Get AI Category Market Landscape

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

Annotations already declare readOnly/idempotent/non-destructive, so the bar is lower. The description adds genuine context beyond them: numbers are computed from live catalog data at request time and are explicitly not predictions or estimates, which tells the agent to treat output as current factual state rather than a forecast.

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?

One front-loaded sentence that leads with the core payload and closes with a scoping disclaimer. It is slightly long because of the 'never a prediction, estimate, or industry-wide claim' clause, but that clause earns its place by bounding the data's authority.

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-value explanation is not strictly required, yet the description still previews the metric set, which helps an agent decide whether to call it. With annotations covering safety and the schema covering the sole parameter, the definition is complete enough for a one-parameter read tool.

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% and the single 'category' parameter is already documented with slugs and a fallback path (search_ai_tools/browse). The description adds no syntax or format information beyond the schema, 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?

The description names a specific verb and resource (a computed statistical snapshot of one category) and enumerates the payload: tool count, score distribution, top-scoring tools. It distinguishes itself from most siblings, though it does not explicitly differentiate from the closest sibling get_site_stats (site-wide vs category-scoped).

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 explicit when-to-use/when-not-to-use guidance or named alternative for the statistical use case. The only routing hint is inside the schema ('use search_ai_tools or browse to find valid category slugs'), which addresses slug discovery rather than selecting this tool over get_site_stats or compare_ai_tools.

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