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Glama

list_objects

Read-onlyIdempotent

List every table and view a caller may read, with names, kinds, column counts, and descriptions, to show available data or debug schema selection.

Instructions

List every table and view this caller may read: 'objects' holds each one's name, kind (table or view), column count and description, with 'count' visible out of 'total_objects'. Use it to show what data exists, or when select_schema did not return what you expected. It returns no DDL and no rows, and on a large database it is long: to answer a question, call select_schema instead. Pass principal and roles; restricted objects are absent for callers without the role.

Input Schema

NameRequiredDescriptionDefault
rolesNoThe caller's roles or groups, e.g. ['finance', 'payroll']. Objects and columns restricted to a role are visible only when it is listed here. Omitted = no roles.
principalNoWho is asking, as an identity string such as 'okta:jdoe'. Pass it whenever you know the user: visibility is decided for this identity. Omitted = anonymous, which sees only unrestricted objects.

Output Schema

NameRequiredDescriptionDefault
resultYes

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.6/5.0
Behavior4/5

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

Annotations already establish readOnly/idempotent/non-destructive, so the description correctly spends its budget elsewhere: it discloses that no DDL or rows are returned, that output is long on large databases, and that role-restricted objects are silently absent for unauthorized callers. That last point is important behavioral disclosure not derivable from annotations or schema.

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 output contract, then usage, then the cost warning, then the permission parameters. Every clause earns its place, though the single dense paragraph packs four distinct ideas and would benefit from light separation.

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?

The tool has an output schema, so return values need not be spelled out, yet the description still summarizes them usefully. Purpose, alternatives, permission semantics, and the truncation/length caveat are all covered; nothing needed to invoke it correctly is missing.

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 100%, so the baseline is 3, but the description goes further by tying the parameters to an observable consequence: restricted objects are absent for callers whose role is not passed. That gives the agent a reason to supply principal/roles rather than treat them as optional noise.

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 ('List every table and view this caller may read') and immediately describes the returned shape ('name, kind, column count and description'). It explicitly distinguishes itself from select_schema, so an agent can choose 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?

Gives named use cases ('show what data exists', 'when select_schema did not return what you expected') and an explicit counter-indication with the alternative ('to answer a question, call select_schema instead'). Both when-to-use and when-not-to-use are present.

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