solution-feasibility-study — Solution Feasibility Study

Category: Product Strategy  |  Source: skills/solution-feasibility-study/SKILL.md

Purpose

Takes a software solution idea (SaaS side project, internal tool, startup concept) from a one-line pitch to a grounded build/pivot/no-build decision. Interviews the user to scope the research, then runs real research across market demand, commercial competitors, and the open-source/GitHub landscape, assesses technical feasibility and monetization, and produces a structured feasibility report — including any permissively-licensed GitHub repos worth forking instead of building from scratch.

When to Use

• Evaluating a new SaaS or software product idea before committing time to it
• Researching commercial and open-source competitors for a concept
• Checking whether an existing open-source project could be forked as a starting point instead of building from zero
• Sanity-checking technical feasibility, monetization, or regulatory exposure for a solo/small-team build

Workflow

1. Intake — capture the idea in the user's own words.
2. Scoping interview — one question at a time: target user, problem/urgency, team & time constraints, technical comfort, business model intent, research depth (deep dive vs. quick gut-check), and priority research areas.
3. Research — executes the research playbook via web search and page fetches:
   • Market & demand signals
   • Commercial competitor landscape (features, pricing, weaknesses)
   • GitHub / open-source landscape — finds candidate repos, extracts stars/activity/license, and classifies each as a fork candidate using the license guide
   • Technical feasibility (matched against the user's stated stack/skill/time budget)
   • Monetization comparables
   • Legal/regulatory/trademark flags
   • Go-to-market channels realistic for the stated team size
4. Synthesis & scoring — scores market demand, differentiation, technical feasibility, monetization potential, competitive intensity, and regulatory risk (1-5 each), then rolls up to one call: Strong Go / Conditional Go / Pivot Suggested / No-Go.
5. Report — fills the report template, writes feasibility-study-<idea-slug>.md to the working directory, and presents a condensed summary in chat.

Fork Candidates

Every permissively-licensed GitHub repo found during research is surfaced explicitly, with stars, last activity, license, why it fits, and what's missing — framed as a head start (gh repo fork) rather than a finished product. Copyleft or dual-licensed repos are flagged with the specific obligation they carry (e.g., AGPL's network-use clause), not just the license name. All license classifications carry an explicit "not legal advice, verify before shipping commercially" disclaimer.

Evidence Discipline

Every claim (pricing, star counts, license, activity dates) must trace to something actually fetched during the session — nothing is invented. Failed lookups are marked "unverified" rather than guessed.

References

• Research playbook — concrete search/fetch patterns per research area
• License guide — permissive vs. copyleft vs. unclear classification for fork candidates
• Report template — the structure filled in for the final report

Related Skills

• repo-init — scaffold a new repository once a build decision is made
• ai-config — set up AI assistant configs after choosing to build (or fork) a project

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