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

Annotations already cover read-only safety, but the description adds substantial behavioral context beyond them: the 2-year maximum date range constraint and the specific auth requirement ('Read detailed stats' permission, delegated token support). These are non-obvious operational details that the annotations do not provide.

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 core purpose and date-range limit are front-loaded efficiently, but the token/permission boilerplate is verbose and partially redundant with the readOnly annotation. The structure is functional but not tight.

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 read-only analytics tool with no output schema and full schema coverage, the description covers purpose, return shape, range limit, and auth requirements. It is nearly complete; only explicit sibling routing would push it higher.

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 documents all parameters including the exclusive end_date semantics. The description only reinforces the date-range constraint (2 years), which is the one parameter-related fact not in the schema. Baseline 3 is appropriate.

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?

States a specific verb+resource ('Retrieve language analytics for a video') and describes the exact output breakdown (plays by viewer browser language, sorted descending). This distinguishes it from sibling analytics tools like get_media_stats and get_media_traffic_breakdown.

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 this is for language-specific analytics on a single video but names no alternative when a different dimension is needed (e.g., get_media_traffic_breakdown). Usage context is implied rather than explicit, which is the minimum viable level.

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