testcase

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

No annotations are provided, so the description carries the full burden. It usefully discloses output behavior (3-5 cases, edge cases included, beyond the default examples), but says nothing about determinism, latency, whether results are cached, or how failures (invalid problem ID, no problem found) are surfaced.

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?

A single front-loaded sentence with no filler and the key scope (3-5 edge-case test cases) clearly placed. Efficient, though it lacks the extra routing sentence that would make it maximally useful.

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 simple one-parameter tool this is nearly adequate, but with no output schema the description should say something about the returned format (e.g., input/output pairs, JSON structure) and whether output varies. It covers quantity but not shape.

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 100% and the single problemId parameter accepts string or integer, so the schema already documents it. The description only restates '백준 문제 ID를 받아', adding no format or range detail beyond the schema; baseline 3 for high coverage.

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?

States a specific verb (생성합니다) and resource (추가 테스트 케이스) and specifies scope: 3-5 cases including edge cases beyond the basic examples. It is easy to distinguish from siblings (hint, answer, refactor), though it never names them, so it stops short of explicit sibling differentiation.

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?

Usage is implied by the tool name and purpose (use it when you want extra test data for a solved/attempted problem), but there is no explicit when-to-use, when-not-to-use, or alternative routing to hint/answer/refactor. Minimum viable guidance only.

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