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add_time_intelligence

Generate YTD, QTD, MTD, prior-year, and YoY % measures for a base measure using a date column.

Instructions

Generate the standard time-intelligence measure set for a base measure: YTD, QTD, MTD, PY (prior year), and YoY %. Needs a date table column (e.g. Calendar[Date]).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
homeTableNohome table for the new measures (optional; defaults to the base measure's table)
sessionIdYes
dateColumnYesdate column, e.g. Calendar[Date]
baseMeasureYesexisting base measure, e.g. Total Sales
Behavior3/5

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

With no annotations, the description carries the full burden of disclosing behavior. It adds useful context about the created measures and the need for a date table column, but it does not explicitly state that this is a mutation (creating measures) nor mention potential side effects like overwriting existing measures or permission requirements.

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 concisely written in two sentences, front-loads the primary action, and includes only necessary detail without filler. It efficiently communicates the core purpose and a key requirement.

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

Completeness2/5

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

The description provides a high-level purpose but fails to address the existence of several closely related time-intelligence tools, making selection difficult. It also does not describe the return value, idempotency, or what happens if the preconditions are not met, leaving important gaps for an AI agent.

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 75%, and the description largely repeats examples already present in the schema (e.g., 'Calendar[Date]'). The description does not add new meaning beyond the schema's parameter descriptions, so it meets the baseline but does not exceed it.

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

Purpose4/5

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

The description clearly states the tool's action ('Generate') and resource ('standard time-intelligence measure set') and enumerates the specific measures produced (YTD, QTD, MTD, PY, YoY). However, it does not distinguish this tool from the similarly named sibling 'add_time_intelligence_measures', which could cause selection ambiguity.

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 implies usage by specifying the standard measure set and the prerequisite of a date table column. But it offers no explicit guidance on when to use this tool versus closely related alternatives like 'add_calendar_based_time_intelligence' or 'add_time_intelligence_measures', and no exclusions are provided.

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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