covers both modes, key parameter interactions, and value formatting. It doesn't explain return values, but no output schema exists and the focus is on the action, not the response. It leaves out session-related details, but those are in the schema. Overall, it's contextually complete for its purpose.

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 description coverage is 89%, so baseline is 3. The description adds meaning beyond the schema by explaining the relationship between kind and values/op, clarifying the values format (comma-separated or JSON array), and defining the comparison op list. It also explains the fieldKind choices. These enrich the schema details, warranting a 4.

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 opens with a specific verb+resource+scope: 'Add a PAGE-level filter (filters every visual on that page).' This clearly distinguishes it from sibling tools like add_visual_filter and add_report_filter by specifying the page-level scope. The purpose is unambiguous.

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 on when to use this tool (to filter all visuals on a page) but does not explicitly mention alternatives or exclusion criteria. It explains the parameter-driven behavior (categorical vs comparison) but stops short of saying 'use add_visual_filter for visual-level filters.' The page-level scope is an implicit usage guideline, so it's a 4.

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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