Skip to main content
Glama

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

TableJSON Schema
NameRequiredDescriptionDefault
targetNo

Output Schema

TableJSON 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.