hackathon-deployment-prep

hackathon-deployment-prep

目标

在评审开始前，确保项目已可靠部署并做好演示准备：生成部署检查清单、验证演示环境、加载测试数据，并为每种关键故障场景制定备用方案。

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触发条件

在以下情况下使用此技能：

• 实现已完成，演示流程可端到端运行
• 项目首次部署到云平台（Vercel、Render、Railway 等）
• 团队需要在评审前验证演示环境
• 排练发现演示流程不稳定
• 在第 8 阶段（交付）调用，此时已完成 hackathon-test-generator，尚未开始 hackathon-submission-prep；每次部署变更后重新调用

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输入

输入	类型	必填	说明
project_title	string	是	项目名称
mvp_demo_flow	object[]	是	来自 hackathon-scope-cutter 的演示步骤
tech_stack	string[]	是	使用的技术
deployment_targets	object[]	是	前端和后端平台详情
demo_blockers	object[]	否	来自 hackathon-test-generator 的已知故障场景
demo_environment	string	否	演示运行环境（例如浏览器、移动设备、CLI、Vercel）
judging_format	string	否	live_demo、video_only 或 both（默认值：both）
deadline_hours_remaining	number	否	距提交截止时间的剩余小时数

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输出

输出	说明
deployment_checklist	按顺序排列的部署验证步骤，含通过/失败标准
demo_environment_plan	稳定演示所需的完整环境配置
demo_data_setup	从干净状态开始运行演示流程所需的测试数据和状态
fallback_plan	针对每种关键故障场景的分级备用策略
go_no_go_criteria	团队开始展示前必须全部满足的条件
recommended_skills	建议接下来调用的技能

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规则

1. deployment_checklist 必须能在全新机器或云 Shell 中按顺序执行。
2. mvp_demo_flow 中的每一项都必须有对应的 demo_data_setup 条目。
3. demo_blockers 中的每一项都必须有对应的 fallback_plan 条目。
4. go_no_go_criteria 必须是二元通过/失败标准，不得包含部分通过状态。
5. 如果 judging_format 包含 live_demo，则必须提供屏幕录制备用方案。
6. 将任何需要超过 15 分钟的部署步骤标记为 [TIME-RISK]。
7. demo_environment_plan 必须指定确切的浏览器、缩放级别、窗口布局和测试账户状态。

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输出格式

deployment_checklist:
  - id: "DC-<number>"
    step: "<what to do>"
    platform: "<Vercel|Render|Railway|local|all>"
    pass_condition: "<what success looks like>"
    time_risk: <true|false>
    estimated_minutes: <number>

demo_environment_plan:
  browser: "<browser name and version>"
  zoom_level: "<percentage>"
  window_layout: "<description of screen layout>"
  demo_account: "<account/user state>"
  pre_loaded_data: "<what must exist before demo starts>"
  notifications: "disabled"
  additional_notes:
    - "<note>"

demo_data_setup:
  - demo_flow_step: <number>
    required_state: "<what must be true in the system>"
    setup_command: "<command or action to create this state>"

fallback_plan:
  - scenario: "<failure scenario>"
    trigger: "<when to invoke this fallback>"
    action: "<what to do>"
    asset_required: "<pre-recorded video|static slide|mock data|none>"

go_no_go_criteria:
  - criterion: "<condition>"
    status: "<PASS|FAIL|NOT_CHECKED>"

recommended_skills:
  - "<skill-name>"

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示例

输入：

project_title: "AnchorAI"
mvp_demo_flow:
  - step: 1
    action: "User types 'I'm feeling overwhelmed today'"
    outcome: "AI responds empathetically"
  - step: 2
    action: "User describes recurring work stress"
    outcome: "AI references last week's conversation from memory"
  - step: 3
    action: "User expresses hopelessness"
    outcome: "Crisis resource card appears"
tech_stack: ["Next.js", "FastAPI", "Supabase", "Groq"]
deployment_targets:
  - role: "frontend"
    platform: "Vercel"
    url: "https://anchorai.vercel.app"
  - role: "backend"
    platform: "Render"
    url: "https://anchorai-api.onrender.com"
demo_blockers:
  - scenario: "Groq API rate limit hit during demo"
    mitigation: "Pre-recorded screen capture"
  - scenario: "Render cold start delays response by 30s"
    mitigation: "Warm-up ping at start"
judging_format: "both"
deadline_hours_remaining: 3

输出：

deployment_checklist:
  - id: "DC-01"
    step: "Verify Render backend is deployed and /health endpoint returns HTTP 200"
    platform: "Render"
    pass_condition: "curl https://anchorai-api.onrender.com/health returns {\"status\": \"ok\"}"
    time_risk: false
    estimated_minutes: 2
  - id: "DC-02"
    step: "Verify Vercel frontend is deployed and loads without console errors"
    platform: "Vercel"
    pass_condition: "https://anchorai.vercel.app loads; browser console has zero errors"
    time_risk: false
    estimated_minutes: 3
  - id: "DC-03"
    step: "Warm up Render instance by sending 3 chat requests and verifying sub-3s response time"
    platform: "Render"
    pass_condition: "All 3 responses received in under 3 seconds"
    time_risk: false
    estimated_minutes: 5
  - id: "DC-04"
    step: "Load demo session history into Supabase for user_id='demo' containing 'exam stress' phrase"
    platform: "all"
    pass_condition: "GET /memory?user_id=demo returns non-empty summary containing 'exam stress'"
    time_risk: false
    estimated_minutes: 5
  - id: "DC-05"
    step: "Run full demo flow end-to-end 3 times from a clean session state"
    platform: "all"
    pass_condition: "All 3 runs complete without error; wow moment (memory recall) triggers consistently"
    time_risk: true
    estimated_minutes: 20

demo_environment_plan:
  browser: "Chrome (latest stable)"
  zoom_level: "125%"
  window_layout: "Full-screen browser, chat interface centred, no other tabs visible"
  demo_account: "user_id='demo'; 1 prior session loaded in Supabase with 'exam stress' content"
  pre_loaded_data: "Supabase 'sessions' table contains row for user_id='demo' with summary field populated"
  notifications: "disabled"
  additional_notes:
    - "Disable OS notifications in System Settings before demo"
    - "Close all other applications; only browser open"
    - "Have pre-recorded fallback video open in a minimized tab"

demo_data_setup:
  - demo_flow_step: 1
    required_state: "Empty chat interface; user_id='demo' session loaded in Supabase"
    setup_command: "python scripts/seed_demo.py --user demo --summary 'User was anxious about exam stress last week'"
  - demo_flow_step: 2
    required_state: "Prior session summary accessible via /memory endpoint"
    setup_command: "curl https://anchorai-api.onrender.com/memory?user_id=demo — verify response contains 'exam stress'"
  - demo_flow_step: 3
    required_state: "Crisis keyword detection active (no config change needed)"
    setup_command: "No setup required; crisis card is triggered by keyword matching in chat router"

fallback_plan:
  - scenario: "Groq API rate limit hit during demo"
    trigger: "Chat response takes >5 seconds or returns error"
    action: "Switch to pre-recorded screen capture tab; narrate over the video"
    asset_required: "pre-recorded video"
  - scenario: "Render cold start delays response by 30s"
    trigger: "First chat request takes >10 seconds"
    action: "Say 'Let me load the warm session' — switch to pre-warmed local fallback or cached response"
    asset_required: "mock data"
  - scenario: "Supabase unavailable; memory not retrieved"
    trigger: "AI response does not reference prior session context"
    action: "Acknowledge gracefully: 'Memory is loading from the database' — continue with mocked recall line"
    asset_required: "none"

go_no_go_criteria:
  - criterion: "Backend /health returns HTTP 200"
    status: "NOT_CHECKED"
  - criterion: "Frontend loads without console errors"
    status: "NOT_CHECKED"
  - criterion: "Demo session data loaded in Supabase"
    status: "NOT_CHECKED"
  - criterion: "Memory recall (wow moment) triggers in 3 of 3 test runs"
    status: "NOT_CHECKED"
  - criterion: "Crisis card appears on hopelessness message"
    status: "NOT_CHECKED"
  - criterion: "Pre-recorded fallback video is accessible in minimised tab"
    status: "NOT_CHECKED"
  - criterion: "Groq API key active and rate limit verified"
    status: "NOT_CHECKED"

recommended_skills:
  - "hackathon-submission-prep"

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上下文文件

知识库

• ../hackathon-shared-resources/knowledge/hackathon-demo-patterns.md
• ../hackathon-shared-resources/knowledge/hackathon-common-failures.md
• ../hackathon-shared-resources/knowledge/hackathon-submission-guidelines.md
• ../hackathon-shared-resources/knowledge/hackathon-demo-psychology.md

模板

• ../hackathon-shared-resources/templates/demo-script-template.md

操作手册

• ../hackathon-shared-resources/playbooks/hackathon-workflow.md
• ../hackathon-shared-resources/playbooks/24h-hackathon-playbook.md
• ../hackathon-shared-resources/playbooks/36h-hackathon-playbook.md
• ../hackathon-shared-resources/playbooks/48h-hackathon-playbook.md