BuildBetter

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 states the tool generates a GraphQL query but doesn't explain how it works (e.g., accuracy, limitations, or output format). For a tool that performs a non-trivial transformation, this is a significant gap, as it doesn't disclose traits like potential errors or the nature of the generated query.

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 a single, clear sentence that efficiently conveys the tool's purpose without unnecessary words. It is front-loaded with the core function, making it easy to understand at a glance. This represents optimal conciseness with no wasted information.

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 complexity of generating GraphQL queries from natural language, the description is incomplete. With no annotations, no output schema, and minimal behavioral details, it fails to provide enough context for effective use. The tool likely has nuances (e.g., query accuracy, schema dependencies) that aren't addressed, making it inadequate for the task's demands.

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 has 100% description coverage, with the single parameter 'description' documented as 'Natural language description of what you want to query'. The tool description doesn't add any further meaning beyond this, such as examples or constraints. Given the high schema coverage, a baseline score of 3 is appropriate, as the schema adequately handles parameter semantics.

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: 'Generate a GraphQL query from a natural language description.' It specifies the verb ('Generate'), resource ('GraphQL query'), and transformation source ('natural language description'). However, it doesn't distinguish this tool from sibling tools like 'build-query' or 'run-query', which might have overlapping functionality, preventing a perfect score.

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 no guidance on when to use this tool versus alternatives. With siblings like 'build-query', 'run-query', and 'query-template', there's no indication of the specific context or prerequisites for using 'nl-query', such as whether it's for initial query construction or a specific use case. This lack of differentiation results in minimal guidance.

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