get_disclosure

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

In addition to the annotations (readOnlyHint, openWorldHint, idempotentHint), the description reveals the tool's data-source behavior (KOSCOM, Naver) and its boundary (does not include company press releases or media articles). This informs correct interpretation of empty results. However, it does not detail pagination, date range, or result ordering, which would further enhance transparency.

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 well-structured: a one-line definition, a usage-routing paragraph with examples, a critical caveat, and a clear Args section. Every sentence adds value and the most important usage guidance is front-loaded.

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?

Given the tool's simplicity (single parameter) and the presence of an output schema, the description covers the essential usage context: source, when to use, and how to interpret empty results. It doesn't specify the number of disclosures returned or time range, but these are likely evident from the output schema, so the description is sufficiently complete.

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?

With 0% schema description coverage, the burden falls entirely on the description. It compensates by defining 'code' as a 6-digit stock code and providing an example ('005930'). This is sufficient for correct invocation, though it omits variations like leading zeros or alternative formats.

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 clearly states the tool's function: '공시목록 — 종목의 최근 거래소 공시 목록' (disclosure list of recent exchange disclosures for a stock). It also specifies the data source (Naver Finance, KOSCOM) and explicitly excludes related but distinct concepts like press releases and media articles, distinguishing it from siblings like get_news and get_reports.

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 description gives concrete query examples ('공시', 'IR', '실적 발표', '공정공시', '오늘 왜 오르나(재료 확인)') and adds a critical exclusion: zero disclosures does not mean 'no materials' because press releases and news are not in this list. This effectively routes an agent to use this tool only for exchange disclosures and to consider alternatives for broader news.

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