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

Annotations already mark the tool as read-only and open-world, so the safety profile is covered. The description adds value beyond annotations by stating the tool is free and by specifying exactly what the response contains, which is especially useful because no output schema exists.

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 short sentences with no redundancy: the first front-loads the core purpose, the second conveys a critical usage warning, and the third notes cost. Every sentence earns its place.

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 two-parameter retrieval tool with full schema coverage and read-only/open-world annotations, the description plus schema fully equips the agent: what to pass, what to expect back, why it matters, and that it is free. The enumerated return values compensate for the missing output schema.

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 the schema already fully documents the template parameter (including version pinning) and include_source. The description adds no parameter-specific detail beyond pointing to the 'data' argument contract, so the baseline score of 3 applies.

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 uses a specific verb ('Fetch') and clearly identifies the resource ('one template version') while enumerating the exact payload components: JSON Schema, default render options, example payload, and HTML source. This immediately distinguishes it from sibling tools like get_render and list_templates.

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 explicitly instructs the agent to read the schema before rendering, positioning this tool as a prerequisite for render or validate_data workflows. It does not explicitly name alternative tools for rendered output, but the usage context is clear.

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