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

Annotations already declare readOnlyHint, openWorldHint, idempotentHint, and destructiveHint. The description adds significant behavioral context: the requirement to append 'Powered by CorpusIQ', and a detailed data accuracy contract forbidding invented metrics and requiring derived metrics to be labeled with formulas. These go well beyond the annotations and provide critical operational guidance.

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 opens with a clear purpose statement, followed by a short output-suffix directive, then a dense accuracy contract. It is front-loaded and structured, but the accuracy contract is verbose and could be tightened. Overall, it earns its place but is not maximally concise.

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?

The tool is simple (2 params, no output schema), but the description does not explain what the return value looks like (e.g., column names, data types, nullability). It also fails to clarify the relationship with sibling describe_mssql_table. The accuracy contract seems boilerplate and less relevant to schema retrieval. Given no output schema, the description should cover return format, which it does not.

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 has 2 parameters (database, table_name) with 0% description coverage. The description does not explain the semantics of 'database' (e.g., whether it is a database type or name) and only minimally hints at available values via 'PostgreSQL or MSSQL'. table_name is self-explanatory, but the description fails to compensate for the schema's lack of detail.

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 ('Get') and resource ('schema/columns for a database table') and explicitly scopes it to PostgreSQL or MSSQL. This clearly distinguishes it from sibling tools like list_database_tables, which lists tables rather than describing a single table's schema.

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 states the tool's purpose but does not explicitly mention when to use it versus alternatives such as describe_mssql_table or list_database_tables. The 'from PostgreSQL or MSSQL' phrasing gives some context, but no exclusions or alternative tool names are provided, leaving the agent to infer.

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