get_table_schema

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

With no annotations, the description must carry the burden of behavioral disclosure. It does mention that the return is a 'Dict[str, Any]' describing the schema 'or an error message', giving some insight into error handling. However, it does not specify whether the table must exist, what happens on missing tables, or any side effects (though the operation is read-only). This is adequate but not rich.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is concise and front-loaded with the purpose. However, the Args section is redundant and inconsistent with the schema, and the Returns section could be more compact. It is brief overall but contains a small structural flaw that prevents a perfect score.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a simple one-parameter tool, the description provides the return type and error possibility. Yet it omits any detail about the shape of the schema dictionary (e.g., whether it includes column names, data types, constraints) and does not clarify behavior for non-existent tables. Given the lack of an output schema, this is a moderate gap.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Although the schema covers the parameter fully (table_name as a string), the description's Args section is misleading: it says 'table_name_input: Object containing the table_name', which contradicts the schema that expects a direct string. This introduces ambiguity and fails to add meaningful semantic value beyond the schema.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Does the description clearly state what the tool does and how it differs from similar tools?

The description uses a specific verb ('Retrieves') and clearly states the resource ('the schema (column names and types) for a specific table'). This unambiguously differentiates it from sibling tools like list_tables (which lists tables) and query_database (which fetches data).

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

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

There is no explicit or implicit guidance on when to use this tool versus alternatives. No mention of 'use this when you need a table structure' or references to sibling tools like list_tables or query_database. The only context is the tool's purpose, which does not qualify as usage guidance.

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