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inspect_chooser_table

Read-onlyIdempotent

Reads a UChooserTable by package path and returns a read-only summary: result type, output class, columns, row count, ResultsStructs, and ContextData counts.

Instructions

Read-only summary of a UChooserTable: ResultType, OutputObjectType, column count + per-column type names, ResultsStructs count, ContextData count, effective row count.

Returns: { table_path: string, result_type: string, output_object_class: string|null, column_count: int, columns: [{index, type}], row_count: int, results_count: int, context_data_count: int }

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
table_pathYesLong package path of an existing UChooserTable.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv1.1.0

TDQS

A3.7/5.0
Behavior4/5

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the description's 'read-only' label is partly redundant. However, it goes beyond the annotations by disclosing precisely which internal fields are surfaced (ResultType, OutputObjectType, per-column types, counts) and notes 'effective row count', which is useful behavioral context.

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?

Two sentences, front-loaded with the operation and then the exact return shape; no filler. The embedded 'Returns:' block is dense but earns its place given no output schema exists.

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?

A read-only inspector whose annotations cover safety and whose description supplies the full return shape in the absence of an output schema. Little is missing; the only gap is any guidance on how to obtain or validate a table_path.

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?

There is a single parameter with 100% schema description coverage ('Long package path of an existing UChooserTable'), so the schema already carries the semantics. The description adds nothing about the path beyond echoing table_path in the return shape, which is the expected baseline 3.

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+resource ('Read-only summary of a UChooserTable') and enumerates exactly what is summarized, so the agent knows it is an inspector, not a mutator or a value reader. It does not explicitly distinguish itself from siblings like get_chooser_column_values or get_chooser_row_values, which is the only thing keeping it from a 5.

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?

Usage is only implied by the word 'summary' – there is no explicit when-to-use, when-not-to-use, or pointer to alternatives (e.g., list_chooser_tables to discover a table_path, or get_chooser_column_values for per-cell detail). Adequate but leaves routing to inference.

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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