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

Annotations already declare readOnlyHint=true, so safety is covered and the description is free to add other context. It does so usefully: it separates measured facts (prices measured on store pages, cost per click measured) from modelled assumptions (conversion, price, months), and states that economics.estimate is true with economics.basis listing both. That is real behavioral context an agent would otherwise have to discover. It says nothing about report freshness, failure modes for an unfinished scan, or size/latency, which keeps it off a 5.

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 purpose is front-loaded in the first clause, which is good. However, the body is a single sprawling sentence with deeply nested parentheticals enumerating every report section, which makes it dense to scan and pushes the format guidance to the very end. The content is relevant but the packaging costs readability.

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?

There is no output schema, and the description compensates thoroughly by describing the returned sections and the JSON key set. For a two-parameter read-only tool whose schema is fully documented, an agent has everything needed to call it and interpret the result.

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 explains both parameters, and the baseline is 3. The description adds some value by spelling out what format 'json' yields (verdict, product, economics, prices, seo, aso, names, landing, channels, validation, risks, neighbours, next_checks) and by confirming markdown as the reading default, but the id semantics are essentially restated from 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 opens with a specific verb and resource: it returns the final niche report of a finished scan, or the report research itself, in Markdown. It enumerates the report's sections concretely (verdict, product, prices, economics, SEO, ASO, names, landing, channels, validation, risks), so an agent knows exactly what it gets. It does not, however, distinguish itself from get_research or get_project, so sibling selection still requires inference.

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?

Usage is only implied by the phrase 'of a finished scan', which suggests the tool is for completed research. The description does route the agent elsewhere for one follow-up action ('start_research with the phrase and the same country checks one'), but that is guidance for what to do with next_checks, not guidance on when to call get_report instead of get_research or list_research. No exclusions or prerequisites are stated.

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