get_schema

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

Annotations already declare readOnlyHint=true, and the description adds the output content (column names/types) and the scoping to a specific table. It does not disclose additional behaviors such as error handling or requirements, but given the annotation coverage, this is adequate baseline.

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 a single, concise sentence that immediately conveys the tool's function. Every word contributes meaning, with no redundancy or filler.

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 tool with two clearly described parameters, the description fully explains what the tool returns and when it is used. The lack of an output schema is compensated by the explicit statement of return content, and the read-only annotation covers the safety profile.

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?

The input schema already provides descriptions for both parameters (source and table), achieving 100% coverage. The description adds minimal semantic value beyond the schema, merely reinforcing that the table is 'specific' and that the output is schema-related, so the baseline of 3 is appropriate.

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 'Return' and clearly states the resource ('column names and types for a specific table'). It distinguishes itself from siblings like list_tables (which lists table names) and query (which returns data) by focusing on schema metadata.

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?

The description implies the tool should be used when you need the column names and types of a specific table, providing clear context. It does not explicitly mention alternatives or exclusions, but the purpose is specific enough to guide appropriate usage among the sibling tools.

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