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

Annotations already declare readOnlyHint=true, idempotentHint=true, and destructiveHint=false, so the safety profile is covered. The description adds valuable context beyond annotations: the data is embedded as curated static reference, no API key is required, and the source is the 2023–2024 Kitces Research survey. This helps the agent understand the tool's behavior (no live query, no auth needed) without contradicting the annotations.

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: the first sentence states the core purpose, followed by a bulleted list of categories, then the default behavior, source, and auth requirement. Every sentence earns its place, and the structure makes the tool's scope immediately scannable.

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?

The description is complete for the tool's primary use case: retrieving benchmark data by category. It covers the default, the source, and the auth requirement. The output schema exists, so return values are documented elsewhere. The only gap is that the description doesn't mention the filtering/tracking parameters (wholesaler_ids, question_asked, etc.), but those are secondary for this tool and are documented in the schema.

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 must compensate. It does so by explaining the 'category' parameter's options and default ('all'), and by listing the five category values. However, the description does not explain the other parameters (mcp_prompt_id, question_asked, wholesaler_ids, etc.), which are documented in the schema but not in the description. Since the description covers the primary parameter well but ignores the rest, a 4 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 states a specific verb ('Return'), a clear resource ('Kitces Research advisor practice benchmark data'), and the target audience ('independent and RIA-affiliated financial advisors'). It enumerates five concrete metric categories, which distinguishes it from sibling tools that focus on tickers, filings, or fund data. The tool's purpose is unmistakable even without opening the schema.

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 gives clear context on what data is included and how to retrieve all categories at once ('Set category='all' (default)'). It also notes the data source and that no API key is required. However, it does not explicitly state when to use this tool versus alternatives or when not to use it, so it falls just short of a 5.

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