get_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 the tool is simulated, read-only (never executes SQL), and uses a demo condition language. It does not discuss error handling or side effects, but the core behavioral trait (safe simulation) is clearly conveyed.

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, front-loaded with the core purpose, and every phrase is informative without redundancy.

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's simplicity (3 parameters, all documented in schema) and the existence of an output schema, the description provides sufficient context: purpose, simulated nature, example condition, and explicit no-SQL guarantee.

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 covers all 3 parameters with descriptions, achieving 100% coverage. The description adds value by providing an example for 'condition' (e.g., `status == shipped`) and contextualizing the parameters within a fake database environment.

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 returns simulated rows from a fake database using a demo condition language, and explicitly says it never executes SQL. This distinguishes it from the sibling tool 'get_schema', which likely returns schema definitions.

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 context that this tool is for demo/testing purposes (simulated, fake sample database) and that it does not execute real SQL. However, it does not explicitly list when not to use it or alternative tools.

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