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

Annotations already cover the read-only, open-world profile. The description adds real value beyond them: the exact cost per call (50포인트) and a hard boundary that source documents are excluded, plus the return shape. It does not clarify how pagination interacts with an aggregated response, which is a small residual gap.

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?

Core facts (classification scope, output fields, cost) are front-loaded, but the English and Korean sentences are parallel restatements of the same content, so roughly half the text is duplication. Nothing irrelevant, though not maximally economical.

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, the description steps in to enumerate the return sections (summary, distribution, timeline, high_risk, insights), and it discloses cost and the absence of raw filings. Annotations handle safety. For a 5-param analytical tool this is close to complete, lacking only usage routing to siblings.

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 all five params (pageNo, numOfRows, startDate, endDate, corpCode) are already documented. The description adds no date-format or corpCode guidance beyond the schema, and its 'no raw list' claim slightly muddies why pagination parameters exist. 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 verb+resource: analyzing Korean corporate disclosures into event types with density and risk timelines. It also names the concrete output sections, so the agent knows exactly what the tool produces. It never names its nearest siblings (dart_company, dart_financials), so differentiation is only implicit.

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 line '원문 목록은 제공하지 않습니다' (no raw filing list is returned) implicitly steers the agent elsewhere when raw documents are wanted, and the response-field list signals when this analytical view is right. But no sibling is named and no explicit when-to-use/when-not rule is given.

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