debug_request

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

With no annotations, the description transparently describes the tool's behavior (GET request, return format) and parameter details (path format). It adequately covers the key behavioral aspects without contradictions.

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 very concise: a single sentence with a clear structure followed by bullet-pointed parameter details. No extraneous 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 that the tool is a simple debug GET with an output schema, the description covers the essential aspects: purpose, parameters, and return format. It could be slightly more detailed about the output schema but is sufficient.

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?

Since the input schema has 0% description coverage, the description adds valuable meaning: it clarifies that the path parameter may start with '/v1/' or 'v1/', and that query is an optional dictionary. This compensates for the schema's lack of descriptions.

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 is a low-level debugging helper that makes a GET request and returns status, headers, and a body preview. This is specific and distinct from sibling tools focused on user/organization data, but it does not explicitly highlight the 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 'low-level debugging helper' label implies usage for debugging rather than production, but there is no explicit guidance on when not to use it or mention of alternative tools for regular data retrieval.

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