hackathon-judge-simulator
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Chinesehackathon-judge-simulator
黑客松评委模拟器
Goal
目标
Simulate a panel of hackathon judges evaluating a project, generating likely questions, critical objections, and a predicted scoring outcome so the team can strengthen their pitch and demo.
模拟黑客松评委团对项目进行评估,生成可能的问题、关键异议和预测评分结果,帮助团队优化路演和演示内容。
Trigger Conditions
触发条件
Use this skill when:
- The pitch deck is drafted and the demo is recorded
- The team needs to stress-test the pitch before live judging
- Adversarial questions and rebuttal strategies must be prepared
- Predicted scores reveal gaps that can be addressed before presentation
- Invoked during Phase 7 (Evaluation); re-invoke after pitch improvements are made for a second simulation pass
在以下场景使用该技能:
- 项目路演PPT已完成初稿,演示内容已录制
- 团队需要在正式评审前对路演进行压力测试
- 需准备针对性问题及反驳策略
- 预测分数可揭示路演中需改进的漏洞
- 在第7阶段(评估阶段)调用;路演优化完成后可再次调用进行第二轮模拟
Inputs
输入项
| Input | Type | Required | Description |
|---|---|---|---|
| string | Yes | Name of the project |
| string | Yes | The problem being solved |
| string | Yes | How the project solves it |
| string[] | Yes | What was built |
| string[] | Yes | Technologies used |
| object[] | Yes | Judging criteria from |
| string | No | Draft pitch or slide content for more targeted simulation |
| string[] | No | Types of judges expected (e.g., technical, business, domain expert) |
| 输入项 | 类型 | 是否必填 | 描述 |
|---|---|---|---|
| string | 是 | 项目名称 |
| string | 是 | 项目解决的问题 |
| string | 是 | 项目解决方案概述 |
| string[] | 是 | 已完成的MVP功能 |
| string[] | 是 | 使用的技术栈 |
| object[] | 是 | 来自 |
| string | 否 | 路演初稿或幻灯片内容,用于更精准的模拟 |
| string[] | 否 | 预期的评委类型(如技术型、商业型、领域专家型) |
Outputs
输出项
| Output | Description |
|---|---|
| Simulated judge types with their likely priorities |
| Expected judge questions with recommended answers |
| Critical concerns judges are likely to raise |
| Score per evaluation axis with reasoning |
| Simulated overall impression and ranking likelihood |
| Specific changes to address predicted weaknesses |
| 输出项 | 描述 |
|---|---|
| 模拟的评委类型及其优先级 |
| 预期的评委问题及推荐回答 |
| 评委可能提出的关键顾虑 |
| 各评审维度的得分及理由 |
| 模拟的整体评价及排名可能性 |
| 针对预测短板的具体改进建议 |
Rules
规则
- Simulate at least 3 distinct judge personas if is not provided.
judge_personas - Generate at least 2 questions per evaluation axis.
- Include at least one question that targets a weakness in the solution.
- must use the same 1–5 scale as
predicted_scores.hackathon-idea-scoring - must be paired with a recommended rebuttal strategy.
objections - must be actionable within the remaining hackathon time.
pitch_improvements - Do not simulate only favorable outcomes; include at least one skeptical judge perspective.
- 若未提供,至少模拟3种不同的评委角色
judge_personas - 每个评审维度至少生成2个问题
- 至少包含1个针对解决方案短板的问题
- 必须使用与
predicted_scores一致的1-5分制hackathon-idea-scoring - 每个需搭配对应的推荐反驳策略
objections - 必须是在剩余黑客松时间内可落地的行动
pitch_improvements - 不能仅模拟正面结果,需包含至少1个持怀疑态度的评委视角
Output Format
输出格式
yaml
judge_personas_used:
- persona: "<type>"
priorities:
- "<priority>"
questions:
- judge_persona: "<type>"
question: "<question text>"
recommended_answer: "<suggested response>"
difficulty: "<easy|medium|hard>"
objections:
- objection: "<concern>"
likelihood: "<high|medium|low>"
rebuttal_strategy: "<how to address>"
predicted_scores:
- axis: "<axis name>"
score: <1-5>
reasoning: "<why>"
overall_verdict:
impression: "<string>"
ranking_likelihood: "<top-3|mid-field|long-shot>"
key_strengths:
- "<strength>"
key_weaknesses:
- "<weakness>"
pitch_improvements:
- issue: "<problem>"
action: "<what to change>"
priority: "<high|medium|low>"yaml
judge_personas_used:
- persona: "<type>"
priorities:
- "<priority>"
questions:
- judge_persona: "<type>"
question: "<question text>"
recommended_answer: "<suggested response>"
difficulty: "<easy|medium|hard>"
objections:
- objection: "<concern>"
likelihood: "<high|medium|low>"
rebuttal_strategy: "<how to address>"
predicted_scores:
- axis: "<axis name>"
score: <1-5>
reasoning: "<why>"
overall_verdict:
impression: "<string>"
ranking_likelihood: "<top-3|mid-field|long-shot>"
key_strengths:
- "<strength>"
key_weaknesses:
- "<weakness>"
pitch_improvements:
- issue: "<problem>"
action: "<what to change>"
priority: "<high|medium|low>"Example
示例
Input:
yaml
project_title: "AnchorAI"
problem_statement: "College students wait 6 weeks for counseling while anxiety compounds."
solution_summary: "GPT-4 companion with Redis-backed session memory for persistent emotional context."
mvp_features: ["GPT-4 check-in conversation", "Session memory", "Crisis escalation (mocked)"]
tech_stack: ["Python", "FastAPI", "React", "Redis", "OpenAI GPT-4"]
evaluation_axes:
- axis: "Innovation"
- axis: "Impact"
- axis: "Technical Execution"Output:
yaml
judge_personas_used:
- persona: "Technical judge"
priorities: ["Working implementation", "Appropriate tech choices", "Scalability awareness"]
- persona: "Impact/domain judge"
priorities: ["Real user need", "Safety guardrails", "Clinical validity concerns"]
- persona: "Business judge"
priorities: ["Market size", "Differentiation", "Go-to-market path"]
questions:
- judge_persona: "Technical judge"
question: "How does the memory actually work — what are you storing and retrieving?"
recommended_answer: "We store a GPT-4 generated summary of each session in Redis, keyed by user ID. On the next session, we prepend that summary to the system prompt. It's simple and it works for the demo."
difficulty: "medium"
- judge_persona: "Impact/domain judge"
question: "Is this safe? What happens if someone is in genuine crisis?"
recommended_answer: "We detect distress signals and surface hotline resources immediately. We're explicit that AnchorAI is not a therapist. In the roadmap, we escalate to human counselors."
difficulty: "hard"
- judge_persona: "Business judge"
question: "How is this different from Woebot or BetterHelp?"
recommended_answer: "Woebot has no memory and uses rigid scripts. BetterHelp is $80/week. AnchorAI is the only free, always-available companion that actually knows your history."
difficulty: "medium"
objections:
- objection: "This could give vulnerable users dangerous advice"
likelihood: "high"
rebuttal_strategy: "Acknowledge directly. Explain the safety guardrails and the explicit non-therapist framing. Offer to show the crisis card in the demo."
- objection: "Memory feature is just system prompt injection — not novel"
likelihood: "medium"
rebuttal_strategy: "Agree it's a simple mechanism. Pivot to impact: the novelty is the UX, not the implementation. Show the user experience, not the code."
predicted_scores:
- axis: "Innovation"
score: 4
reasoning: "Memory-based continuity in mental health context is genuinely novel for a hackathon"
- axis: "Impact"
score: 5
reasoning: "Large, underserved audience with real demonstrated need"
- axis: "Technical Execution"
score: 4
reasoning: "Working live demo with real API integration; Redis memory functions correctly"
overall_verdict:
impression: "Strong emotional narrative with a memorable live demo moment. Safety question will come up — being prepared for it is the difference between winning and not."
ranking_likelihood: "top-3"
key_strengths:
- "Emotionally resonant problem framing"
- "Live working wow moment (memory recall)"
- "Clear differentiation from existing tools"
key_weaknesses:
- "Safety and clinical validity will be scrutinized"
- "Business model not addressed"
pitch_improvements:
- issue: "No mention of how AnchorAI avoids causing harm"
action: "Add one sentence to the solution slide: 'AnchorAI is not a therapist — it's a bridge to one.'"
priority: "high"
- issue: "No business or monetization framing"
action: "Add one bullet to vision slide: 'Free tier for students; licensed model for universities'"
priority: "medium"输入:
yaml
project_title: "AnchorAI"
problem_statement: "College students wait 6 weeks for counseling while anxiety compounds."
solution_summary: "GPT-4 companion with Redis-backed session memory for persistent emotional context."
mvp_features: ["GPT-4 check-in conversation", "Session memory", "Crisis escalation (mocked)"]
tech_stack: ["Python", "FastAPI", "React", "Redis", "OpenAI GPT-4"]
evaluation_axes:
- axis: "Innovation"
- axis: "Impact"
- axis: "Technical Execution"输出:
yaml
judge_personas_used:
- persona: "Technical judge"
priorities: ["Working implementation", "Appropriate tech choices", "Scalability awareness"]
- axis: "Impact/domain judge"
priorities: ["Real user need", "Safety guardrails", "Clinical validity concerns"]
- persona: "Business judge"
priorities: ["Market size", "Differentiation", "Go-to-market path"]
questions:
- judge_persona: "Technical judge"
question: "How does the memory actually work — what are you storing and retrieving?"
recommended_answer: "We store a GPT-4 generated summary of each session in Redis, keyed by user ID. On the next session, we prepend that summary to the system prompt. It's simple and it works for the demo."
difficulty: "medium"
- judge_persona: "Impact/domain judge"
question: "Is this safe? What happens if someone is in genuine crisis?"
recommended_answer: "We detect distress signals and surface hotline resources immediately. We're explicit that AnchorAI is not a therapist. In the roadmap, we escalate to human counselors."
difficulty: "hard"
- judge_persona: "Business judge"
question: "How is this different from Woebot or BetterHelp?"
recommended_answer: "Woebot has no memory and uses rigid scripts. BetterHelp is $80/week. AnchorAI is the only free, always-available companion that actually knows your history."
difficulty: "medium"
objections:
- objection: "This could give vulnerable users dangerous advice"
likelihood: "high"
rebuttal_strategy: "Acknowledge directly. Explain the safety guardrails and the explicit non-therapist framing. Offer to show the crisis card in the demo."
- objection: "Memory feature is just system prompt injection — not novel"
likelihood: "medium"
rebuttal_strategy: "Agree it's a simple mechanism. Pivot to impact: the novelty is the UX, not the implementation. Show the user experience, not the code."
predicted_scores:
- axis: "Innovation"
score: 4
reasoning: "Memory-based continuity in mental health context is genuinely novel for a hackathon"
- axis: "Impact"
score: 5
reasoning: "Large, underserved audience with real demonstrated need"
- axis: "Technical Execution"
score: 4
reasoning: "Working live demo with real API integration; Redis memory functions correctly"
overall_verdict:
impression: "Strong emotional narrative with a memorable live demo moment. Safety question will come up — being prepared for it is the difference between winning and not."
ranking_likelihood: "top-3"
key_strengths:
- "Emotionally resonant problem framing"
- "Live working wow moment (memory recall)"
- "Clear differentiation from existing tools"
key_weaknesses:
- "Safety and clinical validity will be scrutinized"
- "Business model not addressed"
pitch_improvements:
- issue: "No mention of how AnchorAI avoids causing harm"
action: "Add one sentence to the solution slide: 'AnchorAI is not a therapist — it's a bridge to one.'"
priority: "high"
- issue: "No business or monetization framing"
action: "Add one bullet to vision slide: 'Free tier for students; licensed model for universities'"
priority: "medium"Context Files
上下文文件
Knowledge Base
知识库
knowledge/hackathon-judging-criteria.mdknowledge/hackathon-pitch-strategy.mdknowledge/hackathon-winning-patterns.mdknowledge/hackathon-demo-psychology.md
knowledge/hackathon-judging-criteria.mdknowledge/hackathon-pitch-strategy.mdknowledge/hackathon-winning-patterns.mdknowledge/hackathon-demo-psychology.md
Playbooks
操作手册
playbooks/hackathon-workflow.md
playbooks/hackathon-workflow.md