fetch_problem_content_boj

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

With no annotations provided, the description carries the full burden. It discloses important behaviors: scraping target URL, 10-second timeout, up to 2 retries, 30-day cache, and the fact that hints are excluded. It also reveals the response structure. While it doesn't explicitly state read-only semantics or auth requirements, the disclosed operational details are substantial and go well beyond minimal expectations.

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 with clear sections (purpose, response structure, usage scenarios, limitations, platform warning). While it is relatively lengthy, every section adds practical information. It is not redundant or bloated, though the phrase '힌트 제외' appears both in the opening and in the hint warning, which is a minor duplication.

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 no output schema and no annotations, the description compensates well by listing the response fields and constraints. It covers usage context, technical limits, and platform ambiguity. It does not detail possible failure modes or error handling, but for a scraping tool of moderate complexity, the provided information is sufficient for an agent to invoke it correctly.

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 input schema already documents problem_id with type and description, giving 100% coverage. The description adds valuable context beyond the schema: the exact URL pattern (https://www.acmicpc.net/problem/{problem_id}) and the platform-disambiguation logic, which helps clarify how the parameter value should be interpreted and used.

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 a specific verb and resource: it scrapes the BOJ problem statement (title, description, I/O format, examples, limits) and explicitly excludes hints. It distinguishes itself from the hint-generation sibling by directing users to generate_hint_boj when hints are needed.

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 '사용 시나리오' section explicitly lists when to use the tool (before solving, during review, for code analysis). It also provides a critical platform-disambiguation warning, instructing the agent to confirm whether the platform is BOJ or Programmers when only a problem number is given. This is clear, actionable guidance.

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