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

No annotations are supplied, so the description bears full responsibility for disclosing behavior. It only states the source and categories of retrieved data; there is no information about side effects, read-only expectation, computation involved, rate limits, or output fidelity. For a read-style tool this is minimal and leaves behavioral assumptions to the agent.

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 a single, efficient sentence that front-loads the verb and clarified resource. It is not redundant and earns its words. It loses a point because the three data categories are packed together without any formatting that could make them scan more clearly.

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?

With no output schema and no annotations, the description must carry return-format expectations. It lists the three data categories being returned, which provides a basic notion of output content. However, it leaves terms like 'confirmed transitions' and 'sitemap submission evidence' undefined, and does not specify the structure or aggregation, so completeness is just adequate.

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?

The input schema already provides full coverage of the two parameters with descriptions, defaults, constraints, and enums. The description's phrase 'fixed-window facts' minimally reinforces the windowDays parameter but adds no meaningful insight beyond the schema. Baseline 3 is appropriate when schema covers 100% of parameters.

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 and identifies three concrete data resources: Google eligibility dimensions, confirmed transitions, and sitemap submission evidence. It also names a source scope, fixed-window facts, which distinguishes it from sibling analytics tools. However, it does not explicitly contrast it with a sibling or scope out what it does not return.

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?

There is no guidance on when to choose this tool over the many other devtune_get_* siblings. The description gives no selection criteria, prerequisites, or examples of contextual use. An agent is left to infer its purpose from the name alone.

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