DART-MCP

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

With no annotations provided, the description explains that the tool filters disclosures based on data availability for requested items and describes the return format as summary text ('주요 재무 정보 요약 텍스트'). However, it omits operational details such as rate limits, authentication requirements, or error handling behaviors that would be necessary for full 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 follows a clear docstring structure with purpose stated first, followed by detailed Args and Returns sections, making efficient use of space. While detailed, the parameter documentation is necessary given the complete lack of schema descriptions, though the inclusion of 'ctx' (not present in the schema) slightly detracts from precision.

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 lack of annotations and schema descriptions, the description adequately covers the tool's purpose, parameter usage with examples, and return value format ('검색된 각 공시의 주요 재무 정보 요약 텍스트'). It could be improved by adding error scenarios or operational constraints, but provides sufficient information for correct invocation despite the complexity of date range searching and item filtering.

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?

The description comprehensively compensates for the 0% schema description coverage by providing detailed semantics for all parameters, including format examples for dates (YYYYMMDD), example company names ('삼성전자, 네이버'), and an enumerated list of valid financial items for requested_items. It clearly documents the default behavior when requested_items is None.

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 searches and provides major financial information of companies ('회사의 주요 재무 정보를 검색하여 제공하는 도구'). It specifies that it targets disclosures ('공시') and mentions the filtering capability by specific financial items, which helps distinguish it from sibling tools like search_detailed_financial_data, though it lacks explicit comparative guidance.

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 explains the filtering behavior when requested_items is provided versus when it is None, indicating when disclosures will be returned based on data availability. However, it lacks explicit guidance on when to choose this tool over siblings such as search_detailed_financial_data or search_json_financial_data.

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