validate_prompt

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

With no annotations, the description must carry the full burden. It lists the checks performed, which gives some behavioral insight, but does not disclose whether the tool is read-only, what it returns (e.g., pass/fail, issues list), or any side effects. The presence of an output schema is noted but its content is not described. More detail on output behavior would improve transparency.

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: a single opening sentence with the verb and resource, followed by a bulleted list of checks. Every line adds value, and the content is front-loaded with the core purpose immediately.

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 the tool has 4 parameters and an output schema, the description covers the main validation checks but lacks guidance on when to use it relative to siblings and does not describe expected output behavior (though output schema exists). No annotations add further gaps. It is adequate but not rich enough for complete agent decision-making.

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 description coverage is 100%, so baseline is 3. The description adds context about prompt validation rules, which complements the prompt parameter, and mentions resolution compatibility, which relates to width/height. However, it does not add detailed semantics beyond the schema for negative_prompt or width/height.

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's purpose: 'Validate a prompt against Animagine XL rules.' It lists specific checks (quality tags, ordering, tag count, consistency, resolution), making the scope precise. This distinguishes it from sibling tools like optimize_prompt (which improves) and explain_prompt (which explains).

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 implies usage by listing validation checks, but it does not explicitly say when to use this tool versus alternatives. For instance, it does not mention using this before generation or that optimize_prompt is for adjustments. No explicit when/when-not guidance is provided, only implied context.

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