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infino-ai

Infino MCP server

Official
by infino-ai

Describe an Infino table

infino_describe_table
Read-onlyIdempotent

Inspect a table's column names and types before querying to know exactly which fields to target.

Instructions

Return a table's column names and types — call before searching so you know which column to target and what fields each result row carries.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
tableYesTable name (from infino_list_tables).

Schema Changelog

Changes observed during successful MCP inspections. Dates show when Glama detected each change.

  1. Changed1 schema field changedv0.10.0
    • removedInput schema / additionalProperties
      Removed value: -false
  2. First observedv0.7.0

TDQS

A4/5.0
Behavior3/5

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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds the practical context of using it before searching, but does not disclose output format, error behavior, or other behavioral details beyond what annotations provide.

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?

The description is a single sentence that front-loads the core function ('Return a table's column names and types') and then adds a concise, high-value usage note. Every word earns its place with no redundancy.

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 simple one-parameter read-only tool, the description covers what it returns and when to call it. There is no output schema, but the description adequately explains the return value; it could be more complete by mentioning what happens for a non-existent table, but that is a minor gap.

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% and the only parameter, 'table', is already described as 'Table name (from infino_list_tables).' The tool description adds no additional parameter-level meaning, so it stays at the baseline for full schema coverage.

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 uses a specific verb ('Return') and resource ('a table's column names and types'), making the tool's function immediately clear. It also distinguishes itself from search and table-management siblings by framing its role as a pre-search introspection step.

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

Usage Guidelines4/5

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

The description explicitly tells the agent when to call this tool ('call before searching') and why, which is strong usage guidance. It does not name alternative tools or state when not to use it, but the context is clear enough for correct selection among siblings.

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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