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Max Kmet 的 Skills 45
weakness-detection
Analyzes idea-scoring output to identify the weakest dimensions, root causes of low scores, and probable failure modes if the idea were pursued as-is.
user-segmentation-profiler
Classifies the user into an ICP tier (beginner/builder/growth) based on experience, constraints, and goals. Run once per user session before any workflow.
user-background-interviewer
Conducts a deep background interview to understand what types of app ideas this specific user is most likely to succeed with based on their domain knowledge, networks, and skills.
trend-to-product-mapper
Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit.
trend-analysis
Analyzes market trends across platforms (TikTok, Reddit, App Store, Google Trends) for a given topic or category. Writes a new file to memory/market_insights/.
tam-sam-som-builder
Estimates TAM, SAM, and realistic SOM for a B2C app idea using triangulated bottom-up methodology anchored to market_insights trend data, competitor revenue proxies, and community size signals. Includes indie capture rate benchmarks and growth-rate adjustments by trend velocity.
retention-predictor
Predicts retention potential by evaluating usage frequency, habit formation mechanics, and churn risk factors for a B2C app idea.
pricing-and-wtp
Models willingness to pay using Van Westendorp price sensitivity analysis, desire-premium multipliers, category benchmarks, and market_insights monetization signals. Recommends pricing model, freemium conversion estimate, and annual/monthly strategy.
pivot-engine
Generates structured pivot options for a scored idea based on weak dimensions, market_insights signals, and founder constraints. Includes scoring simulation, minimum viable pivot criteria, effort estimation, and indie buildability filtering.
idea-scoring
Aggregates all dimension scores into a final idea score (0–100) and issues a verdict. Implements a multiplicative-floor algorithm with Riskiest Assumption Test (RAT). The final output of every validation workflow.
distribution-analysis
Evaluates organic reach potential, paid feasibility, platform distribution advantages, creator economy fit, and founder edge for a B2C app idea. Includes viral coefficient estimation, ASO scoring rubric, and tier-adjusted verdicts.
desire-evaluator
Scores the strength of core human desire motivations (survival, status, belonging, control, curiosity) for a given app idea to predict user pull and retention potential.
decision-memo
Writes a concise, human-readable decision brief summarizing the full validation analysis — including score, verdict, RAT experiment, pre-mortem, and tier-appropriate next actions. The document a founder actually acts on.
competitor-mapper
Maps the full competitive landscape — direct, indirect, substitute, and emerging competitors — with positioning gap analysis, review mining, and market_insights-calibrated saturation scoring. Feeds into idea-scoring, cac-modeler, pricing-and-wtp, and tam-sam-som-builder.
cac-modeler
Models LTV, CAC by channel, LTV:CAC ratios, and payback period for an indie developer. Uses market_insights to calibrate channel CPMs and competitive intensity. Includes indie budget tier definitions and viability thresholds.
weakness-detection
Identifies weak scoring dimensions, root causes, and failure modes. See canonical definition in skills/weakness-detection/SKILL.md.
user-segmentation-profiler
Classifies the user into an ICP tier (beginner/builder/growth). See canonical definition in skills/user-segmentation-profiler/SKILL.md.
user-background-interviewer
Deep background interview to surface domain fit and distribution advantages. See canonical definition in skills/user-background-interviewer/SKILL.md.