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list_indexes

List indexes for a table or entire model, showing unique flags and covered columns for simple, unique, and composite indexes.

Instructions

List indexes of one table or of the whole model. Shows unique flag and covered columns (supports simple, unique and composite indexes).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
model_idYes
table_refNo

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior3/5

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

With no annotations, the description carries the full burden. It discloses what the tool shows (unique flag, covered columns) and the index types supported, but it does not explicitly state that it is a read-only operation or mention any permissions or side effects. The verb 'list' implies non-destructive behavior, but for a tool with zero annotation coverage, a bit more explicitness would be stronger.

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 purpose and scope, then adds detail on output contents and supported index types. No wasted words; every clause adds value.

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 listing operation with two parameters and no output schema, the description covers the essential facts: what it does, scope, and what it returns. It does not describe the exact return format (e.g., list of objects), but for a list tool that is typically self-evident. The absence of annotations is mitigated by the clear scope and behavior.

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 0%, so the description must clarify parameters. It explains table_ref's role (specifying a table vs. whole model) and its default behavior via the 'one table or whole model' phrasing. model_id is not explicitly defined, but its name and required status make it self-evident. This compensates well for the schema's lack of descriptions.

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 clearly states the tool lists indexes with a specific scope (one table or the whole model) and specifies what it shows (unique flag, covered columns, index types). This distinguishes it from siblings like get_index (single index) and list_keys (keys), giving an agent a precise understanding of the operation.

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 implies usage: if you want indexes for a specific table, provide table_ref; otherwise, leave it empty for the whole model. It does not explicitly name alternatives or state when not to use this tool, but the scope condition is clear enough for an agent to decide between this and get_index.

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