mcpField

hackathon-problem-space

github.com/bernieweb3Productivity47 installs
Repository

About hackathon-problem-space

hackathon-problem-space is a skill for mapping a hackathon project’s problem domain before ideation. It helps teams identify user segments, rank pain points, review existing approaches, and frame opportunity gaps.

Key features

  1. 01Identify distinct user segments
  2. 02Rank pain points by severity
  3. 03List existing solutions and limitations
  4. 04Derive gaps and a how-might-we statement
  5. 05Mark inferred market signals

Use cases

  1. 01Narrow a broad hackathon domain
  2. 02Choose target users before ideation
  3. 03Find gaps in current solutions
  4. 04Frame the project problem statement

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/bernieweb3/hackathon-ai-devkit --skill hackathon-problem-space

After installing, type/hackathon-problem-spacein Claude Code to confirm it loaded.

Details

From the project README

hackathon-problem-space

Goal

Map the problem domain for a hackathon project by identifying target users, core pain points, existing solutions, and whitespace opportunities.


Trigger Conditions

Use this skill when:

  • A hackathon track has been analyzed and track_summary is available
  • The team needs to identify who the target user is before generating ideas
  • The problem domain is broad and must be narrowed before ideation
  • Existing solutions must be surveyed to identify gaps worth exploiting
  • Invoked immediately after hackathon-track-analyzer completes

Inputs

InputTypeRequiredDescription
track_summarystringYesOutput from hackathon-track-analyzer or manual description
domainstringYesBroad domain area (e.g., healthcare, fintech, education)
target_user_hintstringNoInitial hypothesis about target user segment
constraintsstring[]NoKnown technical or sponsor constraints

Outputs

OutputDescription
user_segmentsIdentified user groups with brief profiles
pain_pointsRanked list of pain points per user segment
existing_solutionsKnown tools or approaches currently addressing the problem
solution_gapsGaps in existing solutions that represent opportunity
problem_statementOne-sentence problem statement (how-might-we format)
market_signalsEvidence that this problem is real and worth solving
recommended_skillsSuggested next skills to invoke

Rules

  1. Identify at least 2 distinct user segments.
  2. Rank pain points from most to least severe for each segment.
  3. List at least 3 existing solutions with their key limitations.
  4. Derive solution gaps from the delta between pain points and existing solution limitations.
  5. Write the problem statement as: "How might we [action] for [user] so that [outcome]?"
  6. Do not invent market signals; clearly mark inferred signals as [INFERRED].

Output Format

user_segments:
  - segment: "<name>"
    profile: "<brief description>"

pain_points:
  - segment: "<name>"
    pains:
      - severity: "<high|medium|low>"
        description: "<pain>"

existing_solutions:
  - name: "<solution>"
    limitation: "<key gap>"

solution_gaps:
  - "<gap description>"

problem_statement: "<How might we ...>"

market_signals:
  - source: "<real|[INFERRED]>"
    signal: "<description>"

recommended_skills:
  - "<skill-name>"

Example

Input:

track_summary: "Use AI to improve mental health outcomes for young adults."
domain: "mental health / digital health"
target_user_hint: "college students experiencing anxiety"
constraints:
  - "Must use OpenAI GPT-4 API"

Output:

user_segments:
  - segment: "College students"
    profile: "Ages 18–22, high stress, low access to campus counseling"
  - segment: "Young professionals"
    profile: "Ages 23–30, work-related burnout, too busy for scheduled therapy"

pain_points:
  - segment: "College students"
    pains:
      - severity: "high"
        description: "2–6 week wait times for campus counseling appointments"
      - severity: "high"
        description: "Stigma prevents help-seeking behavior"

existing_solutions:
  - name: "Woebot"
    limitation: "Rigid scripted responses; no memory across sessions"
  - name: "BetterHelp"
    limitation: "Expensive ($60–$100/week); not accessible to students"
  - name: "Headspace"
    limitation: "Meditation only; does not address acute anxiety episodes"

solution_gaps:
  - "No affordable, always-available, context-aware emotional support for acute moments"
  - "No peer-community facilitation layer between self-help and professional care"

problem_statement: "How might we provide always-available emotional support for college students so that they can manage anxiety between professional appointments?"

market_signals:
  - source: "real"
    signal: "40% of US college students reported anxiety as top mental health concern (ACHA 2023)"
  - source: "[INFERRED]"
    signal: "Rising demand for async, text-based support given phone anxiety in Gen Z"

recommended_skills:
  - "hackathon-idea-generator"

Context Files

Knowledge Base
  • ../hackathon-shared-resources/knowledge/hackathon-judging-criteria.md
  • ../hackathon-shared-resources/knowledge/hackathon-winning-patterns.md
  • ../hackathon-shared-resources/knowledge/hackathon-mvp-strategy.md
  • ../hackathon-shared-resources/knowledge/hackathon-common-failures.md
Playbooks
  • ../hackathon-shared-resources/playbooks/hackathon-workflow.md

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