Skateboard Personalizado

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

Annotations already flag this as a non-read-only, non-idempotent, non-destructive, closed-world write; the description reinforces non-idempotency ('Each successful call creates a new design') and adds genuinely new behavior: the design is stored unlisted, no AI artwork is produced, and no order is placed. It also discloses the full return surface, which no output schema covers.

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?

Three tight sentences: what it saves and returns first, then the input either/or, then the behavioral caveats (unlisted, no AI art, no order, new design each call). No filler and the most decision-relevant facts are front-loaded.

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 mutation tool with no output schema and a nested composition object, the description covers the return values, the either/or input and the side-effect profile. The notable remaining gap is locale (language of the returned link/preview), which is undocumented in both schema and description and could affect an agent's default choice.

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 80%, so the schema carries most parameter meaning (fit, background, composition element geometry). The description adds the crucial cross-parameter constraint that exactly one of image_base64 or composition is accepted, which the schema does not encode since all properties are optional. The locale parameter remains unexplained in both places.

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?

Opens with a specific verb and resource: 'Saves finished artwork on a skateboard deck', then states the returns (3D preview/edit/order link plus an assembled-with-trucks picture). An agent can tell this apart from get_deck_spec by the outcome described. It stops short of explicitly naming the sibling and contrasting the two, so 4 rather than 5.

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?

Gives a hard input rule ('Takes exactly one of image_base64 or composition') and clears up two likely misuses: it generates no AI artwork and places no order. It also warns that each call creates a new design, implying retries duplicate. No explicit pointer to an alternative tool for read-only spec lookups, so usage context is clear but not fully routed.

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

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

Annotations already cover the safety profile (readOnly, idempotent, non-destructive, closed-world), so the lower bar applies; the description still adds real context by disclosing what information is returned, including the 'upload alternative' and the 'current' (i.e., time-sensitive) price. It does not discuss caching, staleness, or format of the response, which keeps it short of a 5.

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?

A single sentence that front-loads the verb and packs four concrete return items plus a timing cue with no filler. Every clause carries 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?

With no output schema, the description correctly takes on the burden of describing return contents, and with no parameters and full annotation coverage the remaining surface is small. Minor gap: it never states the response shape or units (e.g., dimension units) an agent might need when consuming the result.

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?

Zero parameters, so per the rubric the baseline is 4; there is nothing for the description to clarify. The listed items describe return content rather than inputs, which is appropriate for a no-arg tool.

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?

Names a specific verb ('Get') and resource ('deck specifications') and enumerates the concrete payload: artwork dimensions, supported formats, upload alternative, current deck price. An agent can distinguish it from the sibling create_deck (read specs vs. create), though the description never names that sibling explicitly.

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 trailing clause 'before preparing a design' hints at the right moment to call it, but there is no explicit when-not guidance, no prerequisite statement, and no routing to or away from create_deck. Usage is implied rather than stated.

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