List tables

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

Annotations already declare readOnlyHint: true, so the bar for additional disclosure is lower. The description adds significant behavioral context: it specifies the return format (JSON object with tables and database), and details on presentation (never mention tool name, card vs. Markdown layout, formatting rules). This goes well beyond the annotation.

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-organized with clear sections (purpose, usage, return format, presentation). It is more verbose than strictly necessary, but every section contributes useful guidance. The first sentence immediately conveys the core action, and the structured formatting rules are justified for consistent agent output.

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 read-only tool, the description covers all essential aspects: what it does, when to use it, what it returns, and how to format the answer. The presence of an output schema and annotations covers remaining structural details, making the description comprehensive.

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?

Schema description coverage is 100%, with both parameters (db_id and database) well-documented in the schema itself. The description does not add parameter-specific details, but the schema already explains optionality and defaults, so a baseline score 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 clearly states 'List tables in a database' with a specific verb and resource. It further clarifies the purpose ('when the user wants to see what tables exist') and distinguishes from sibling tools like list_databases and describe_table by focusing on the list of tables.

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?

It explicitly says 'Use this tool when the user wants to see what tables exist,' providing a clear use case. However, it does not mention alternatives or when not to use it, so it stops short of full comparative guidance.

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