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

Annotations already declare the full safety profile (readOnlyHint=false, destructiveHint=true, idempotentHint=false, openWorldHint=true). The description adds genuinely useful non-annotation context: the operation consumes SEO add-on credits and requires a top-up. However, it does not explain the refresh behavior or why the call is non-idempotent/destructive, leaving annotation and description loosely reconciled.

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?

Front-loaded with the core purpose, then the metric list and the cost caveat. The metric enumeration ('positive/negative/neutral sentiment split, the emotions behind those mentions') is slightly padded but each clause contributes to what the tool returns.

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?

Output schema exists, so return values need not be explained, and the credit/top-up caveat covers the main operational concern. The remaining holes are the undocumented 'refresh' parameter and no clarification of why a monitoring tool is marked destructive/non-idempotent — modest but real gaps for a 2-param tool.

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 0%, so the description carries the burden for both parameters. It implies a brand name input, but says nothing about the 'refresh' boolean: no meaning, no default, no cost/rate implications (the credit-cost note never ties to refresh). With low coverage and an entirely undocumented parameter, this is a clear gap.

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 names a specific capability (brand mention and sentiment monitoring) and enumerates what it returns: mention frequency, sentiment split, emotions, and top domains. It also explicitly positions itself against the nearby sibling 'AI-citation (GEO)', so an agent can distinguish it from seo_geo_citations/seo_geo_tracker without opening schemas.

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?

It gives clear context for use ('reputation and brand tracking') and names the tool it complements ('complements AI-citation (GEO)'), which effectively routes the agent between brand sentiment and GEO citation work. It stops short of explicit when-to-use/when-not statements or prerequisites.

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