recommend_prompt_template_tests

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It describes the tool's function and output format ('structured array of test cases'), but lacks details on permissions, rate limits, side effects, or error handling. For a tool with no annotations, this leaves significant gaps in understanding its operational behavior.

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-structured with clear sections (About, Parameters, Example usage, Tool output instructions) and front-loaded key information. It's appropriately sized for the tool's complexity, though some sentences could be more concise (e.g., the example usage is detailed but necessary). Overall, it's efficient with minimal waste.

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 moderate complexity (1 parameter with nested objects), no annotations, and no output schema, the description provides a good foundation but has gaps. It explains the purpose, parameters, and output format, but lacks details on behavioral traits, error cases, and doesn't fully cover all schema parameters (e.g., temperature). It's adequate but not fully complete for safe and effective use.

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 description provides a 'Parameters' section that lists and briefly explains each parameter (promptTemplate, contextSchema, promptOrigin, model), adding meaning beyond the input schema. Since schema description coverage is 0%, the description compensates well by documenting the parameters, though it doesn't cover all schema parameters (e.g., temperature is omitted). The value added is substantial but not complete.

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 purpose: 'generates an array of recommended tests for a given prompt template.' It specifies the verb ('generates') and resource ('recommended tests'), though it doesn't explicitly differentiate from sibling tools like 'run_evaluation_tests' or 'find_flaky_tests' which might also involve testing. The purpose is clear but lacks sibling differentiation.

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 usage context by mentioning it's 'part of a toolchain that generates and provides test cases for a prompt template,' suggesting it should be used in a testing workflow. However, it doesn't explicitly state when to use this tool versus alternatives like 'run_evaluation_tests' or provide clear exclusions. The guidance is implied but not explicit.

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