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By MaxKmet
Skills
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| # | Skill | Repository | Stars | Used in | Tokens | Auto-check | Licence | Updated |
|---|---|---|---|---|---|---|---|---|
| 1 | Models LTV, CAC by channel, LTV:CAC ratios, and payback period for an indie developer. | MaxKmet/ | 477 | — | ~3.3k | Automated safety check: Pass | MIT | 3 mo ago |
| 2 | Maps the full competitive landscape — direct, indirect, substitute, and emerging competitors — with positioning gap analysis, review mining, and marketinsights-calibrated saturation scoring. | MaxKmet/ | 477 | — | ~3.3k | Automated safety check: Pass | MIT | 3 mo ago |
| 3 | Writes a concise, human-readable decision brief summarizing the full validation analysis — including score, verdict, RAT experiment, pre-mortem, and tier-appropriate next actions. | MaxKmet/ | 477 | — | ~2k | Automated safety check: Pass | MIT | 3 mo ago |
| 4 | 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. | MaxKmet/ | 477 | — | ~551 | Automated safety check: Pass | MIT | 3 mo ago |
| 5 | Evaluates organic reach potential, paid feasibility, platform distribution advantages, creator economy fit, and founder edge for a B2C app idea. | MaxKmet/ | 477 | — | ~3.1k | Automated safety check: Pass | MIT | 3 mo ago |
| 6 | Aggregates all dimension scores into a final idea score (0–100) and issues a verdict. | MaxKmet/ | 477 | — | ~3.2k | Automated safety check: Pass | MIT | 3 mo ago |
| 7 | Generates structured pivot options for a scored idea based on weak dimensions, marketinsights signals, and founder constraints. | MaxKmet/ | 477 | — | ~4.7k | Automated safety check: Pass | MIT | 3 mo ago |
| 8 | Models willingness to pay using Van Westendorp price sensitivity analysis, desire-premium multipliers, category benchmarks, and marketinsights monetization signals. | MaxKmet/ | 477 | — | ~3.7k | Automated safety check: Pass | MIT | 3 mo ago |
| 9 | Predicts retention potential by evaluating usage frequency, habit formation mechanics, and churn risk factors for a B2C app idea. | MaxKmet/ | 477 | — | ~577 | Automated safety check: Pass | MIT | 3 mo ago |
| 10 | Estimates TAM, SAM, and realistic SOM for a B2C app idea using triangulated bottom-up methodology anchored to marketinsights trend data, competitor revenue proxies, and community size signals. | MaxKmet/ | 477 | — | ~3.3k | Automated safety check: Pass | MIT | 3 mo ago |
| 11 | Analyzes market trends across platforms (TikTok, Reddit, App Store, Google Trends) for a given topic or category. | MaxKmet/ | 477 | — | ~1.2k | Automated safety check: Pass | MIT | 3 mo ago |
| 12 | Maps viral social content and trending topics to concrete app opportunities by extracting the underlying problem and validating monetization fit. | MaxKmet/ | 477 | — | ~1.8k | Automated safety check: Pass | MIT | 3 mo ago |
| 13 | 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. | MaxKmet/ | 477 | — | ~4.9k | Automated safety check: Pass | MIT | 3 mo ago |
| 14 | 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. | MaxKmet/ | 477 | — | ~508 | Automated safety check: Pass | MIT | 3 mo ago |
| 15 | Classifies the user into an ICP tier (beginner/builder/growth) based on experience, constraints, and goals. | MaxKmet/ | 477 | — | ~422 | Automated safety check: Pass | MIT | 3 mo ago |
