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search_metadata

Discover tables, column definitions, and business terms across DatI-connected databases to resolve schema ambiguity before running SQL.

Instructions

Search tables, column definitions, and business semantic terms across databases connected to DatI.

Behavior: - Read-only: Safe to call anytime with no side effects or destructive actions. Usage Guidelines: - Call this tool FIRST to discover existing tables, columns, and business terms before invoking execute_parameterized_sql. - Suitable for resolving NL2SQL schema ambiguity and understanding domain-specific abbreviations.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYesNatural language question, table name keyword, or business term to search.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. Changed1 schema field changedv0.1.1
    • addedInput schema / properties / query / description
      Added value: +"Natural language question, table name keyword, or business term to search."
  2. First observedv0.1.0

TDQS

A4.5/5.0
Behavior4/5

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

With no annotations provided, the description does disclose the key behavioral trait: 'Read-only: Safe to call anytime with no side effects or destructive actions.' It does not mention caching, rate limits, or result ordering, but the safety profile is adequately covered.

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?

It is short, front-loaded with the purpose, and uses clear labeled sections ('Behavior', 'Usage Guidelines') that make it easy to scan. Every sentence adds value with no filler.

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

Completeness5/5

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

Given a single parameter with full schema coverage, an output schema that already defines return values, and no complex annotations, the description covers the essential behavioral and usage context. Nothing an agent needs to call it correctly 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?

Schema description coverage is 100%, so the schema already documents the single 'query' parameter as a natural-language question, table keyword, or business term. The description adds no additional syntax or format details beyond what the schema provides, so the baseline 3 is appropriate.

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?

The description states a specific verb ('Search') and a precise resource set ('tables, column definitions, and business semantic terms across databases'), which is far more than the bare name implies. It clearly delineates it from the sibling tool execute_parameterized_sql by focusing on discovery rather than execution.

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?

It explicitly says 'Call this tool FIRST ... before invoking execute_parameterized_sql' and specifies use cases like 'resolving NL2SQL schema ambiguity' and 'understanding domain-specific abbreviations.' This gives concrete when-to-use guidance and names the alternative tool, leaving no ambiguity about ordering.

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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