idea-validation-agents

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/.

Generates evidence-backed pivot options with scoring simulation, effort estimation, and indie buildability filtering. Writes pivot_options.json (structured) and pivot_report.md (human-readable brief). See canonical definition in skills/pivot-engine/SKILL.md.

Generates structured pivot options based on weak scoring dimensions. Writes pivot_options.json (structured) and pivot_report.md (human-readable brief). See canonical definition in skills/pivot-engine/SKILL.md.

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.

Models LTV, CAC by channel, LTV:CAC ratios, payback period, and viability verdict using retention data, market_insights calibration, and indie budget tiers. See canonical definition in skills/cac-modeler/SKILL.md.

Maps direct, indirect, substitute, and emerging competitors with review mining, positioning gap analysis, and market_insights-calibrated saturation scoring. See canonical definition in skills/competitor-mapper/SKILL.md.

Writes a decision brief with verdict, RAT experiment, pre-mortem, tier-calibrated next actions, and kill criteria. See canonical definition in skills/decision-memo/SKILL.md.

Scores human desire motivations (survival, status, belonging, control, curiosity). See canonical definition in skills/desire-evaluator/SKILL.md.

Evaluates organic reach, paid feasibility, platform advantages, creator fit, and founder edge with viral coefficient estimation, ASO rubric, and tier-adjusted verdicts. See canonical definition in skills/distribution-analysis/SKILL.md.

Aggregates all dimension scores into a final 0-100 score with verdict using multiplicative-floor algorithm and Riskiest Assumption Test (RAT). See canonical definition in skills/idea-scoring/SKILL.md.

Models WTP using Van Westendorp analysis, desire-premium multipliers, category benchmarks, and market_insights monetization signals. Includes freemium conversion estimation and B2B2C pricing. See canonical definition in skills/pricing-and-wtp/SKILL.md.

Predicts retention via usage frequency, habit formation, and churn risk. See canonical definition in skills/retention-predictor/SKILL.md.

Estimates TAM, SAM, and realistic SOM using triangulated bottom-up methodology with market_insights trend data, capture rate benchmarks, and growth-rate adjustments. See canonical definition in skills/tam-sam-som-builder/SKILL.md.

Analyzes market trends across TikTok, Reddit, App Store, and Google Trends. Writes a new file to memory/market_insights/. See canonical definition in skills/trend-analysis/SKILL.md.

Maps viral content and trending topics to concrete app opportunities. See canonical definition in skills/trend-to-product-mapper/SKILL.md.

Deep background interview to surface domain fit and distribution advantages. See canonical definition in skills/user-background-interviewer/SKILL.md.

Classifies the user into an ICP tier (beginner/builder/growth). See canonical definition in skills/user-segmentation-profiler/SKILL.md.

Identifies weak scoring dimensions, root causes, and failure modes. See canonical definition in skills/weakness-detection/SKILL.md.

Models CAC by channel and acquisition viability at indie scale. See canonical definition in skills/cac-modeler/SKILL.md.

Maps direct, indirect, and substitute competitors with positioning gaps. See canonical definition in skills/competitor-mapper/SKILL.md.

Writes a human-readable decision brief with verdict, strengths, risks, and next step. See canonical definition in skills/decision-memo/SKILL.md.

Evaluates organic reach, paid feasibility, platform advantages, creator fit. See canonical definition in skills/distribution-analysis/SKILL.md.

Aggregates all dimension scores into a final 0-100 score with verdict. See canonical definition in skills/idea-scoring/SKILL.md.

Models willingness to pay and viable pricing models. See canonical definition in skills/pricing-and-wtp/SKILL.md.

Estimates TAM, SAM, and realistic SOM using bottom-up methodology. See canonical definition in skills/tam-sam-som-builder/SKILL.md.

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.

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.

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.

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.

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.

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.

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.

Predicts retention potential by evaluating usage frequency, habit formation mechanics, and churn risk factors for a B2C app idea.

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.

Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit.

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.

Classifies the user into an ICP tier (beginner/builder/growth) based on experience, constraints, and goals. Run once per user session before any workflow.

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.