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

Annotations already declare readOnly/idempotent/non-destructive, so the description is free to add value, and it does: change-from-previous-period comparisons, an extra 'locations' block for multi-location brands, competitor ordering 'weakest first', and the counted_engines note. That said, pagination/response limits and empty-state behavior are unaddressed.

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?

Front-loaded with the core question and then the two modes, with no filler. The final sentence is long and slightly run-on, but every clause conveys distinct output structure.

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 four optional parameters, the description carries the return-shape burden and does so by describing what each by mode yields plus the location block. Minor gaps remain (what an engine with no data returns, how window_days interacts with the 'change' comparison), but the essentials are present.

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 documents every parameter including the engine defaults and brand_id omission rule. The description's mention of the by default and engine list largely restates the schema rather than adding new syntax or constraints, so the baseline 3 applies.

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?

States a specific resource (brand mention visibility across named AI engines) and enumerates the exact metrics returned, so the agent knows this is the analytics read for AI-answer mentions. It does not explicitly distinguish itself from close siblings like get_citations or get_competitors, which leaves some ambiguity about which tool answers which question.

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 by=engine/by=question split gives clear mode selection with a stated default, which is real usage guidance. However, there is no guidance on when to call this instead of get_citations, get_competitors, or get_changes, and no prerequisites or exclusions are mentioned.

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