Stop building "another todo app." Find a blue ocean topic before you write a single line of code.
A cross-platform AI Skill that validates your hackathon project idea through multi-round dialogue, multi-channel search, social demand discovery, and three-dimensional scoring. Works with TRAE, Claude Code, Cursor, Windsurf, and any tool that reads Markdown.
66% of hackathon projects are "reskins" — todo apps, weather dashboards, GPT wrappers. They don't win. The #1 factor that determines hackathon success is topic selection, not code quality. This skill helps you pick a topic that is:
- Rare — not already built by 500 other teams
- Original — not a reskin of a common pattern
- Meaningful — solves a real problem with real users
User describes idea
│
▼
┌──────────────┐
│ 1. Clarify │ AI asks 2-3 sharp questions
│ (反问) │ Who's the user? What's the core scenario?
└──────┬───────┘
▼
┌──────────────┐
│ 2. Search │ GitHub · Devpost · Product Hunt
│ (同类搜索) │ How many similar projects exist?
└──────┬───────┘
▼
┌──────────────┐
│ 3. Discover │ Reddit · Twitter · V2EX · Zhihu
│ (社媒需求) │ "I wish there was a tool that..."
└──────┬───────┘
▼
┌──────────────┐
│ 4. Score │ Python script → deterministic score
│ (三维评分) │ Scarcity + Originality + Meaning
└──────┬───────┘
▼
┌──────────────┐
│ 5. Report │ 🌊 Blue / ⚡ Yellow / 🔥 Red
│ (分析报告) │ + differentiation strategies
└──────┬───────┘
▼
┌──────────────┐
│ 6. Iterate │ Adjust idea → re-analyze
│ (迭代优化) │ until you find a winner
└──────────────┘
Composite = Scarcity × 40% + Originality × 35% + Meaning × 25%
| Score | Ocean Type | What It Means |
|---|---|---|
| ≥ 70 | 🌊 Blue Ocean | Scarce, original, high social value — go build it! |
| 45–69 | ⚡ Yellow Ocean | Some competition, but you can differentiate |
| < 45 | 🔥 Red Ocean | Saturated. Pivot or find a unique angle. |
| Dimension | Weight | How It's Calculated |
|---|---|---|
| Scarcity | 40% | GitHub + Devpost search result count and hit ratio. 0 results = 95 pts; 5000+ results = 10 pts. |
| Originality | 35% | Base 70. Subtract penalty for matched common patterns (25 patterns in library). Add bonus for originality boosters (accessibility, AI agent, AR, etc.). |
| Meaning | 25% | Base 50. Add bonus for social impact boosters (elderly, disaster relief, rural, etc.). New: social demand modifier from Reddit/Twitter quotes (+10 / -10). |
TRAE (project-level):
cp -r hackathon-topic-advisor/ .trae/skills/Claude Code (project-level):
cp -r hackathon-topic-advisor/ .claude/skills/Cursor / Windsurf / others: see install/other-tools.md
Just talk naturally — the skill auto-activates when you mention hackathons:
You: "我想参加黑客松，想做一个帮老年人管理用药的App"
AI: "这个方向有意思。在搜索之前我想确认几点：1. 你的目标用户是独居老人还是养老院？2. 核心功能是提醒吃药还是药物相互作用检测？..."
Or explicitly invoke: /hackathon-topic-advisor
# 🏆 选题分析报告
## 📊 三维评分
| 维度 | 得分 | 说明 |
|------|------|------|
| 原创性 | 82/100 | 匹配 accessibility + deaf 加分 |
| 稀缺度 | 89/100 | GitHub 仅5个同类仓库 |
| 意义感 | 76/100 | 社媒强需求 +10 |
| **综合** | **83/100** | |
## 🌊 海域判定
🌊 蓝海项目！这个方向稀缺度高，社会价值显著，有很大机会脱颖而出。
## 💬 社媒需求发现
- 需求强度: Strong
- 用户原话摘录:
> "I wish there was a real-time sign language translator..." — Reddit user
> "要是有一个能把手语翻译成文字的工具就好了" — V2EX 用户hackathon-topic-advisor/
├── SKILL.md # Core methodology (6-phase workflow)
├── references/
│ ├── concept-map.md # 110 CN→EN keyword mappings
│ ├── common-patterns.md # 25 common "reskin" patterns + differentiation strategies
│ ├── blue-ocean.md # 8 blue ocean directions + 18 originality boosters
│ └── scoring-rules.md # Scoring algorithm with worked examples
├── scripts/
│ └── topic_scorer.py # Pure Python scorer (stdlib only, no pip install)
├── tests/
│ └── test_topic_scorer.py # 9 unit tests (all passing)
├── install/
│ ├── trae.md # TRAE setup
│ ├── claude-code.md # Claude Code setup
│ └── other-tools.md # Cursor / Windsurf / AGENTS.md
└── README.md # You are here
| Asset | Count | Source |
|---|---|---|
| CN→EN concept mappings | 110 | From HackCheck's conceptMap |
| Common project patterns | 25 | From HackCheck's commonPatterns |
| Blue ocean directions | 8 | From HackCheck's blueOceanDirections |
| Originality boosters | 18 | From HackCheck's originalityBoosters |
echo '{"description":"AI sign language glove","search_total_count":5,"search_hit_ratio":0.2,"matched_patterns":[],"matched_boosters":["accessibility","deaf"],"social_demand_level":"strong"}' | python scripts/topic_scorer.pyOutput:
{
"originality": 82,
"scarcity": 89,
"meaning": 76,
"composite": 83,
"ocean_type": "blue",
"verdict": "蓝海项目！这个方向稀缺度高，社会价值显著，有很大机会脱颖而出。"
}| Platform | Status | How It Works |
|---|---|---|
| TRAE | ✅ Native | Reads .trae/skills/ — uses name + description fields |
| Claude Code | ✅ Native | Reads .claude/skills/ — uses full frontmatter (triggers, tags, allowed-tools) |
| Cursor | ✅ Adapted | Copy SKILL.md body to .cursor/rules/ |
| Windsurf | ✅ Adapted | Copy SKILL.md body to .windsurfrules |
| Any AGENTS.md tool | ✅ Adapted | Reference SKILL.md in AGENTS.md |
The SKILL.md frontmatter includes fields for both TRAE and Claude Code. Each platform reads what it needs and ignores the rest — one file, all platforms.
- Python 3.6+ (only for the scoring script; AI falls back to manual scoring if unavailable)
- Any AI coding tool that supports custom instructions/skills
Derived from HackCheck — a hackathon full-process assistant web app. The topic validation module was extracted, enhanced with social demand discovery and multi-round dialogue, and packaged as a portable skill.
Enhancements over the original web app:
- AI asks clarifying questions before searching (multi-round dialogue)
- Searches social media for real user demand quotes (Reddit, Twitter, V2EX, Zhihu)
- Cross-platform — works in any vibe-coding tool, not just a browser
- Lightweight Python scoring script — deterministic, testable, no dependencies
MIT