recommend_text_size

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

No annotations are provided, so the description carries the full behavioral burden, yet it discloses nothing about how sizing is computed, what units are returned, whether face geometry is required, or what the defaults mean. A single marketing sentence is far below the minimum for a five-parameter calculation tool with no annotations or output schema.

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?

It is a single short sentence with no wasted clauses, so it is concise and front-loaded. However, the brevity is under-specification rather than efficiency, and 'one-stop' is promotional filler that does not earn 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 tool with five parameters, 40% schema coverage, no annotations, and no output schema, the description is essentially absent. An agent cannot tell what a valid call looks like, what the result represents, or how to interpret face_fill_pct and face_width_mm.

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 only 40%, and the description adds no parameter-level meaning at all. It does not explain product_type, face_name, char_count, face_fill_pct, or face_width_mm, leaving required inputs and the two optional numeric defaults undocumented.

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 says it is a 'text-sizing helper for product decoration,' which vaguely restates the tool name without specifying that it returns a recommended text size from product type, face name, and character count. It does not distinguish this from siblings like get_face_emboss_depth, describe_face, or list_decoratable_faces.

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?

There is no guidance on when to use this tool versus alternatives, no prerequisites, and no exclusions. The phrase 'one-stop' implies broad applicability but gives the agent no routing signal among the many decoration and face-related siblings.

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