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Jakeschincariol

Founder Consumer skill

The consumer panel. Spins up a swarm of buyer sub-agents (default 100, --quick for 20) trained on the user's target customer, each with a different income, age, buying behaviour and objection, shows every one the same pitch, and runs the business through 100 buyer scenarios to see who buys, who doesn't, and why. Tallies the answers into buy rates by segment, the reasons people pass in their own words, what would flip

$npx skills add Jakeschincariol/founder-skill --skill founder-consumer
View this skill on GitHubJakeschincariol/founder-skill/skills/founder-consumer/SKILL.md
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Pack installs
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Updated
35 days ago
License
MIT
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Jakeschincariol

Founder Consumer

Install Founder Consumer

Pick your agent. Every command is ready to paste.

$npx skills add Jakeschincariol/founder-skill --skill founder-consumer

The open skills CLI detects your agents (Claude Code, Cursor, Codex and 70+ more) and installs to the right folder. Add -g to install globally.

01

Install it

Run the command above, or upload the folder in Claude.

02

Ask naturally

Describe the task. Your agent loads founder-consumer when the request matches its description.

03

Name it if needed

If it does not trigger, say “use the founder-consumer skill”. In Codex, type $founder-consumer.

The skill itself

SKILL.md

FolderGitHub

founder-consumer

The craziest part of the pack. Instead of guessing whether people will buy, you ask a hundred of them, each one a sub-agent playing a specific buyer drawn from your target customer. You are the moderator. You never answer for a buyer.

What the user typed after /founder-consumer: $ARGUMENTS

The tool

All bookkeeping goes through panel.py in this skill's folder:

python3 "${CLAUDE_SKILL_DIR}/panel.py" <command>

Below, PANEL means exactly that. If the path is not expanded, use the base directory Claude Code printed for this skill. State lives in founder/panel/.

Step 1: the target customer

Write founder/customer.json (shape: customer.example.json in this folder):

  • business, and target: who the customer is, in one specific line.
  • segments: 2 to 4 groups with a share and an income range [low, high].
  • behaviours: 4 to 8 buying behaviours with a share and a how line (daily regular, deal hunter, reads every review, loyal to a competitor...).
  • objections: the 4 to 8 doubts this kind of buyer really has.
  • habits (optional): everyday context lines that make a buyer concrete.

Ground it in something real. Use what the user knows about their customers, and if /founder-competitors ran, the complaints in founder/competitors.md. If the user has real customer data (interviews, reviews, survey answers), prefer it to your guesses and say which parts are guesses. Show the user the profile in a few lines and let them correct it before you deal: a wrong customer makes the whole panel wrong.

Step 2: the pitch

Write founder/pitch.md: what a buyer would actually see. The product, the price, where and how to get it, any opening offer. Three to six plain lines, no superlatives, nothing the business cannot deliver. Every buyer sees exactly this.

Step 3: deal and run

PANEL init --customer founder/customer.json --pitch founder/pitch.md --n 100
PANEL prompts

init deals the persona cards (same seed, same cards; the seed is recorded). prompts writes one brief per buyer and lists them in waves of 10. For each wave, send ONE message with one Agent tool call per buyer in that wave (the Agent tool is called Task in older Claude Code versions):

  • subagent_type: general-purpose
  • description: panel <id>
  • prompt: Read <brief path> and follow it exactly. It is your whole brief.

Wait for the whole wave before the next one. Claude Code runs about 10 tool calls at once by default, so 100 buyers is 10 waves. After the last wave:

PANEL check      # lists missing or broken answers
PANEL prompts    # rewrites briefs for those only; run them once more
PANEL tally

If a buyer printed its JSON in its reply instead of writing the file (it happens), file its own reply with PANEL save <id> and the reply on stdin; save refuses anything that is not a valid answer. A buyer that fails twice is left out and counted in the results. Never write an answer for a buyer yourself.

Before a 100-buyer run, tell the user it is 100 sub-agent calls and suggest --quick (20 buyers) for a first look. Sub-agents write one file each into founder/panel/answers/; in the default permission mode that is one approval per file, so suggest accept-edits mode (Shift+Tab) for the run.

Step 4: read it to the user

PANEL tally writes founder/panel/results.md and results.json. Give the user:

  1. The headline: "40 buy · 60 pass" and the buy rate.
  2. Who buys and who doesn't: the segment and behaviour rows that differ most.
  3. Why they pass: the top three reasons with one quote each, as written.
  4. What would flip a no: the most repeated answers.
  5. One sentence on what to change before spending money, and which skill does it (pricing, offer, marketing).

Honest limits, say them once

These are simulated buyers. They are good at surfacing objections, segments and wording you had not thought of, and bad at predicting real conversion: language models lean agreeable, so treat the buy rate as an upper bound. Confirm the big calls with real people (a waitlist, a pre-sale, a landing page with a price) before signing anything. Do not present panel quotes as customer testimonials.

The brief every buyer gets

panel.py fills the card into a fixed template (see BRIEF in the script): who the buyer is (name, age, segment, income, buying behaviour, a habit, the doubt that comes to mind), the pitch word for word, an instruction not to be agreeable and not to invent facts, and the exact JSON to write: buys, purchases in the first month, a reason code, the reason in their own voice, their main objection, what would change their mind, and four price answers (too cheap, a bargain, getting expensive, too expensive). Never edit a brief for one buyer.

Output

founder/customer.json, founder/pitch.md, founder/panel/ (cards, briefs, answers, results). Next: /founder-pricing reads the price answers, /founder-offer and /founder-marketing read the objections.

Tips for Founder Consumer

  • • Start a fresh session after installing so your agent picks up the new skill.
  • • This skill ships scripts. Read them before the first run, and run it in a project without secrets first.
  • • It is part of a pack with 11 skills. Install only the ones you need with --skill to keep triggers precise.
  • • If two skills overlap, mention the one you want by name.

Questions about Founder Consumer

What does the Founder Consumer skill do?

The consumer panel. Spins up a swarm of buyer sub-agents (default 100, --quick for 20) trained on the user's target customer, each with a different income, age, buying behaviour and objection, shows every one the same pitch, and runs the business through 100 buyer scenarios to see who buys, who doesn't, and why. Tallies the answers into buy rates by segment, the reasons people pass in their own words, what would flip

How do I install Founder Consumer?

Run "npx skills add Jakeschincariol/founder-skill --skill founder-consumer" in your project. The skills CLI installs it for Claude Code, Cursor, Codex and 70+ other agents. In Claude on the web, upload the skill folder as a ZIP under Customize > Skills.

Does Founder Consumer work in Cursor and Codex?

Yes. Founder Consumer uses the open SKILL.md format, so it works in Claude Code, Claude, Cursor, OpenAI Codex, Gemini CLI, GitHub Copilot and other agents that support agent skills.

Is Founder Consumer free?

Founder Consumer is open source on GitHub under the MIT license. It is free to install; check the license before commercial use.

Who made Founder Consumer?

Founder Consumer is published by Jakeschincariol in the Jakeschincariol/founder-skill repository, together with 10 other skills.

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