read_stored_data

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

The description discloses chunking behavior, default chunk size, and return format including meta, data, and chunk_info. It mentions that without chunk_index, all data is returned. No annotations are provided, but the description adequately covers behavioral traits.

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 concise and well-structured with clear sections (Args, Returns, Example). Every sentence adds value, and the example clarifies usage without redundancy.

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 moderate complexity, the description covers all necessary aspects: parameter explanations, return format with example, and reference to sibling tools for obtaining data_id. It is complete despite missing annotations.

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 0%, so the description compensates by explaining each parameter: data_id source, chunk_index start and optionality, chunk_size default. This adds meaning beyond the schema alone.

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 purpose: '저장된 원본 데이터를 읽습니다' (reads stored original data). It specifies the resource (stored data) and verb (read), and distinguishes from sibling tools that focus on statistics or browsing.

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 when to use the tool (to read stored data, with chunking for large data) and provides examples. It does not explicitly state when not to use or compare to alternatives, but the context is clear.

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