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mfbaig35r
by mfbaig35r

table_describe

Inspect a review table's structure, including its review unit, grouping, instructions, and column-level details such as types, execution stages, and verification caveats.

Instructions

Describe a table: its review unit, grouping, Table Instructions, and every column.

Each column reports its native type, execution stage, configured options, and any pre-run verification caveat the inventory recorded against its type.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYesTable number as the corpus defines it, e.g. '01' or '13'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

B3.4/5.0
Behavior3/5

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

No annotations are present, so the description carries the disclosure burden. It clearly frames the tool as descriptive and lists the kinds of metadata returned, but it does not explicitly say the operation is read-only or note any side effects, error conditions, or access 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?

Two tight paragraphs: the first states scope, the second details column-level coverage. No filler or repetition; the most important content is front-loaded.

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?

For a low-complexity describe operation with a documented schema and output schema, the description covers what is described and what each column report includes. It could add explicit read-only/semantic context, but little essential information is missing.

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?

The schema describes the single parameter well ('Table number as the corpus defines it, e.g. '01' or '13''), and the description reinforces that the table is the subject being described. With 100% schema coverage, there is no gap to compensate for, so a baseline 3 is appropriate.

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 names a specific action and resource: 'Describe a table' and enumerates what is covered (review unit, grouping, Table Instructions, every column). It is clear but does not explicitly distinguish itself from sibling tools like table_read or columns_find.

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

Usage Guidelines2/5

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

No guidance on when to prefer this tool over alternatives. The description implies 'use when you need table metadata,' but it never states exclusions, prerequisites, or contrasts with table_read or columns_find.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.