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get_problem_programmers

Fetch Programmers problem details including title, description, constraints, and examples to prepare for solving, review, or code analysis.

Instructions

프로그래머스 문제 상세 정보 조회 (웹 스크래핑).

프로그래머스 페이지에서 문제 제목, 설명, 제한사항, 입출력 예제를 가져옵니다.

응답 구조: problemId, title, level, category, description, constraints, examples, tags

사용 시나리오:

  • 프로그래머스 문제 풀이 전 문제 본문 확인

  • 문제 복습 시 문제 내용 참조

  • 코드 분석 시 문제 요구사항 비교

제한사항:

참고:

  • BOJ와 다르게 프로그래머스는 fetch + cheerio 사용 (SSR 페이지)

  • 프로그래머스는 태그 정보가 없으므로 tags 필드는 빈 배열

⚠️ 플랫폼 판별: 문제 번호만 입력된 경우 대화 맥락에서 플랫폼을 파악하거나, 맥락이 없으면 반드시 BOJ/프로그래머스 중 어느 플랫폼인지 사용자에게 확인 후 호출하세요.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
problem_idYes문제 ID 또는 프로그래머스 URL. 예: 42748 또는 https://school.programmers.co.kr/learn/courses/30/lessons/42748
Behavior5/5

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

With no annotations, the description fully discloses operational behavior: web scraping via fetch + cheerio, target URL, 10-second timeout, max 2 retries, 1 request/second rate limit, and that tags field is empty for Programmers. This goes well beyond a simple getter and gives the agent critical expectations.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is relatively long but well-organized with labeled sections (usage scenarios, limitations, notes). Every section contributes necessary operational detail for a scraping tool, although it could be tightened slightly without losing value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

Despite no output schema, the description lists the full response structure (problemId, title, level, category, description, constraints, examples, tags). It also covers rate limiting, retries, timeout, platform-specific behavior, and the platform disambiguation requirement, making it complete for an agent to invoke correctly.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters4/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

The schema already covers the single problem_id parameter with examples and 100% coverage. The description adds valuable disambiguation guidance: when only a problem number is given, the agent must determine the platform from context or ask the user. This extra semantic helps correct invocation.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's function: '프로그래머스 문제 상세 정보 조회 (웹 스크래핑)' and lists the returned fields (problemId, title, level, etc.), distinguishing it from BOJ tools. However, it does not explicitly differentiate from the sibling fetch_problem_content_programmers, which may overlap.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

Provides explicit usage scenarios (before solving, during review, code analysis) and clear guidance for platform disambiguation when only a problem number is given. It does not, however, list when not to use this tool or mention alternative siblings such as fetch_problem_content_programmers.

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

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