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

Annotations already establish readOnlyHint=true and openWorldHint=false, so safety is covered. The description adds one genuinely useful behavioral fact — no scan credits are consumed — but with no output schema it should say more about what the returned payload actually looks like beyond 'a realistic sample'.

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 short sentences, front-loaded with what the tool returns and immediately followed by why you'd call it. Nothing is padded or repeated from the title.

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 zero-required-parameter, read-only fixture tool with a fully documented enum, the description gives enough to call it correctly and know why. The only gap is that, absent an output schema, it doesn't characterize the shape of the sample response it returns.

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?

Schema coverage is 100% and the single optional enum is fully documented in the schema, so the baseline is 3. The description loosely groups the scenarios into 'success, an unreliable photo, errors and progress results', which adds a little orientation but does not cover all six enum values or explain the two progress variants.

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 names a specific resource ('a realistic sample of any Body Scan API response') and its use case ('build and test the UI'), so an agent knows exactly what comes back. It doesn't explicitly contrast itself with nearby siblings like get_code_example or get_endpoint_reference, so the sibling differentiation is only implied.

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?

'so you can build and test the UI without spending scan credits' gives a concrete condition for reaching for this tool rather than the live scan path. There is no explicit when-not guidance or named alternative for fetching reference material, which keeps it below a 5.

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