generate_query_template

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

No annotations exist, so description carries the burden. It explains that the output is a template with useful fields and relationships, and mentions the output structure (data.template). However, it lacks details on error cases (e.g., invalid entity) or performance implications.

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 concise and well-structured. It starts with the main purpose, then lists parameter descriptions, and ends with the workflow placement. Every sentence adds value 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 three parameters, no output schema, and no annotations, the description sufficiently covers purpose, parameters, return value, and context within the sibling workflow. It enables an agent to use the tool effectively.

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?

With 0% schema description coverage, the description provides clear explanations for all three parameters: entity_name with examples, include_relationships stating its purpose, and max_fields describing its control over template size. This adds value beyond the raw schema.

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 it generates a ready-to-use GraphQL query template for any data type, with specific verb+resource. It explicitly places itself in a workflow sequence (get_schema_summary → get_schema_entity → here → validate_query → execute_graphql), distinguishing it from siblings.

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?

Provides the intended workflow and prerequisite (entity name from get_schema_summary). While it doesn't explicitly exclude alternatives, the workflow gives clear context on when to use this tool in the pipeline.

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