db_sample_data

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

With no annotations, the description carries full burden. It discloses that it returns exactly 5 rows and works on tables/views, but doesn't mention whether rows are randomly selected, deterministic, or if any side effects exist. Basic behavior is clear, but additional traits (e.g., row ordering, limits for small tables) are unspecified.

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 two sentences with no redundant words. It front-loads the primary function ('Returns 5 sample rows') followed by practical usage guidance. Every word contributes 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?

For a single-parameter tool without an output schema, the description is nearly complete: it defines the output (5 rows), the target (table/view), and the use case. It could optionally specify response format or ordering, but the essentials are well covered.

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 already provides 100% coverage for the 'table' parameter with a description and example. The tool description adds no new parameter-specific meaning beyond restating 'table or view', so the baseline 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 the tool's function: 'Returns 5 sample rows from a table or view.' It uses a specific verb and resource, and distinguishes itself from siblings like db_describe_table (schema) and db_run_readonly (general queries) by focusing on sample data exploration.

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 clear usage context: 'Use this to understand the actual data format, values and patterns before writing a more specific query.' This implies when to use it (exploratory phase) and suggests alternatives (later specific queries). It doesn't explicitly name sibling tools or state when not to use, but the guidance is strong enough.

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