Skip to main content
Glama

generate_hint_boj

Generate step-by-step hints for Baekjoon problems. Adjusts hint depth based on user progress: problem analysis, core idea, or detailed solution.

Instructions

백준(BOJ) 문제 힌트 생성. 3단계 가이드 프롬프트 제공.

🎯 핵심: 한 번에 1개 레벨 힌트만 제공. 1,2,3 단계를 동시에 제시하지 마세요.

📋 응답에 포함된 정보:

  • hint_levels[0]: Level 1 - 문제 분석 (처음 시도)

  • hint_levels[1]: Level 2 - 핵심 아이디어 (부분 구현)

  • hint_levels[2]: Level 3 - 상세 풀이 (거의 완성)

🤖 사용자 상황 판단 → 적절한 1개 레벨만 제시:

1️⃣ Level 1 제시 (처음/막힐 때): "사용자가 코드 없거나 어디서부터 시작해야 할지 모를 때" → hint_levels[0].prompt로 문제 접근법 제시

2️⃣ Level 2 제시 (다시 요청하거나 부분 구현 언급): "사용자가 '더 필요해', '더 자세히' 요청하거나, 이미 코드를 시작했다고 언급" → hint_levels[1].prompt로 핵심 로직 제시

3️⃣ Level 3 제시 (상세 풀이 명시 요청): "사용자가 '정답', '풀이', '코드' 등 최종 답변 요청" → hint_levels[2].prompt로 상세 구현 가이드 제시

📖 [권장] 어려운 문제는 본문 먼저 확인:

  • 난이도 높은 문제(Gold 이상, level ≥ 11)는 메타데이터만으로 부족할 수 있음

  • fetch_problem_content로 실제 문제 본문 확인 후 힌트 생성 권장

  • 문제 본문을 보면 더 정확하고 맞춤형 힌트 제공 가능

  • 예: mcp-cli call algokit/fetch_problem_content '{"problem_id": 1234}'

  • 본문 확인은 권장사항이며 필수는 아님

정답 정책: 힌트만 기본 제공. 사용자가 "정답", "풀이", "코드" 명시 요청 시만 전체 풀이 제공.

⚠️ 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_idYes백준 문제 번호
Behavior5/5

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

No annotations were provided, so the description carries full responsibility. It discloses key behavioral rules: only one hint level is provided at a time, the response structure contains hint_levels[0-2], and the answer policy (full solution only when explicitly requested). These details help the agent anticipate interactions.

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 well-structured with headings, emojis, and numbered lists, making it scannable despite length. Each section adds value, though some repetition occurs in usage versus policy sections. Still, every sentence earns its place.

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?

Given the tool's complexity (multi-level hint selection, platform ambiguity, answer policy), the description is exceptionally complete. It covers all operational aspects, references a complementary tool for hard problems, and offers clear decision rules for the agent.

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 fully describes problem_id (100% coverage), so baseline is 3. The description adds useful context about platform disambiguation and that the hint depends on problem_id, enhancing the schema but not contradicting it.

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

Purpose5/5

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

The description clearly states the tool generates Baekjoon (BOJ) problem hints using a 3-stage guide prompt. It distinguishes this tool from siblings like get_problem_boj and fetch_problem_content_boj by focusing on hint generation rather than retrieval or analysis.

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

Usage Guidelines5/5

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

Provides explicit when-to-use conditions for each hint level based on user context, recommends fetch_problem_content for difficult problems, and instructs to verify platform ambiguity when only problem_id is given. This goes beyond simple guidance by including exclusions and alternatives.

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

Install Server

Other Tools

Latest Blog Posts

MCP directory API

We provide all the information about MCP servers via our MCP API.

curl -X GET 'https://glama.ai/api/mcp/v1/servers/itsme-shawn/algoKit-mcp'

If you have feedback or need assistance with the MCP directory API, please join our Discord server