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Glama

list_tables

List tables in a database schema with comments, estimated row counts, and size, and filter by partial table name. Use it to explore large schemas before writing queries.

Instructions

列出某个 schema 下的表,带表注释、估算行数和体积。可用 name_contains 按表名过滤。注意有的 schema 有 600 多张表,建议配合过滤条件使用,或者直接用 search_metadata。

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
limitNo最多返回多少张表
schemaYesschema 名,例如 cses_data
name_containsNo按表名模糊过滤,不区分大小写

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault

No arguments

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.3/5.0
Behavior4/5

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

With no annotations, the description carries the burden and does disclose a real behavioral trait: result sets can be very large (600+ tables) and filtering is advised. It also previews returned fields (comments, row estimates, size). It stops short of covering permissions or rate/limit behavior beyond the schema's limit field.

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?

Purpose is front-loaded, then the filter hint, then the large-schema warning, all in three compact sentences. The listing of returned fields is mildly redundant given an output schema exists, but nothing is bloated.

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?

An output schema exists, so return values need no explanation, and the description still adds the crucial large-schema caveat plus the sibling alternative. Complete enough for correct invocation, missing only minor operational detail.

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 schema, name_contains and limit. The description only restates the name_contains filter, adding no syntax or format detail beyond the schema, so the baseline 3 applies.

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 (list) and resource (tables under a schema), and further specifies the returned payload (table comments, estimated row counts, size). It also distinguishes itself from the sibling search_metadata, so an agent can route between them without opening either schema.

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?

Explicitly tells the agent to pair it with a filter (name_contains) and, when that isn't appropriate, to use search_metadata instead. It also warns that some schemas exceed 600 tables, giving a concrete condition that selects the alternative.

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