
founder-consumer
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 a no, and price answers for founder-pricing. Use when the user says "would people buy this", "test it on customers", "run the consumer panel", "simulate buyers", "who is my customer", or "validate demand".
- Installs
- 341
- Last 24h
- +27
- Trending rank
- #4714
- Security
- Not audited
Install
Works with every agent the skills CLI supports.
npx skills add https://github.com/jakeschincariol/founder-skill --skill founder-consumer- 01
Install
Run the command in your project. The CLI asks which agents to install for.
- 02
Describe the task
Ask your agent for something this skill covers. It loads founder-consumer automatically when relevant.
- 03
Review the result
The agent follows the SKILL.md steps, scripts and references bundled with the skill.
SKILL.md
The instructions your agent reads when the skill is triggered.
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, andtarget: who the customer is, in one specific line.segments: 2 to 4 groups with ashareand anincomerange [low, high].behaviours: 4 to 8 buying behaviours with ashareand ahowline (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-purposedescription: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:
- The headline: "40 buy · 60 pass" and the buy rate.
- Who buys and who doesn't: the segment and behaviour rows that differ most.
- Why they pass: the top three reasons with one quote each, as written.
- What would flip a no: the most repeated answers.
- 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.
FAQ
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 a no, and price answers for founder-pricing. Use when the user says "would people buy this", "test it on customers", "run the consumer panel", "simulate buyers", "who is my customer", or "validate demand".
How do I install founder-consumer?
Run npx skills add https://github.com/jakeschincariol/founder-skill --skill founder-consumer in your project. The skills CLI detects the agents you use and copies the skill into the right folder. For Claude Code you can also place the skill folder at ~/.claude/skills/founder-consumer/ (personal) or .claude/skills/founder-consumer/ (project).
Which AI agents can use founder-consumer?
Any agent that supports the open Agent Skills format (a folder with a SKILL.md file), including Claude Code, Codex, Cursor, GitHub Copilot, Gemini CLI, Windsurf, Cline, OpenCode and more.
Is founder-consumer safe to install?
No partner security audit is available yet. Skills can run commands and scripts, so read the SKILL.md and any bundled files before installing.
Who maintains founder-consumer?
It is published by jakeschincariol in jakeschincariol/founder-skill. It has 341 recorded installs.
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Finds the price buyers will actually pay. Reads the consumer panel's four price answers per buyer into a Van Westendorp price-sensitivity range (too cheap, a bargain, getting expensive, too expensive), sets it against what competitors really charge and against the CFO's margin, and recommends a price, a price ladder (good / better / best) and an opening offer to test. Use when the user says "how much should I charge", "price this", "is $X too expensive", "pricing strategy", "what price", or after the consumer panel.
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