get_example

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

With no annotations, the description carries the burden of behavioral disclosure. It states the tool returns a full JSON spec and that the name comes from list_examples, but it does not mention potential errors, authentication requirements, or whether the operation is read-only. This is adequate for a basic fetch but lacks depth.

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?

Two sentences, front-loaded with the purpose, followed by concise usage guidance. Every word serves a purpose with no redundancy or filler.

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?

For a simple one-parameter tool with no output schema, the description sufficiently explains what is returned (full JSON spec) and how to use it (as a template, preserving track structure). It references list_examples for discovery, making the tool self-contained in context. Missing details like exact return format or error cases are minor given the tool's simplicity.

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 covers the 'name' parameter completely with a clear description, and the tool description reinforces the source (list_examples) but adds little beyond the schema. Baseline of 3 is appropriate because the schema already documents the parameter well.

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 fetches a full JSON spec for a named example, distinguishing it from list_examples (which lists examples) and other sibling tools. The verb 'Fetch' and resource 'full JSON spec of a named example' are specific and actionable.

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 clear guidance on how to use the returned spec (as a starting template, with specific modifications like icons and labels) and implies the discovery flow via list_examples. It does not explicitly state when not to use this tool, but the context is sufficient for a simple fetch operation.

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