list_tables

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

Discloses row counts are exact (MyISAM), return structure (dict with count, tables, truncated), and ordering. No annotations provided, so description fully covers behavioral aspects.

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?

Concise with clear Args/Returns sections, examples, and key details. No unnecessary text.

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?

Complete for a simple list tool with 2 params. No output schema but return format is explained. Sibling tools cover other needs.

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 has 0% description coverage, but the description adds full meaning: filter is case-insensitive substring, limit is max count with default. Includes practical filter examples.

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 lists tables with exact row counts and engine, specifying the database is MyISAM. It distinguishes from siblings like describe_table (single table) and schema_overview.

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?

Provides filter examples and limit context (default 500, DB has 242), guiding effective use. Lacks explicit when-not-to-use but implied by sibling tools.

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