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Found 134 Skills
Design lean startup experiments (pretotypes) for a new product. Creates XYZ hypotheses and suggests low-effort validation methods like landing pages, explainer videos, and pre-orders. Use when validating a new product idea, creating pretotypes, or testing market demand.
Display the current state of the FPF knowledge base
Research ideation partner. Generate hypotheses, explore interdisciplinary connections, challenge assumptions, develop methodologies, identify research gaps, for creative scientific problem-solving.
Systematically validate your business hypotheses before building anything. Master Steve Blank's Customer Development methodology that became the foundation of Lean Startup and YC's approach. Use when: **Starting a new venture** to avoid building something nobody wants; **Before writing a line of code** to validate problem-solution fit; **Pivoting decisions** to systematically test new directions; **Early-stage fundraising** to prove market validation; **Product roadmap planning** to prioritiz...
Use when making predictions or judgments under uncertainty and need to explicitly update beliefs with new evidence. Invoke when forecasting outcomes, evaluating probabilities, testing hypotheses, calibrating confidence, assessing risks with uncertain data, or avoiding overconfidence bias. Use when user mentions priors, likelihoods, Bayes theorem, probability updates, forecasting, calibration, or belief revision.
Build stronger product taste + intuition as a PM by running a Taste Calibration Sprint (benchmark set, product critique notes, intuition→hypothesis log, validation plan, practice loop). Use for “product taste”, “product sense”, “intuition”, “calibrate taste”.
Statistical analysis: t-tests, chi-squared, Mann-Whitney, p-values, CIs, Bonferroni/BH, Bayesian A/B
Design rigorous A/B tests with hypotheses, variants, metrics, and sample size calculations.
This skill should be used when the user's request or requirement is ambiguous and needs iterative questioning to become actionable. Trigger on "clarify requirements", "refine requirements", "요구사항 명확히", "요구사항 정리", "뭘 원하는 건지", "make this clearer", "spec this out", "scope this", "/clarify". Turns vague inputs into concrete specs. For strategy blind spots use unknown; for content-vs-form reframing use metamedium.
Generate structured research questions, testable hypotheses, and empirical strategies from a topic or dataset
Display the current state of the FPF knowledge base
Facilitates the learning step of a proven customer-interview method — the synthesis half: reads a directory of per-interview debrief files against the working HYPOTHESES.md and QUESTIONS.md and proposes evidence-cited updates ONE at a time — double down, tune numbers, mark disproved, park heard-once observations in a 'That's funny' watch section, add new hypotheses with new questions — applying each agreed change directly to the files with a change log, and ending with a stop-or-continue-or-re-aim verdict on the interviewing itself. Load when the user says 'what did we learn from these interviews,' 'update my hypotheses from the interviews,' 'synthesize my interview notes,' or 'should I keep interviewing?' Do NOT load for recording a single conversation into a debrief (the previous step), for writing initial goals, hypotheses, or interview questions (earlier steps), or for deciding what to build next (comes after this method).