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run_insight_query

Read-only

Compute an analytics insight (a single value, a comparison, a breakdown, or a time-series) over a filtered period of transactions, from an ad-hoc spec, WITHOUT saving it. Use this to answer one-off analytical questions like 'how much did I spend on Dining last month' or 'compare income vs expense this year'. If the user wants to keep the result pinned on their dashboard, use propose_saved_insight instead.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
specYesThe visualization spec describing what to compute. vizType is one of: 'value' (single number), 'comparison' (template income_vs_expense / period_over_period, or custom A/B), 'chart_time' (bucketed time series), 'breakdown' (top groups by category/envelope/account/type), 'table' (list of N transactions). Always set filter.period - use relative.value='this_month' / 'last_30_days' etc. unless the user gave explicit dates.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.2/5.0
Behavior4/5

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

The description clearly indicates a read-only operation ('generate'), and the readOnlyHint annotation confirms no side effects. However, it doesn't state that it does not modify data, which could be made explicit.

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 succinct and directly states what the tool does without unnecessary details. It appropriately omits schema internals, keeping it concise.

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?

The description, tool name, and sibling tools (create/update/delete/get/share) make it clear this is the execution action for insights. It gives enough context for an agent to understand when to use it, though it could explicitly mention that it runs an existing ad-hoc query or saved insight definition.

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?

The single 'spec' parameter has a detailed schema defining metric, groupBy, filter with periods and optional account/category filters. However, the schema is complex with multiple variantsainer and the description provides no explanation of the parameter structure, relying entirely on the schema.

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 name 'run_insight' and description explicitly state that this tool generates an insight (a number, chart, or breakdown). Sibling tools like create/update/delete differentiate this as the execution/read operation, making the purpose unambiguous.

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 what the tool does but provides no guidance on when to use it versus alternatives or prerequisites. While the sibling tools imply run is for executing existing insights, there's no explicit direction on selecting this tool.

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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