hackathon-deployment-prep（黑客马拉松部署准备）

hackathon-deployment-prep

Goal

Ensure the project is reliably deployed and demo-ready before judging begins, by generating a deployment checklist, validating the demo environment, loading test data, and defining a fallback plan for every critical failure scenario.

Trigger Conditions

Use this skill when:

• Implementation is complete and the demo path runs end-to-end
• The project is being deployed to a cloud platform (Vercel, Render, Railway, etc.) for the first time
• The team needs to validate the demo environment before judging
• A rehearsal has revealed instability in the demo path
• Invoked during Phase 8 (Delivery), after hackathon-test-generator and before hackathon-submission-prep; re-invoke after any deployment change

Inputs

Outputs

Rules

1. deployment_checklist must be executable in order from a fresh machine or cloud shell.
2. Every item in mvp_demo_flow must have a corresponding demo_data_setup entry.
3. Every item in demo_blockers must have a corresponding fallback_plan entry.
4. go_no_go_criteria must be binary pass/fail — no partial states.
5. If judging_format includes live_demo, a screen recording fallback is mandatory.
6. Flag any deployment step that requires >15 minutes as [TIME-RISK].
7. demo_environment_plan must specify exact browser, zoom level, window layout, and test account state.

Output Format

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>"

Example

Input:

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

Output:

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"

Context Files

Knowledge Base

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

Templates

• templates/demo-script-template.md

Playbooks

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