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

The tool defines a specific behavioral characteristic: data is returned as 'relative peak-normalized scores.' This explains the *nature* of the output data (relative vs. absolute) which is a crucial behavioral trait beyond the scope of standard annotations like 'readOnlyHint.'

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 extremely concise, using only two sentences. Both sentences are essential, with the first defining the function and the second clearly stating the critical limitations, resulting in zero wasted language.

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 combination of the description (data type, normalization, limitations) and annotations (read-only, safe) provides a complete and high-confidence context for the agent. While it doesn't detail the return format (which is common for read-only tools), it covers all semantic ground necessary for a correct tool invocation.

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?

Given the 50% schema coverage, the description helps define the granularity and output structure by specifying the demographic dimensions (age and gender) used for the data breakdown. This provides necessary semantic meaning that a pure schema definition would lack, compensating for the moderate coverage 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 purpose is clearly defined: providing 'Nexscope Trends relative keyword interest' specifically broken down by 'age and gender.' This scope is highly specific and clearly differentiates it from general keyword volume or broader demographic tools in the sibling list.

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 provides strong usage boundaries by explicitly stating what the tool *does not* infer ('population shares, counts, income, or unreturned demographic buckets'). This manages user expectations and steers the agent away from misuse by preventing false assumptions about absolute data.

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