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 that recommendations are grounded in recent video performance, which is useful context, but says nothing about response shape or what the modes return. With annotations carrying the behavioral load, a 3 is appropriate.

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: the first defines the resource and scope, the second lists usage triggers. Nothing is wasted and the purpose is front-loaded.

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 recommendation tool with full schema coverage and no output schema, the description covers purpose, scope, and when to invoke. A brief note on what the recommendations look like or how modes differ would make it complete.

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 all three parameters are documented in the schema itself. The description only indirectly hints at the mode semantics through the word 'coaching' and does not clarify the cryptic 'working/slump/idea' coach-card modes, so it adds little beyond the schema. Baseline 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?

States a specific verb and resource ('Get Viral Studio recommendations for short-form videos') and names the three platforms covered. It is clearly distinguishable from data-retrieval siblings like get_account_stats, though it does not explicitly differentiate itself from get_viral_studio_overview.

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?

Gives concrete usage triggers: 'when someone asks what to do next,' 'wants coaching on short-form strategy,' or 'wants cross-platform recommendations based on recent video performance.' It lacks an explicit 'do not use when...' or a named alternative such as get_viral_studio_overview, which keeps it from a 5.

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