graphql_query

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

With no annotations provided, the description carries full responsibility for disclosing behavior. It states it returns a dict with response or error information, but does not clarify whether this can execute mutations, require special permissions, or have rate limits. The term 'raw' hints at power but does not explicitly disclose risks.

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, with a clear purpose followed by Args and Returns sections. Every line adds value without redundant explanation.

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?

The description covers the basic purpose, arguments, and return type, and the presence of an output schema reduces the need to detail return values. However, it lacks guidance on when to use this raw tool versus siblings and does not mention potential side effects or use cases, leaving gaps for an AI agent deciding how to proceed.

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 schema has no descriptions for parameters, so the description's Args section adds meaning by specifying that query is the GraphQL query string and variables are optional. This is helpful, though it does not provide examples or constraints beyond optionality.

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 runs a raw GraphQL query against the sales API, using a specific verb and resource. The word 'raw' distinguishes it from the specialized sibling tools like get_order_by_id, indicating it is a low-level, flexible query mechanism.

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?

There is no explicit guidance on when to use this tool versus the specialized sibling tools. The description mentions it is a 'raw' query but does not state when it should be preferred (e.g., for custom queries not covered by get_* functions).

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