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

Annotations already declare readOnlyHint=true, but the description adds significant behavioral context beyond that: date is the filing date while event dates are in raw row fields; holdings counts distinguish all-time cumulative from in-period values; DART accepts no dates and filters client-side; an empty timeline does not mean no events; and event_type_counts is pre-truncation. These are exactly the kind of non-obvious behaviors an agent needs to interpret results correctly.

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?

The description is long, but the Purpose/Usage/Response/Rules structure front-loads selection guidance and each section contributes non-redundant caveats. Some content overlaps with the already-detailed schema, and the Korean/English mixing adds length, but the density of operational guidance warrants the size.

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 compensates well by covering response date semantics, holdings count semantics, per-endpoint error indicators, truncation behavior, and default event-type selection. It does not fully enumerate response shapes for all 38 event types, but for a tool of this complexity the critical invocation and interpretation context is 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 coverage is 100% and the event_type parameter description is already very rich, including enums, aliases, automatic mode switching, and array behavior. The description adds practical value through usage examples that show valid parameter combinations, such as event_type arrays with start dates, and it clarifies how defaults behave in timeline mode. This justifies slightly above the baseline 3 for fully-schema-documented parameters.

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 opens with a specific verb and resource: it queries 주요사항보고서 capital/governance events (36 types) plus 5% rule and executive equity disclosures. It also explicitly names sibling tools for adjacent use cases, such as get_registration_statement and search_disclosures, so an agent can distinguish this tool from alternatives without inferring.

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 Purpose section gives concrete routing rules: for subsequent issuance/merger conditions use get_registration_statement, for list skims use search_disclosures, and for annual report snapshots use get_periodic_report. The Usage section provides three example user intents mapped directly to corp, mode, event_type, and start, making when-to-use guidance explicit rather than implied.

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