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Glama

table_sizes

Read-only

Rank tables by data and index size to find storage hogs and plan capacity. Returns a ranked list, flagging when more results exist.

Instructions

[READ] Largest tables by data + index size.

Args: limit: Number of tables to return, largest first (default 20). target: Target name from config; omit for the default.

Returns an envelope: {"tables": [...], "returned": N, "limit": L, "truncated": bool}. When "truncated" is true there is more beyond what was returned — re-run with a higher limit rather than treating this as the complete picture.

Input Schema

NameRequiredDescriptionDefault
limitNo
targetNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.5.0

TDQS

A4.1/5.0
Behavior4/5

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

Annotations only declare readOnlyHint=true, so the description carries the rest: it discloses the return envelope (tables/returned/limit/truncated) and, importantly, the truncation semantic with a corrective action. It does not cover query cost or ordering guarantees beyond 'largest first', leaving a small gap.

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 one-line summary followed by Args and Returns sections; every sentence carries information, including the truncation caveat. Minor redundancy between the '[READ]' tag and readOnlyHint, and the envelope spelled inline is slightly dense.

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?

With no output schema, the description compensates by documenting the return envelope and truncation behavior, and covers both parameters. It stops short of explaining what 'target' config values are valid or any auth/cost considerations an agent might need.

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 description coverage is 0%, so the description must supply all parameter meaning, and it does: limit is 'number of tables, largest first (default 20)' and target is 'target name from config; omit for the default'. The 'target name from config' phrasing stays vague about what a valid target resolves to, which keeps it short of a 5.

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 resource and metric - 'Largest tables by data + index size' - with a clear read verb marker. This distinguishes it cleanly from neighbors such as table_fragmentation, table_status, and index_stats without needing to open any schema.

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

Usage Guidelines3/5

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

It gives useful in-tool guidance ('omit for the default', 're-run with a higher limit' when truncated) but never states when to choose this over siblings like table_fragmentation or table_status. Usage is implied by the resource name rather than spelled out against alternatives.

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