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

Annotations already establish readOnly/non-destructive/closed-world, so the bar is lower, yet the description adds real context: it is a stored table read (cheap, reliable), it covers the user's own apps plus competitors tracked under them, and a rival's finding never asks_action. It does not discuss rate limits or pagination beyond the schema-stated cap. Solid added value, not exhaustive.

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 scope and the cost/reliability rationale are front-loaded, and the enumeration of finding types is dense but useful. A few sentences carry rhetorical flourish ('how an assistant stops being believed') that is informative but slightly padded for a tool description. Still efficient overall.

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 an output schema present, return-value detail is not required, and the description covers scope (own apps + tracked competitors), cost profile, filtering behavior and the meaning of severity vs asks_action. Nothing an agent needs to invoke it is missing, though it could be tighter about interaction with sibling tools.

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 every one of the 8 parameters is already fully documented with defaults, formats and precedence rules. The description adds no per-parameter syntax or meaning beyond that, so the baseline 3 applies — the schema does the heavy lifting.

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 concretely what the tool returns: stored findings such as rank moves, chart entries, review spikes, competitor releases, price changes, plus own-app traffic/conversion shifts. That is far more specific than the tool name and lets an agent distinguish it from performance/history tooling. It does not, however, name a sibling tool it should be preferred over, so 4 rather than 5.

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?

It gives a clear selection rationale against a competing approach ('This is a stored table read, not a reconstruction, so it is both cheaper and more reliable than diffing rank histories yourself'). The include_sent parameter note also supplies conditional guidance ('Set it whenever you are about to summarise a period'). It stops short of explicit when-not-to-use or sibling routing, so not a 5.

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