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

With no annotations, the description carries the full burden. It does disclose the data sources and competitive scope, but it does not mention default behavior (e.g., 30-day window), output format, or any constraints such as data availability. This is adequate but 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?

Two tight sentences with the core action and metrics first, and the scope in the second. No filler or repetition of parameter names.

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 simple tool with two optional parameters and no output schema, the description covers purpose, metrics, and scope. It could mention the output shape or default window, but nothing critical prevents a correct call.

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 coverage is 100%, so the baseline is 3, but the description adds real meaning by mapping the metric enum to 'npm weekly downloads' and 'GitHub stars.' It does not add detail on the windowDays parameter, but the schema already explains the allowed values and default.

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 resource ('SDK/package adoption trends') and concrete metrics ('npm weekly downloads and GitHub stars'), so an agent knows exactly what the tool returns. It also states the competitive scope, which distinguishes it from other read-only analytics tools among the many devtune_get_* siblings.

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 phrase 'adoption trends' implies when the tool is appropriate, and the scope ('primary domain and competitors') is useful context. However, it gives no explicit when-not-to-use guidance or alternatives, even though sibling tools like devtune_get_competitive_position and devtune_get_visibility_summary could overlap in an analytics context.

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