hackathon-scope-cutter

Goal

Reduce a project's feature set to the minimum viable product (MVP) that can be shipped within the hackathon time limit while preserving demo impact.

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Trigger Conditions

Use this skill when:

• A top idea has been selected and confirmed by hackathon-idea-scoring
• A feature wishlist exists and must be reduced to a shippable set
• The hackathon duration and team size are known
• The team is at risk of building too much and shipping nothing
• Invoked once per project, immediately after idea selection; output is an upstream dependency for planning, implementation, and presentation skills

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Inputs

Input	Type	Required	Description
project_title	string	Yes	Name of the selected project
feature_wishlist	string[]	Yes	Full desired feature list
core_mechanism	string	Yes	The single mechanism the project must demonstrate
hackathon_duration_hours	integer	Yes	Total hours available
team_size	integer	Yes	Number of team members
team_skills	string[]	Yes	Technologies the team can use effectively
wow_factor	string	Yes	What must land for judges to be impressed

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Outputs

Output	Description
mvp_features	Features included in the MVP
deferred_features	Features cut from MVP (post-hackathon backlog)
cut_rationale	Why each deferred feature was cut
mvp_demo_flow	Minimal user journey that demonstrates core value
time_budget	Rough hour estimate per MVP feature
scope_risk	Remaining risks even after scoping
recommended_skills	Suggested next skills to invoke

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Rules

1. Include a feature in MVP only if it is required to demonstrate core_mechanism or wow_factor.
2. Default to cutting any feature that cannot be implemented in less than 20% of total time.
3. Preserve at least one visually compelling UI moment in mvp_demo_flow.
4. Total time_budget must not exceed 70% of hackathon_duration_hours (reserve 30% for polish and presentation).
5. Mark features as [FAKE-OK] if they can be simulated or hardcoded for demo purposes.
6. Do not cut the feature that delivers wow_factor.

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Output Format

mvp_features:
  - feature: "<name>"
    purpose: "<why it's essential>"
    fake_ok: <true|false>

deferred_features:
  - feature: "<name>"
    cut_rationale: "<reason>"

mvp_demo_flow:
  - step: <number>
    action: "<user action>"
    outcome: "<visible result>"

time_budget:
  - feature: "<name>"
    estimated_hours: <number>

scope_risk:
  - "<risk>"

recommended_skills:
  - "<skill-name>"

---

Example

Input:

project_title: "AnchorAI"
feature_wishlist:
  - "User authentication and profiles"
  - "GPT-4 emotional check-in conversation"
  - "Session memory (recall past conversations)"
  - "Mood trend dashboard"
  - "Push notifications for daily check-ins"
  - "Crisis escalation to hotline resources"
  - "Onboarding quiz to personalize tone"
core_mechanism: "GPT-4 conversation with persistent emotional context memory"
hackathon_duration_hours: 24
team_size: 3
team_skills: ["Python", "React", "OpenAI API"]
wow_factor: "AI recalls emotional context from past sessions and adapts tone in real time"

Output:

mvp_features:
  - feature: "GPT-4 emotional check-in conversation"
    purpose: "Core mechanism — must ship"
    fake_ok: false
  - feature: "Session memory (recall past conversations)"
    purpose: "Delivers the wow factor"
    fake_ok: false
  - feature: "Crisis escalation to hotline resources"
    purpose: "Safety requirement visible to judges"
    fake_ok: true

deferred_features:
  - feature: "User authentication and profiles"
    cut_rationale: "3–4h cost; demo uses single hardcoded session"
  - feature: "Mood trend dashboard"
    cut_rationale: "Not in demo flow; 4h cost"
  - feature: "Push notifications"
    cut_rationale: "Backend complexity; irrelevant to live demo"
  - feature: "Onboarding quiz"
    cut_rationale: "Can be mocked with pre-set tone for demo"

mvp_demo_flow:
  - step: 1
    action: "User opens app and types: 'I'm feeling really overwhelmed today'"
    outcome: "AI responds empathetically with personalized opening"
  - step: 2
    action: "User describes a recurring work stress"
    outcome: "AI references last week's similar conversation from memory"
  - step: 3
    action: "User expresses hopelessness"
    outcome: "AI surfaces crisis resource card gracefully"

time_budget:
  - feature: "GPT-4 check-in conversation"
    estimated_hours: 4
  - feature: "Session memory"
    estimated_hours: 5
  - feature: "Crisis escalation (mocked)"
    estimated_hours: 1

scope_risk:
  - "Memory retrieval latency may degrade demo experience on slow networks"

recommended_skills:
  - "hackathon-task-planner"
  - "hackathon-wow-detector"

---

Context Files

Knowledge Base

• knowledge/hackathon-mvp-strategy.md
• knowledge/hackathon-common-failures.md
• knowledge/hackathon-winning-patterns.md
• knowledge/hackathon-demo-patterns.md

Playbooks

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