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

Annotations already declare readOnlyHint=true, destructiveHint=false, openWorldHint=true. Beyond that, the description discloses substantial behavior an agent could not infer: superseded_by semantics, withdrawn:true meaning a 철회신고서, version_check indicating incomplete checks, fetch_failed/truncated_note meaning 'unconfirmed' not 'none', and that 사모·일괄신고서·소액공모 are out of scope. This is rich, non-obvious operational context.

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 organized into [Purpose]/[Usage]/[Response]/[Rules] headers and is front-loaded with the core purpose. It is dense and lengthy, but nearly every sentence carries behavioral detail (superseded, withdrawn, fetch_failed, out-of-scope types), so little is pure filler.

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 by describing the return shape (filings[] per rcept_no, newest first, the named sections, date semantics, omitted '-' fields). Combined with edge-case rules for truncated, withdrawn, version_check, and out-of-scope types, an agent has everything it needs to interpret results correctly.

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%, so the schema already documents most parameters, giving a baseline of 3. The description adds value by reinforcing the window-widening advice ('keep the window wide') and clarifying that date = 접수일 and that 정정본 dates may fall outside the window, which informs how start/end should be set.

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 opening sentence names a specific verb (조회) and resource (증권신고서 주요정보 6종: 모집·매출 조건, 인수인, 자금 사용목적, 합병·분할 조건) returned as structured JSON. The [Purpose] block further distinguishes it from siblings by routing board decisions to get_corporate_event, listing scans to search_disclosures, and narrative risk factors to download_document. An agent can tell exactly what this tool returns and how it differs from neighbors.

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 [Usage] section gives a concrete trigger example ('대한항공 유상증자 조건' → corp/statement_type) and the [Purpose] block maps adjacent needs to specific alternative tools. It clearly frames the context for invoking this tool, though it stops short of explicitly stating exclusions like 'do not use for private placements' framed as guidance (that constraint appears later under [Rules]).

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