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

Annotations already declare readOnlyHint, idempotentHint and destructiveHint=false, so the safety profile is covered. The description still adds real content beyond them: results are broken out per engine, and Gemini and Grok answer from model knowledge and carry no citation URLs — a data-quality caveat an agent would otherwise misread as missing data.

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?

Three short sentences with the core purpose front-loaded, followed by return-shape and caveat. No filler, no repetition of the title, and the most easily misread detail (missing citation URLs) is stated up front rather than buried.

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?

An output schema exists, so return values need not be spelled out, and the annotations cover safety. However, the description never clarifies what one 'analysis' entity is, whether results are the latest run or historical, or how limit interacts with the per-engine grouping — gaps that matter for a list-style analytics tool with a cluster filter.

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% — both limit (1-50, default 20) and cluster_id are documented inline — so the baseline of 3 applies. The description adds nothing about either parameter, and notably never explains that cluster_id narrows the analysis to a single tracked cluster.

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?

"Get GEO (Generative Engine Optimization) analyses" names a specific verb and resource and expands the acronym, then scopes it to brand mentions across five named engines. That is enough to separate it from siblings like get_metrics or list_llm_sources, though it never explicitly contrasts itself with them.

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 when-to-use statement, no exclusion, and no pointer to an alternative such as get_metrics or list_missed_citations. The agent must infer from the purpose sentence alone whether to call this or a neighbouring analytics tool, and the availability of the cluster_id filter is never tied to a use case.

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