Idea Feasibility Analyzer

Turns a raw idea into a structured, machine-readable analysis: enrichment, market research, and a 9-dimension feasibility study, delivered as a single JSON object matching the schema below.

Workflow

Work through these stages in order. Do not skip market research — it is the part that must be grounded in real, current web data, not model knowledge alone.

Stage 0 — Intake

If the user's idea is a single vague sentence, ask at most 3-4 short clarifying questions covering whatever is missing from:

• Target geography/market (affects market size and competitor search)
• Rough budget/team size constraint (affects feasibility scoring)
• Timeline expectation
• Legal/regulatory scope: "Is this a general idea check, or do you need validation for specific country/countries (legal, regulatory, permits, licensing)?" If specific countries are named, Stage 3 performs a deep country-specific legal/regulatory analysis; otherwise a light regulatory scan is sufficient.

If the user has already given enough to proceed (a clear idea + at least an implicit target market), skip straight to Stage 1 rather than blocking on questions — assume reasonable defaults and note the assumption in the output's assumptions field.

Stage 1 — Enrichment

Expand the raw idea into:

• A clear one-paragraph problem statement (what pain point, for whom)
• A one-sentence value proposition
• 2-4 target user segments
• 3-5 differentiators vs. obvious alternatives
• 2-3 plausible variations/pivots on the core idea

This stage is reasoning, not research — no search needed yet.

Stage 2 — Market Research (requires WebFetch / web search)

Run actual web searches — do not rely on memorized figures, which go stale and are often wrong for market sizing. For each idea, search for:

1. Direct competitors / existing products solving the same problem (aim for 3-6 named competitors or close substitutes)
2. Market size figures (TAM/SAM if findable; otherwise the best available industry sizing data, cited by source)
3. Recent trends or news relevant to the space (last 12-18 months)
4. Any notable regulatory/legal considerations for the space and target geography

Never invent a competitor URL — set url: null unless it was actually seen in a search result.

Scale the number of searches to how niche the idea is — a common category (e.g. "meal delivery app") may need 3-4 searches; a novel or cross-industry idea may need 6-10 to properly triangulate. Cite sources by name/URL rather than fabricating numbers. If a figure can't be found, say so explicitly and set it to null.

Stage 3 — Feasibility Study

Using the enrichment + market research, assess all 9 dimensions below.

Original 4 dimensions:

• Technical: what needs to be built, how hard (low/medium/high complexity), key technical risks
• Financial: rough cost bands to build an MVP (ranges, not false precision) and to reach initial traction; note it's a rough estimate, not a budget
• Operational: key dependencies (partnerships, data, licenses, suppliers), business structure, premises, equipment
• Market: how crowded the space is given Stage 2 findings, whether there's a believable wedge

New 5 dimensions (from the QLD Government feasibility framework):

• Product/Service viability: market fit, safety, R&D needs, IP protection strategy, long-term value outlook (5-10 yr), adaptability to tech/industry change
• Customer: usability testing plan, universal design considerations, how pricing affects market size, competitor pricing pressure, maintenance/upgrade needs
• Business model: ownership structure fitness, distribution channels, licensing/export potential, scalability model, long-term operational sustainability
• Team/HR: founder/leader capability, equity partner needs (and how much equity to offer), staff gaps vs contractors, key advisors needed (legal, finance, IP, marketing)
• Legal/Regulatory: scope depends on Stage 0 answer — General (no specific country): light scan of major regulations, common permits/licences, data privacy basics. Country-specific: deep dive per named country — registrations, permits, licences, trade barriers, data privacy laws (e.g. GDPR, CCPA), labour laws, sector-specific regulations. Search each country's requirements separately.

Risks: top 5-7 risks with a one-line mitigation each.

Feasibility scores: score each of the nine dimensions 1-10 (10 = highly feasible), plus an overall score, based on reasoned judgment of the evidence — state briefly why in the rationale field, don't just output numbers.

Scoring anchors:

• 1-3 = significant blockers / strongly not feasible as-is
• 4-6 = feasible with caveats / needs changes
• 7-8 = pursue with changes / modest de-risking needed
• 9-10 = strong pursue, ready to build

Stage 4 — Output

Return only the JSON object below (plus a short 2-3 sentence plain-language summary in chat before or after it — the user is piping the JSON into their own app, so don't wrap it in extra commentary or markdown headers inside the JSON).

After delivering the JSON, optionally run the validation-committee prompt at references/002-idea-validation-committee.md (relative to this skill folder) using the feasibility.risks and scores as input, to pressure-test the riskiest assumptions further.

Output Schema

{
  "idea": {
    "raw_input": "string - the idea as the user stated it",
    "assumptions": ["string - any assumption made to fill gaps"]
  },
  "enrichment": {
    "problem_statement": "string",
    "value_proposition": "string",
    "target_segments": ["string"],
    "differentiators": ["string"],
    "variations": ["string"]
  },
  "market_research": {
    "competitors": [
      {"name": "string", "description": "string", "url": "string or null"}
    ],
    "market_size": {
      "tam_estimate": "string or null - include currency/year/source",
      "sam_estimate": "string or null",
      "notes": "string - caveats, or why unavailable"
    },
    "trends": ["string - each with implicit recency (last 12-18mo)"],
    "regulatory_considerations": ["string"],
    "sources": ["string - names/URLs used"]
  },
  "feasibility": {
    "technical": {"summary": "string", "complexity": "low|medium|high", "key_risks": ["string"]},
    "financial": {"mvp_cost_range": "string", "traction_cost_range": "string", "notes": "string"},
    "operational": {"summary": "string", "business_structure": "string", "premises_needs": "string", "dependencies": ["string"]},
    "market": {"summary": "string", "crowdedness": "low|medium|high", "wedge": "string"},
    "product_viability": {
      "summary": "string",
      "market_fit": "low|medium|high",
      "ip_protection": "string or null - strategy or not applicable",
      "long_term_outlook": "string - 5-10 year viability assessment",
      "adaptability": "string - ability to adapt to tech/industry changes"
    },
    "customer": {
      "summary": "string",
      "usability_testing_plan": "string or null",
      "pricing_analysis": "string - how pricing affects market size",
      "competitor_pricing_pressure": "low|medium|high",
      "maintenance_or_upgrade_needs": "string or null"
    },
    "business_model": {
      "summary": "string",
      "ownership_structure": "string",
      "distribution_channels": ["string"],
      "licensing_export_potential": "string or null",
      "scalability": "string"
    },
    "team_hr": {
      "summary": "string",
      "owner_capability": "string - assessment of founder/leader fit",
      "equity_partner_needs": "string or null",
      "staff_gaps": ["string - roles needed beyond current team"],
      "key_advisors_needed": ["string - e.g. legal, finance, IP, marketing"]
    },
    "legal_regulatory": {
      "scope": "general|country_specific",
      "countries": ["string - empty array if general"],
      "summary": "string",
      "registrations_permits": ["string - what's needed"],
      "data_privacy": "string or null",
      "trade_barriers": "string or null",
      "ip_protection_notes": "string or null"
    },
    "risks": [
      {"risk": "string", "mitigation": "string"}
    ],
    "scores": {
      "technical": 0,
      "financial": 0,
      "operational": 0,
      "market": 0,
      "product_viability": 0,
      "customer": 0,
      "business_model": 0,
      "team_hr": 0,
      "legal_regulatory": 0,
      "overall": 0,
      "rationale": "string - brief justification for the overall score"
    }
  },
  "recommendation": {
    "verdict": "pursue|pursue_with_changes|reconsider|not_recommended",
    "summary": "string - 2-3 sentences"
  }
}

Keep field values concise (arrays of short strings/objects, not paragraphs) — this is meant to be consumed programmatically, not read as prose.

See Also

• Worked example, guiding principles, and roadmap: references/roadmap.md
• Validation committee prompt (optional follow-up): references/002-idea-validation-committee.md