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

Annotations already declare readOnlyHint=true and openWorldHint=false, so the safety profile is covered. The description adds real context beyond that: 'No cost, no allowance used' (quota behavior) and the code-point vs UTF-16 measurement nuance, which is non-obvious behavior for emoji-containing text.

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 tight sentences with the core measurement claim front-loaded; each clause carries information. Slightly dense with three numeric examples, but nothing is filler.

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?

There is no output schema, so the description carries the return-value burden — and it does, describing both the limit outputs and the dual code-point/UTF-16 measurement. Nothing an agent needs to call this correctly is missing.

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%, so the baseline is 3, but the description adds concrete semantics for the 'field' enum by giving actual limit values (title 100/search ~60, description 5000/~120 visible), which enriches the choice beyond the bare enum labels.

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?

Specific verb+resource: counts text against YouTube's limits, and names the exact metrics reported (hard cap, softer cutoff, code points vs UTF-16 units). Clearly distinguishes from siblings like runsheet_style_text or runsheet_preserve_line_breaks, which transform rather than measure text.

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 when you'd use it (to check whether text fits YouTube's display limits), but never states prerequisites, when-not-to-use, or how it relates to alternatives such as style_text. Usage context is inferred rather than stated.

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