Repository
MaxKmet/idea-validation-agents agent skills
- skills
- 15
- GitHub stars
- 473
GitHub description: “AI agents that act as your personal venture analyst - from startup idea brainstorming to full validation and go-to-market strategy. Built for developers who'd rather validate in 10 minutes than regret in six months. Powered by Claude Code, OpenAI Codex, and Cursor.”
- Stars
- 473 (56 forks)
- Licence
- MIT
- Last push
- Jun 2026
- Created
- Apr 2026
- ai-agents
- ai-skills
- appstore
- aso-intelligence
- brainstorming
- claude-code
- codex
- cursor
- idea-generation
- idea-validation
- market-analysis
- skills
- startup
- tiktok
- workflow-automation
Install all skills
npx skills add MaxKmet/idea-validation-agentsAdd --skill <name> for a single skill and -a <agent> to choose the agent (see the agent guides).
Skills in MaxKmet/idea-validation-agents, ranked
Ranked by score. Sort bymost stars,trending,newest,recently updated
| # | 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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~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/ | 473 | — | ~422 | Automated safety check: Pass | MIT | 3 mo ago |
Questions, answered from the data.
What is the best skill in MaxKmet/idea-validation-agents?
Cac Modeler from MaxKmet/idea-validation-agents ranks first of the 15 skills in MaxKmet/idea-validation-agents listed here, with the highest score: its repository has 473 GitHub stars, its SKILL.md loads about 3.3k tokens and it passes the automated safety check with no findings. Next come Competitor Mapper and Decision Memo.
Are the skills in MaxKmet/idea-validation-agents official?
None yet. All 15 skills in MaxKmet/idea-validation-agents listed here come from community repositories; a skill counts as official when the product's own GitHub organization publishes it.
How do I install all skills from MaxKmet/idea-validation-agents?
Run npx skills add MaxKmet/idea-validation-agents in your project: the open-source skills CLI installs the repository's skills into your coding agent's skills folder. To install a single skill, open its page here for the exact command.
How are these skills ranked?
By Skill Navigator score, which combines the GitHub stars of the skill's repository (shared across that repo's skills and discounted for large collections), how many other GitHub owners carry a copy of the skill, and automated SKILL.md quality checks, minus penalties for safety-check warnings and for each further skill from the same repository. Skills that fail the safety check are not listed.