Brainstorming
xpinjection/test-driven-spring-boot
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior.
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.
$ npx skills add MaxKmet/idea-validation-agents --skill user-background-interviewer -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install MaxKmet/idea-validation-agents user-background-interviewer --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/user-background-interviewer .claude/skills/user-background-interviewer && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "user-background-interviewer" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/user-background-interviewer into .claude/skills/user-background-interviewer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "user-background-interviewer", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/user-background-interviewerType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add MaxKmet/idea-validation-agents --skill user-background-interviewer -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install MaxKmet/idea-validation-agents user-background-interviewer --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/user-background-interviewer .agents/skills/user-background-interviewer && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "user-background-interviewer" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/user-background-interviewer into .agents/skills/user-background-interviewer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "user-background-interviewer", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MaxKmet/idea-validation-agents --skill user-background-interviewer -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install MaxKmet/idea-validation-agents user-background-interviewer --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/user-background-interviewer .cursor/skills/user-background-interviewer && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "user-background-interviewer" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/user-background-interviewer into .cursor/skills/user-background-interviewer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "user-background-interviewer", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/MaxKmet/idea-validation-agents.git --path skills/user-background-interviewer--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add MaxKmet/idea-validation-agents --skill user-background-interviewer -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install MaxKmet/idea-validation-agents user-background-interviewer --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/user-background-interviewer .gemini/skills/user-background-interviewer && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "user-background-interviewer" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/user-background-interviewer into .gemini/skills/user-background-interviewer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "user-background-interviewer", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install MaxKmet/idea-validation-agents user-background-interviewerInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add MaxKmet/idea-validation-agents --skill user-background-interviewer -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/user-background-interviewer .github/skills/user-background-interviewer && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "user-background-interviewer" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/user-background-interviewer into .github/skills/user-background-interviewer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "user-background-interviewer", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add MaxKmet/idea-validation-agents --skill user-background-interviewer -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install MaxKmet/idea-validation-agents user-background-interviewer --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/MaxKmet/idea-validation-agents.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/user-background-interviewer .opencode/skills/user-background-interviewer && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "user-background-interviewer" agent skill from https://github.com/MaxKmet/idea-validation-agents/tree/main/skills/user-background-interviewer into .opencode/skills/user-background-interviewer/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "user-background-interviewer", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
user-background-interviewerConducts 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.
User Background Interviewer is an agent skill from MaxKmet/idea-validation-agents. 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.
Its SKILL.md is about 4.9k tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.
It sits in Agent Workflows, covering Brainstorming. The repository describes itself as: 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… The licence is MIT.
7 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit 3a4c800. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
No scripts in the folder and no shell commands in SKILL.md (its code samples are json).
From the folder's file list and the shell code blocks in SKILL.md.
No URLs in SKILL.md.
From URLs in SKILL.md, links to its own repository left out.
Names no API keys, tokens, secrets or passwords.
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
User Background Interviewer loads about 4.9k tokens when it runs. Until then it costs about 52 tokens; SKILL.md has 2,530 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.
The full file from MaxKmet/idea-validation-agents at commit 3a4c800, republished under its MIT licence (© MaxKmet). 2,530 words, ~4,907 tokens.
.claude/skills/user-background-interviewer/SKILL.md (or your agent's skills folder).<!-- version: 0.2.0 | outputs: memory/user_profile.md -->
Understand what types of ideas this specific user is most likely to succeed with. Surface hidden advantages, domain expertise, and natural distribution channels the user may not have considered.
memory/user_profile.md to extendBefore showing the opening message, check if memory/user_profile.md already exists.
If a profile exists, present a summary and ask:
I already have a profile on file for you:
- Domains:
<list strong_domains or selected_interest_domains>- Technical level: <technical_level, if present>
- Tier: <icp_tier, if present>
- Mode last time: <interview_mode>
Would you like to:
- "Use it" — Keep this profile and move on to idea generation.
- "Update" — Run the interview again (full or short version) to refresh your profile.
- "Browse topics" — Pick new topics to explore, keeping the rest of your profile.
Routing (existing profile):
user_profile.md.selected_interest_domains into the existing profile (preserve other fields).If no profile exists, proceed directly to the Opening Message.
Before asking the first question, say exactly this:
I'm going to ask you 10 questions to understand your background, skills, and interests. This helps me find app ideas that genuinely fit you — not generic ideas, but ones where you have a real edge.
Answer as freely as you'd like. There are no right or wrong answers.
Not sure where to start, or prefer not to answer questions? No problem — pick one:
- "Browse topics" — I'll show you real product domains people pay for. Pick 2–3 that interest you, and I'll generate ideas around those.
- "Short version" — Just 4 quick questions instead of 10.
- "Skip" — Jump straight to idea generation with generic recommendations.
Routing:
If the user wants to skip entirely, still ask the mandatory technical ability question:
No problem — I'll skip the interview. Just one quick question I need to generate relevant ideas:
What's your technical ability? (no-code / beginner / intermediate / expert)
If the user refuses to answer even this, default to "beginner" and note it.
Then write a minimal profile:
{
"strong_domains": ["unknown"],
"hidden_opportunities": [],
"natural_problem_spaces": [],
"distribution_advantages": [],
"inner_circle_domains": [],
"technical_level": "no-code | beginner | intermediate | expert",
"fit_score_by_niche": {},
"interview_summary": "User skipped the background interview. Technical level: <level>. Profile is generic — recommendations will not be personalized to domain fit or distribution advantages.",
"interview_mode": "skipped",
"all_questions_and_answers": []
}Then proceed to the next skill in the workflow. Downstream skills will use default/neutral values when profile data is missing.
When the user has no idea what they want to build or prefers not to answer personal questions, present product domains they can browse and pick from. These domains are organized around core human desires (from memory/extra-context/core-human-desires.md) but presented as concrete, relatable product categories — not psychology theory.
After presenting each batch and receiving the user's response, show this status prompt:
Your picks so far: <list selected domains, or "none yet">
Pick 2–3 domains total. Then:
- Say "more" to see the next batch of topics
- Say "continue" to start generating ideas with your selected topics
If the user already has 2–3 selections and says "more", show the next batch but remind them: "You've already picked <N> — feel free to swap any out, or say continue whenever you're ready."
If the user says "continue" with fewer than 2 selections, prompt: "Pick at least one more — it helps me generate better ideas. Or say more to see another batch."
If the user says "continue" with more than 3 selections, accept it but note: "That's a lot of ground to cover — I'll focus on the top 3 that produce the strongest signals."
Present exactly this:
Here are some real product spaces where people actually spend money. Look through them and pick 2–3 that interest you — you can select from this batch or say "more" to see another batch. When you're happy with your picks, say "continue".
1. Health & Body — People pay to feel healthier, track symptoms, and manage conditions. Examples: calorie trackers, sleep monitors, symptom journals, medication reminders
2. Personal Finance — People pay to feel in control of their money and build wealth. Examples: budget planners, expense trackers, investment portfolio dashboards, savings challenges
3. Fitness & Movement — People pay to get stronger, look better, and stay consistent. Examples: workout trackers, running coaches, home exercise programs, gym log apps
4. Food & Nutrition — People pay to eat better without the mental load of planning. Examples: meal planners, recipe organizers, grocery list builders, macro trackers
5. Productivity & Focus — People pay to get more done, reduce overwhelm, and feel organized. Examples: task managers, time blockers, habit trackers, Pomodoro timers
6. Dating & Relationships — People pay to find connection, improve relationships, and feel less alone. Examples: dating profile coaches, couples check-in apps, communication skill builders
7. Parenting & Family — People pay to be better parents and manage family chaos. Examples: baby trackers, chore schedulers, co-parenting coordinators, milestone journals
8. Career & Professional Growth — People pay to advance, earn more, and signal competence. Examples: resume builders, interview prep tools, salary negotiation guides, skill trackers
9. Social & Community — People pay to belong, share interests, and not feel isolated. Examples: local event finders, hobby matchmakers, accountability partner apps, group challenge platforms
10. Personal Style & Image — People pay to look good and express who they are. Examples: outfit planners, wardrobe organizers, skincare routine trackers, haircut reference savers
11. Mental Health & Stress — People pay to feel calmer, manage anxiety, and process emotions. Examples: mood trackers, guided journals, breathing exercises, therapy session notes
12. Learning & Education — People pay to acquire new skills and feel like they're growing. Examples: language learning apps, flashcard systems, course trackers, reading habit builders
13. Creative Tools — People pay to make things — art, music, writing, video — and share them. Examples: photo editors, beat makers, writing prompt generators, video thumbnail creators
14. Journaling & Reflection — People pay for structured self-awareness and personal narrative. Examples: gratitude journals, daily reflection prompts, year-in-review generators, life timeline apps
15. Hobbies & Collections — People pay to organize, track, and deepen their hobbies. Examples: plant care trackers, board game loggers, book lists, travel planners, wine journals
16. Home & Living — People pay to manage their space, reduce maintenance stress, and improve their environment. Examples: home maintenance schedulers, cleaning routines, moving checklists, interior design planners
17. Pets & Animals — People pay to take better care of their pets (and share cute photos). Examples: pet health trackers, feeding schedulers, vet visit logs, pet photo journals
18. Sustainability & Ethics — People pay to live according to their values and reduce guilt. Examples: carbon footprint trackers, ethical brand finders, waste reduction challenges, local farm finders
19. Side Hustles & Freelancing — People pay for tools that help them make more money independently. Examples: invoice generators, client trackers, income dashboards, gig expense loggers
20. Spirituality & Mindfulness — People pay to find meaning, build rituals, and feel grounded. Examples: meditation timers, prayer trackers, astrology journals, daily intention setters
Once the user picks 2–3 domains and says "continue" (or similar), you must ask this follow-up before proceeding. Do not skip it — technical level determines what kinds of ideas are feasible for this user:
Great choices. Before I generate ideas, I need to know one thing:
What's your technical ability?
- No-code — I use tools like Bubble, Glide, or Zapier but don't write code
- Beginner — I can follow tutorials and modify existing code
- Intermediate — I can build a simple app from scratch on my own
- Expert — I can build and ship production apps, including backend/infra
Wait for their answer. If they don't pick one of the four levels, map their response to the closest option (e.g., "I know some Python" → beginner or intermediate based on context). Then write the profile:
{
"strong_domains": ["unknown"],
"hidden_opportunities": [],
"natural_problem_spaces": [],
"distribution_advantages": [],
"inner_circle_domains": [],
"inner_circle_testers_available": false,
"fit_score_by_niche": {},
"selected_interest_domains": ["<domain-1>", "<domain-2>", "<domain-3>"],
"technical_level": "no-code | beginner | intermediate | expert",
"interview_summary": "User browsed topic domains and selected: <domains>. Technical level: <level>. No background interview conducted — recommendations based on interest selection only.",
"interview_mode": "browse",
"all_questions_and_answers": []
}The selected_interest_domains field is used by the orchestrator to guide trend-analysis (which niches to research) and trend-to-product-mapper (filter ideas to these domains). This replaces domain-fit scoring — instead of matching ideas to expertise, the system matches ideas to stated interest.
Ask only these four questions (numbered [1/4] through [4/4]):
Question [1/4] covers the mandatory technical ability question. If the user's answer to [1/4] only addresses domain and skips technical level, follow up: "Got it — and what's your technical level? (no-code / beginner / intermediate / expert)"
Apply the same validation rules as the full interview. Write the output using the same schema, filling in what's available and noting gaps.
If at any point the user resists a question or expresses discomfort:
"answer": "declined" in the output.Ask each question one at a time. Show the counter format [X/10] at the start of each question. Do not ask the next question until the current answer is validated (see Validation Rules below).
[1/10] — Technical Skills
What programming languages, platforms, or technical tools do you use regularly? For each one, tell me roughly how long you've been using it and whether you'd call yourself a beginner, intermediate, or expert.
Covers: technical skills
[2/10] — Industry Experience & Inner Circle
What industry or professional domain have you spent the most time in? What do you understand about this space that most outsiders wouldn't?
Also — think about your close friends, family members, or relatives. What do they do for work? Are any of them in industries you find interesting, and would they be willing to give you honest feedback, test an early version of an app, or help you understand their daily problems? (Even one person who'd answer your questions regularly is a massive advantage.)
Covers: industry experience, domain access through personal network
[3/10] — Past Projects
Tell me about a project you've built or worked on — personal, professional, or a side project. What was it, what happened to it, and what's the single biggest thing you learned from it?
Covers: past projects
[4/10] — Interests and Hobbies
What do you spend time on outside of work? Name 2–3 things you genuinely care about — things you'd seek out without anyone asking you to.
Covers: interests and hobbies
[5/10] — What People Ask You
What do friends, colleagues, or people in your life regularly ask you for help with? What topics or problems do people treat you as the go-to person for?
Covers: what people ask them
[6/10] — Communities
What online or offline communities are you part of — subreddits, Discord servers, forums, professional groups, local clubs? Which ones do you actively participate in vs. just observe?
Covers: social patterns (communities)
[7/10] — Content You Consume
What content do you consume most obsessively — specific YouTube channels, newsletters, podcasts, subreddits, X accounts? What topics do you actively seek out or find yourself going down rabbit holes on?
Covers: social patterns (content)
[8/10] — Core Strengths
Which of the following best describes your natural strengths? Pick your top 1–2:
- Engineering / building
- Design / UX
- Marketing / growth
- Sales / persuasion
- Operations / systems thinking
- Research / analysis
Covers: strengths
[9/10] — Existing Audience or Content Creation
Have you created any content online — videos, articles, social posts, a newsletter — or built any kind of following or community? If yes: what topic, what platform, and roughly how large?
Covers: content creation and distribution advantages
[10/10] — Constraints
What are your real constraints for building an app? Give me your best estimate for:
- Available hours per week
- Monthly budget for tools, ads, or subscriptions (in USD)
- Is this a main focus or a side project?
- How much risk are you comfortable with: low (I need it to work fast), medium, or high (I can experiment for months)?
Covers: budget, time, risk tolerance
After each answer, check before proceeding:
| Situation | Action |
|---|---|
| Answer is a single word or clearly too vague | Ask a targeted follow-up: "Can you be more specific? For example, [give a concrete example relevant to the question]." |
| Answer doesn't address the question | Rephrase gently: "I want to make sure I understand — [restate what you're looking for]." |
| Answer contradicts a previous answer | Flag and clarify: "Earlier you mentioned [X], but this suggests [Y] — which is more accurate?" |
| User says "I don't know" or "not sure" | Prompt with options: "Take your best guess — even a rough answer helps. For instance, [two or three concrete examples]." |
| Answer is clear and specific | Proceed to the next question immediately. |
Do not ask more than one follow-up per question. If the second attempt is still too vague, accept what was given and note the gap in the output.
Write to memory/user_profile.md:
{
"strong_domains": [],
"hidden_opportunities": [],
"natural_problem_spaces": [],
"distribution_advantages": [],
"inner_circle_domains": [],
"inner_circle_testers_available": false,
"selected_interest_domains": [],
"technical_level": "",
"fit_score_by_niche": {},
"interview_summary": "",
"interview_mode": "full | fast | browse | skipped",
"all_questions_and_answers": []
}inner_circle_domains field captures industries accessible through the user's personal network. This is a high-signal input for trend-to-product-mapper — domain access through a friend or relative who'd give honest feedback is nearly as valuable as direct experience.interview_mode = "skipped", downstream skills should treat all profile-dependent adjustments as neutral (no domain fit bonus, no distribution advantage, no tier adjustment).interview_mode = "browse", the selected_interest_domains field drives niche selection in trend-analysis and idea filtering in trend-to-product-mapper. The system trades domain-fit precision for user engagement — a user who actively chose "Personal Finance" and "Side Hustles" is more motivated than one assigned those niches by an algorithm.memory/extra-context/core-human-desires.md but reframed as consumer product categories. The underlying desires (survival, status, belonging, etc.) inform why people pay — the domain labels are how users naturally think about what interests them.© MaxKmet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
Just SKILL.md in skills/user-background-interviewer of MaxKmet/idea-validation-agents.
Open the folder on GitHubat commit 3a4c800
User Background Interviewer next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| User Background Interviewer this skillMaxKmet/idea-validation-agents | 474 | — | ~4.9k | Automated safety check: Pass | MIT | |
| Brainstormingxpinjection/test-driven-spring-boot | 112 | 54 repos | ~2.6k | Automated safety check: Pass | MIT | |
| LLM Councilgcpdev/llm-council-skill | 461 | 1 repos | ~1k | Automated safety check: Notes | MIT | |
| Typesafe AIOpenAgentsInc/openagents | 455 | 9 repos | ~2.5k | Automated safety check: Pass | MIT | |
| Yao Meta Skillyaojingang/yao-meta-skill | 2.7k | — | ~768 | Automated safety check: Pass | MIT | |
| Trellis StartROYIANS/foliq-print-template-designer | 135 | 6 repos | ~646 | Automated safety check: Pass | MIT |
xpinjection/test-driven-spring-boot
You MUST use this before any creative work - creating features, building components, adding functionality, or modifying behavior.
gcpdev/llm-council-skill
Multi-LLM collaborative brainstorming and planning. An agent skill from gcpdev/llm-council-skill.
OpenAgentsInc/openagents
Build AI-powered software with TypeSafe: small units of AI intelligence you can use like programming primitives.
yaojingang/yao-meta-skill
Create, improve, or evaluate an existing skill from workflows, prompts, SOPs, scripts.
ROYIANS/foliq-print-template-designer
Initializes an AI development session by reading workflow guides, developer identity, git status, active tasks, and project guidelines from .trellis/.
jnMetaCode/superpowers-zh
Turns a rough idea into an approved design before any code is written, sorting the request into spike, bounded or architectural and enforcing an approval gate.
MaxKmet/idea-validation-agents
Models LTV, CAC by channel, LTV:CAC ratios, and payback period for an indie developer.
MaxKmet/idea-validation-agents
Maps the full competitive landscape — direct, indirect, substitute, and emerging competitors — with positioning gap analysis, review mining, and marketinsights-calibrated saturation scoring.
MaxKmet/idea-validation-agents
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/idea-validation-agents
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/idea-validation-agents
Evaluates organic reach potential, paid feasibility, platform distribution advantages, creator economy fit, and founder edge for a B2C app idea.
MaxKmet/idea-validation-agents
Aggregates all dimension scores into a final idea score (0–100) and issues a verdict.
Categories
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. User Background Interviewer is an agent skill from MaxKmet/idea-validation-agents. 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.
User Background Interviewer fits situations like: tasks that involve Brainstorming.
Run `npx skills add MaxKmet/idea-validation-agents --skill user-background-interviewer -a claude-code`. Or copy the skill folder (skills/user-background-interviewer in MaxKmet/idea-validation-agents) into .claude/skills/user-background-interviewer in your project. Claude Code loads it when a task matches its description.
Run `npx skills add MaxKmet/idea-validation-agents --skill user-background-interviewer -a codex`. Or copy the skill folder (skills/user-background-interviewer in MaxKmet/idea-validation-agents) into .agents/skills/user-background-interviewer in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add MaxKmet/idea-validation-agents --skill user-background-interviewer -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/user-background-interviewer, .gemini/skills/user-background-interviewer, .github/skills/user-background-interviewer and .opencode/skills/user-background-interviewer in your project.
SKILL.md names no scripts, command-line tools or credentials: User Background Interviewer is instructions for the agent only.
SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.
User Background Interviewer is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.
About 4.9k tokens (SKILL.md is roughly 20k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.
Skills that share tags, products or a category with User Background Interviewer: Brainstorming (xpinjection/test-driven-spring-boot, 112 stars), LLM Council (gcpdev/llm-council-skill, 461 stars), Typesafe AI (OpenAgentsInc/openagents, 455 stars) and Yao Meta Skill (yaojingang/yao-meta-skill, 2.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
MaxKmet (a GitHub user) maintains it in MaxKmet/idea-validation-agents, which has 474 GitHub stars. The repository holds 15 skills in this directory. The repository was last updated on June 16, 2026.
Source: MaxKmet/idea-validation-agents on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.