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describe_schema_tool

Call first to read a database's real schema (tables, columns, indexes, row counts) for cost-aware queries that use indexes, not full scans. Read-only; returns need_from_user if schema unavailable.

Instructions

Read a database's REAL schema — tables/collections, columns/fields, INDEXES, and row counts — so you can write a grounded, cost-aware query BEFORE guessing. Call this FIRST when a user asks for data and you don't already know the schema; it tells you which columns are indexed so your query hits an index, not a full scan. READ-ONLY catalog access — never reads data rows. If the schema can't be read it returns need_from_user naming what to ask the user for. Pass target= in a multi-DB setup; combine with list_targets to find which DB has the data.

Input Schema

NameRequiredDescriptionDefault
targetNo

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.2.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations, the description carries the full load and does well: it declares READ-ONLY catalog access, states it never reads data rows, and discloses the failure mode (returns `need_from_user` naming what to ask). It stops short of permissions, rate limits, or latency characteristics, so it is strong but not exhaustive.

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?

Front-loaded with the purpose and the FIRST-call directive before the rationale, and each sentence adds a distinct fact (content, trigger, safety, failure mode, targeting). The dense em-dash enumeration is slightly heavy but still earns its place.

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 single-parameter read tool with an output schema already covering return shape, this covers purpose, trigger, safety, failure handling, and multi-DB targeting. The only notable omission is how it differs from the similarly named preflight_schema_only sibling.

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?

Schema coverage is 0% (the lone `target` property has no description), so the description must compensate, and it does: it explains that target=<name> is used in a multi-DB setup and how to discover the right value via list_targets. That is meaningful guidance beyond the bare 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?

States a specific verb and resource ('Read a database's REAL schema') and enumerates exactly what is returned (tables/collections, columns/fields, indexes, row counts). It also implicitly separates itself from data-returning siblings by emphasizing catalog-only content.

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

Usage Guidelines5/5

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

Gives an explicit trigger ('Call this FIRST when a user asks for data and you don't already know the schema') and names the complementary sibling ('combine with list_targets to find which DB has the data'). The condition for the target parameter is stated as well ('in a multi-DB setup').

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