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

Beyond the annotations (readOnly, idempotent, openWorld, non-destructive), the description discloses authentication behavior (the caller's X-DataGoKr-Key may be needed for API fallback), a privacy guarantee (keys are never returned or stored), result caps (50 columns / 20 rows, 5 rows for Seoul/Gyeonggi public paths), and failure semantics (ok=false means the portal is not responding right now, retry later; deleted IDs return deleted and alternatives). That is genuine behavioral context the annotations cannot convey.

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 purpose is front-loaded in the first sentence, which is good. However, the Korean and English halves largely duplicate each other (including a repeated explanation of data/columns/rows and ok=false), which roughly doubles the length without adding information, and the return-value prose is redundant given an output schema exists.

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?

For a tool whose behavior branches across many dataset types, this description covers the important branches, the key/auth caveat, the row/column caps, and error recovery. Since an output schema exists, the detailed return-field walkthrough is surplus rather than necessary, but nothing critical to calling it correctly appears to be missing.

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 0%, so the description carries the full burden for the two parameters. It implies what dataset_id means through references to deleted IDs and per-type routing, and it hints at row-count limits ('최대5행', '최대 20행'), but it never explains that 'n' is the requested row count or what its default of 5 governs relative to those caps. Partial compensation only.

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 pairs a specific verb ('실제 첫 행 보기 / Preview') with a specific resource (first rows of datagokr datasets) and immediately scopes it by source type (STD_FILE, PORTAL_FILE, OPEN_API, LINK, STD child rows). That is enough to separate it from siblings like search, record, or download_url, though none of those siblings are named explicitly as alternatives.

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 conditional routing rules: OPEN_API datasets return request_templates, LINK types return url, STD child rows need parent_id, and a failed PORTAL_FILE attachment preview may fall back to an API call requiring the caller's own key. It also says what to do on ok=false (retry later) and on deleted IDs (deleted plus alternatives). What is missing is an explicit statement of when to prefer a sibling tool over this one.

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