whodb_tables

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

Annotations already declare readOnlyHint=true and idempotentHint=true, so the description's behavioral burden is lighter. The description adds that the tool returns an 'Array of table objects with name and attributes' and that the optional include_columns parameter returns column details to save separate calls. However, it could mention if include_columns affects performance or cost.

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 well-structured with headings ('Best for', 'Not recommended for', 'Common mistakes', 'Usage Example', 'Returns', 'Note', 'Optional parameter'). It is front-loaded with key information. However, the usage example and note could be slightly more concise; still, it is not overly verbose.

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?

Given the tool has a moderate complexity (3 parameters, 1 required), and there is an output schema (context signal: 'Has output schema: true'), the description adequately covers return values ('Array of table objects with name and attributes') and the behavior of include_columns. It could mention edge cases (e.g., empty schema) but is sufficiently complete for an AI agent.

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 100% description coverage for all three parameters. The description adds extra context: explains that schema uses default if omitted, and that include_columns 'saves you separate whodb_columns calls and gives you everything needed to write queries in a single round-trip.' This goes beyond schema descriptions.

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 clearly states the tool's purpose: 'List all tables in a database schema.' The verb 'list' and resource 'tables' are specific. It distinguishes from siblings by mentioning when to use whodb_columns or whodb_query instead, e.g., 'Not recommended for: When you already know the table name (proceed directly to whodb_columns or whodb_query).'

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 provides explicit when-to-use ('Best for: Discovering what tables exist...'), when-not-to-use ('Not recommended for: When you already know the table name'), and common mistakes ('Not specifying schema when the database has multiple schemas'). A usage example is included, showing the JSON structure.

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