startup-validator

Installation
SKILL.md

@rules/evidence-and-scoring.md @references/frameworks.md

Startup Validator

Score startup ideas with explicit evidence and uncertainty instead of optimism. Organize results as a multi-file folder for future reference.

<when_to_use>

Use this skill when:

  • validating a new startup or product idea
  • deciding whether to proceed, pivot, or narrow the market
  • preparing for customer discovery or fundraising conversations

Do not use this skill when:

  • the main job is generating many new ideas
  • the request is technical implementation planning
  • the user wants first-principles redesign rather than validation scoring

Boundary:

  • use genius-thinking for broad ideation
  • use elon-musk for assumption teardown and redesign

Examples:

/startup-validator AI-based education service
/startup-validator subscription healthcare app
/startup-validator B2B purchasing automation

</when_to_use>

<input_check>

If $ARGUMENTS is missing, ask:

Which startup idea should we validate?

If founder, market, or customer evidence is missing, continue with explicit assumptions instead of inventing certainty.

</input_check>

<owned_job>

For each run:

  1. Restate the idea and identify the key unknowns.
  2. Score the idea using the framework set in references/frameworks.md.
  3. Mark evidence quality and uncertainty for each major claim.
  4. Summarize the strongest strengths, critical weaknesses, and next validation steps.

</owned_job>

<document_shape>

Output Structure

.hypercore/startup-validator/[topic-slug]/
├── flow.json           # phase tracking
├── thesis.md           # idea framing + key hypotheses
├── thiel-scores.md     # per-question rationale and scores
├── pmf-forces.md       # PMF checklist + Forces of Progress
└── verdict.md          # final score + grade + weaknesses + roadmap
  • Use ASCII kebab-case for [topic-slug] (e.g., ai-education-service).
  • Each phase produces its own file for organized reference.
  • flow.json tracks progress through phases. See references/flow-schema.md for the schema.
  • If the folder exists from a prior run, read existing files before updating.

</document_shape>

<flow_tracking>

Flow Tracking

Write flow.json at the start and update as each phase completes.

Phase progression

Phase Output file Next
frame thesis.md — idea thesis + 3 key hypotheses score
score thiel-scores.md — 7 questions with per-question rationale pmf
pmf pmf-forces.md — PMF checklist + Forces of Progress analysis verdict
verdict verdict.md — total score, grade, weaknesses, roadmap done

Resume support

If flow.json already exists, read it and continue from the last incomplete phase. Do not restart completed phases.

</flow_tracking>

Workflow

Phase Task Output file
1 Frame the idea and missing context thesis.md
2 Score the Thiel questions thiel-scores.md
3 Check PMF and switching forces pmf-forces.md
4 Apply penalties, summarize, recommend next actions verdict.md

Scoring rule:

  • do not fabricate precise scores when evidence is thin
  • mark uncertain sections as provisional and explain what evidence would change them

<output_contract>

Each output file should follow the formats defined in the KO version's result_structure section:

  • thesis.md: one-line thesis, value hypothesis, growth hypothesis, key unknowns
  • thiel-scores.md: per-question score + rationale + improvement direction
  • pmf-forces.md: PMF checklist, Forces of Progress (Push/Pull/Habit/Anxiety), switching probability
  • verdict.md: total score/grade, critical weaknesses with severity, improvement roadmap (immediate/30d/90d)

</output_contract>

Before finishing, check:

  • unsupported certainty is called out as provisional
  • evidence quality is distinguished from opinion
  • the score ties back to named frameworks
  • the output includes concrete next validation actions
  • all output files are saved under .hypercore/startup-validator/[topic-slug]/
  • flow.json status is set to completed
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Installs
31
GitHub Stars
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First Seen
Mar 5, 2026