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

Annotations already declare readOnly, idempotent, non-destructive and closed-world, so the safety profile is covered. The description adds genuinely new context: results are capped at 10 per call, each carries measurement dates and AIFinder links, and the underlying attributes are measured on each official site — useful for judging data freshness and trust. It does not mention pagination limits or rate/auth constraints, which keeps it out of 5 territory.

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 compact English sentences plus a bracketed brand tag, front-loaded with the directory identity and scope before the query/return details. The Korean sentence largely mirrors the English, which is redundant for a monolingual reader but defensible for a Korean-market tool. Slight redundancy, no filler otherwise.

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 9 optional parameters and no output schema, the description carries real weight, and it does describe the return payload (up to 10 services, measurement dates, AIFinder links) and the verification model behind the data. What is missing is pagination behavior (the schema caps page at 3, implying a hard result ceiling) and any note on result ordering beyond the sort enum. Complete enough to call correctly, not complete enough to predict result counts.

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 56%, so the schema does part of the work (try, sort, query and category are documented inline; pricing and platform enums are not). The description adds that queries may be full natural-language sentences in Korean or English and that filter-only browsing is possible, which is real added meaning. But it gives no guidance on how the 9 filters combine or which combinations are meaningful, so it does not fully compensate for the coverage gap.

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?

Names a specific verb+resource ('Search AI services listed on AIFinder') and identifies the corpus: a Korean AI-tool directory with verified Korean-language, KRW, business-registration and trial conditions. That is far more than a restatement of the name. It stops short of a 5 because it never distinguishes itself from siblings like get_ai_service, find_alternatives or list_categories, so the agent must infer that this is the discovery entry point rather than a detail or comparison call.

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: 'Accepts natural-language Korean or English queries and filters' tells the agent what inputs work, but there is no statement of when to choose this over find_alternatives or get_ai_service, and no exclusions. The 'Omit to browse by filters only' guidance lives in the schema, not the description. Adequate but the routing decision is left to inference.

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