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

Annotations already cover idempotency and non-destructiveness, so the description's job is lighter. It adds useful context about what the tool returns and that platform affects pattern matching, but it does not clarify whether any state changes occur or how much input content is processed. This is acceptable given the annotations, but still not rich.

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 description is compact and front-loaded, with a clear first sentence of what the tool does, followed by the result components and the explicit usage cases. Every sentence earns its place without redundant 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?

Given the simple parameter count, full schema coverage, available annotations, and presence of an output schema, the description is complete enough for an agent to invoke this tool correctly. It covers the target content, the decision, and the expected output categories.

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 `text`, `niche`, and `platform`. The description adds no per-parameter semantics beyond a minor mention that the platform affects pattern matching, which is already implied 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?

The description uses a specific verb ('Score') and identifies the exact resource ('a TikTok, Reels, or Shorts hook') plus the method ('against proven viral patterns'). It clearly distinguishes this from sibling tools by focusing specifically on hooks and their improved variations, rather than broader virality prediction or account analysis.

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 states when to use the tool: 'Use when the user has a draft hook to validate, wants to compare alternatives, or needs feedback before publishing.' It provides clear invocation context but does not name alternative tools or include explicit when-not-to-use guidance, keeping it one step below full differentiation.

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