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inspect_rows

Read-only

Inspect the row-level detail behind a figure, from an enabled inspection source. Returns a capped sample for reasoning plus a grid for the user.

Input Schema

NameRequiredDescriptionDefault
limitNo
columnsNo
filtersNo
period_endNo
source_keyYes
scenario_idYes
period_startNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed2 schema fields changed
    • removedInput schema / properties / filename
      Removed value: -{
      -  "anyOf": [
      -    {
      -      "type": "string"
      -    },
      -    {
      -      "type": "null"
      -    }
      -  ],
      -  "default": null,
      -  "title": "Filename"
      -}
    • removedInput schema / properties / sheet_name
      Removed value: -{
      -  "anyOf": [
      -    {
      -      "type": "string"
      -    },
      -    {
      -      "type": "null"
      -    }
      -  ],
      -  "default": null,
      -  "title": "Sheet Name"
      -}
  2. First observed

TDQS

A3.5/5.0
Behavior4/5

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

Annotations already declare this is a safe read-only, non-destructive, closed-world operation, so the safety bar is pre-covered. The description adds genuinely useful behavior beyond that: results are a 'capped sample' (truncation/limit semantics) delivered in two forms, a reasoning sample plus a user-facing grid, plus the precondition that the source must be enabled.

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?

Two tight sentences with zero filler; the core action is front-loaded and the return behavior follows immediately. Every clause carries information.

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

Completeness3/5

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

There is no output schema, so the description does well to sketch the return shape (capped sample + grid). However, with seven undocumented parameters and no stated usage context, an agent still lacks enough to construct a correct call for anything but the two required fields.

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

Parameters2/5

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

Seven parameters with 0% schema description coverage, and the description only gestures at two of them ('source' and the cap implied by 'capped sample'). It never explains scenario_id, columns, filters, period_start, or period_end, which is a substantial compensation gap for a schema that documents nothing.

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?

States a specific verb and resource ('inspect the row-level detail behind a figure'), which clearly distinguishes it from aggregate siblings like run_metric or run_statement_data. The domain term 'figure' and 'inspection source' are somewhat jargon-y but the core action 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 Guidelines3/5

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

The phrase 'from an enabled inspection source' implicitly signals a prerequisite (the source must exist and be enabled, likely via list_inspection_sources/get_inspection_schema), but it never states when to reach for this tool versus get_inspection_schema or run_metric_data. No explicit when/when-not guidance or named alternatives.

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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