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

Annotations already mark the operation as read-only, and the description adds useful behavioral context: it is a computed/aggregate scoreboard, returns deltas and trends, works in a single call, and requires an Indie plan. No contradiction exists between the description and the readOnlyHint annotation.

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 detailed but stays on-topic and front-loads the core concept. Every clause contributes useful information about what the result includes, when to call it, or plan requirements. The long listing of output components is justified because there is no output schema to carry that information.

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?

Given there is no output schema, the description does a good job enumerating the returned dimensions: 7-day deltas, spark data, top-10 keywords, rank distribution, and opportunity types. It also covers plan constraints and the recommendation to call this before computing from raw history. A small gap is not describing how errors or untracked apps are surfaced, but overall it is sufficient.

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 100%, so the schema already thoroughly documents both `app_id` and `days`, including that `app_id` is not a store id. The description itself adds little parameter-level detail beyond restating that the tool targets one of your own apps, so it meets the baseline without meaningfully extending the schema.

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, descriptive framing: a dashboard scoreboard for one app, listing exact metrics (visibility index, share of voice, keyword counts, rank distribution, opportunities). It clearly distinguishes this from raw rank-history tools by stating it returns the same computed numbers the dashboard renders, making its purpose unmistakable.

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 explicit when-to-use guidance: 'Read this FIRST when asked how an app is doing.' It also provides a when-not-to guidance by saying you don't need to recompute from raw rank history. It does not name specific sibling alternatives, but the context is clear enough for an agent to route to this tool appropriately.

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