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pbi_create_time_intelligence_pack

Create time-intelligence measures like YTD, MTD, QTD, and YoY from a base measure in Power BI, with automatic dependency handling and optional dry-run to preview changes.

Instructions

Create a family of time-intelligence measures from a base measure.

Default patterns: YTD, MTD, QTD, SPY, YOY, YOY %, MA3. Each generated measure is named "{base_measure} {suffix}" (e.g. "Sales YTD") and lives on table (typically the same fact table as the base measure). Dependency-aware: requesting YOY% automatically adds YOY and SPY so the whole family resolves.

With format_inherit=True, each measure inherits base_measure's format string (best-effort lookup on the live model). format_string overrides that when supplied. Patterns that prescribe their own format (e.g. YOY %"0.00%") win unless format_string is explicit.

With dry_run=True no model mutation occurs — the response carries a plan listing every measure that would be created/updated/skipped.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYes
dry_runNo
patternsNo
overwriteNo
date_tableYes
date_columnYes
base_measureYes
format_stringNo
display_folderNoTime intelligence
format_inheritNo

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior5/5

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

With no annotations provided, the description fully bears the transparency burden. It discloses naming conventions, dependency-aware generation (YOY% adds YOY and SPY), format inheritance rules (format_inherit, format_string, pattern-specific formats), and dry_run behavior (no mutation, returns plan).

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 well-structured with concise paragraphs covering purpose, naming, dependencies, formatting, and dry-run. Every sentence adds value without redundancy.

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?

Given the tool's complexity (10 parameters, 0% schema coverage), the description covers core functionality, dependencies, formatting options, and dry_run behavior. It explains naming and dependency resolution. Minor gaps: prerequisite that date_table must be marked as date table in model is not mentioned, but overall complete for typical usage.

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?

Although schema description coverage is 0%, the description explains key parameters: table, base_measure, date_table, date_column, patterns (with default list), dry_run, overwrite, format_string, display_folder, format_inherit. It adds meaning beyond the schema by detailing behavior, though some parameters like overwrite could be elaborated.

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 'Create a family of time-intelligence measures from a base measure.' It specifies default patterns and naming conventions, distinguishing this tool from sibling measure creation tools like pbi_create_measure or pbi_create_rolling_average_measure.

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

Usage Guidelines3/5

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

The description explains the tool's behavior (dependency-aware, format inheritance) but does not explicitly state when to use it over alternatives. It implies usage for generating multiple time-intelligence measures, but lacks comparative guidance.

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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