investigate_database

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

With no annotations, the description carries the full burden. It adds useful safety context with 'bounded reads' and 'sampling recent rows', but it does not explicitly state that the tool is read-only or mention permission requirements.

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?

A single, front-loaded sentence that communicates purpose and optional behavior with no filler. Every phrase adds value.

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 description is minimal but adequate for a discovery tool, covering core purpose and safety. However, with no output schema and no annotations, it does not explain return values or prerequisite conditions like database existence.

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 schema covers 50% of parameters (db and includeSamples). The description adds meaning by connecting 'sampling recent rows' to the sampling parameters, but it does not explain maxTables or sampleRowsPerTable limitations beyond the schema's numeric constraints.

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 function: 'Discover tables and schemas in a database' with a specific verb and resource. It also mentions optional row sampling, distinguishing it from sibling tools like list_tables or describe_table.

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 use cases (exploration, discovery) but does not explicitly state when to prefer this tool over alternatives like list_tables or describe_table. It lacks exclusions or alternative recommendations.

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