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Bootstrap Growth

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paulklayvc
bootstrap-growth

Design partnerships for startups with little upfront cash: research fitting customers, influencers, and ambassadors, shape their offers, check economics, and plan pilots. Use for bootstrapped acquisition, founding customer deals, referral partners, and ambassador recruitment; not general content marketing or paid ad optimization.

Overview

Publisherpaulklayvc
Repositoryskills
Skill namebootstrap-growth
Stars
50
Forks
4
Bundled files
1
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 1 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by paulklayvc on GitHub. Read the source before you install it.

Installation

Install the Bootstrap Growth AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/paulklayvc/skills/tree/main/bootstrap-growth
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/paulklayvc/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/bootstrap-growth .claude/skills/bootstrap-growth
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Bootstrap Growth in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Bootstrap Growth on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Bootstrap Growth is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Bootstrap Growth

Turn a startup's distinctive assets into a credible exchange: partners contribute adoption, distribution, feedback, or expertise; the startup offers something they value and can realistically receive. Combine useful benefits today with potential upside later. Count delivery costs, future payouts, and founder time even when upfront cash is small.

This method is adapted from the user-provided article about core supporters and ambassador programs. Its reported sales and startup failure statistics are anecdotes or unverified claims, not forecasts or evidence for the user's product.

Establish the offer's foundation

Use available project context before asking for information. Identify the product and stage, target customer, proof of demand, growth bottleneck, cash limit, delivery capacity, and assets the team can actually offer. For economic estimates, establish price, variable costs, and payment timing. Ask only for missing inputs that would materially change the recommendation; mark provisional assumptions clearly.

For a full acquisition or recruitment plan, also establish the target industry, geography, language, and partner profile that will guide research. Ask for missing decisions in one short batch; look up public facts yourself. Do not silently choose a market for the user. Continue independent work on the offer and economics while waiting for a research-critical answer.

Answer why would this product win for this audience, and why would this partner believe it? Tie the answer to evidence such as demonstrated customer outcomes, an engaged user base, distinctive capabilities, or a credible distribution advantage. Separate observed evidence from the founder's hypothesis. If the answer is weak, propose a small product or partnership test that could establish it before promising scale.

Inventory benefits a larger competitor may find difficult to provide: tailored development, fast decisions, meaningful influence on the roadmap, access to founders, learning, recognition, early product access, and participation in commercial upside. Choose benefits according to the partner's actual motivations. Do not assume status or access is valuable to everyone.

Choose the appropriate partnership

Select only the model that fits the request; a plan need not include every model.

ModelBest fitCandidate exchange
Founding customer / core supporterA customer whose adoption, feedback, or reference would materially improve the businessScoped customization and favorable pricing for paid adoption, structured feedback, and an agreed case study; consider advisory participation or equity only when their contribution warrants it
Core influencerA credible creator with a relevant, engaged audience and meaningful distribution capacityProduct access and revenue share for defined distribution; consider additional upside for recruiting productive partners or measurable long-term contributions
AmbassadorActual users, fans, or smaller creators who already value the productAccess, genuine exclusivity, participation, recognition, and referral earnings for useful feedback and audience introductions

Prioritize audience fit, trust, ability to deliver, and mutual value over follower counts or prestige. A recognizable early partner can help recruit subsequent partners when there is an actual result and permission to reference it. Do not invent candidate names, audience metrics, endorsements, or commitments. Verify current facts when researching specific candidates.

Founding customers and core influencers

For a founding customer, explain both sides of the deal: the startup gains a real deployment, product learning, revenue, and potentially a reference; the customer gains a solution shaped around their needs and participation in its development. Bound custom work, support, and acceptance criteria. Near-zero margin can be a deliberate learning investment only when its cost and limit are explicit.

For a core influencer, make the opportunity comparable to participating in a product business without requiring them to build it. Specify the audience benefit, creator contribution, sales attribution, revenue share, and any reward for bringing in other productive influencers. Keep the reward connected to genuine product value and outcomes.

Reserve equity or significant shared upside for contributions valuable enough to justify it. When equity is relevant, outline the proposed contribution, measurable milestones, earning schedule, and what happens if participation stops. Label these as commercial discussion points; do not invent valuation, percentages, or settled terms. Do not offer equity automatically to every customer or creator.

Ambassadors

Build a small bundle from benefits the product and team can sustain:

  • Useful free or discounted access, especially for people who already want the product.
  • Invite codes, private betas, or early features when access is genuinely limited. State the real capacity or timing constraint.
  • A feedback channel and realistic access to the team, including a way to show which suggestions influenced the product.
  • Referral economics that make early participation worthwhile, with clear attribution and payout terms.
  • Community recognition, private groups, or partner benefits that have a real recipient value and a known delivery cost.

Explain why an ambassador would participate before assuming they will promote. Avoid manufactured scarcity, promised roadmap influence the team cannot provide, or founder-access benefits that cannot survive the proposed cohort size.

Research and qualify real candidates

For a full acquisition, partnership, or recruitment plan, research real candidates as part of the task without waiting for a separate request to search. Once the market and partner profile are clear, use available web search and read current sources. Follow references/partner-research.md for qualification and the shortlist. Research only the models selected for this product.

Start with relevant customers, users, and relationships the user already has, then research additional candidates where the pilot needs them. Respect an explicit restriction to existing contacts. For an ambassador program, look for evidence of actual product use or relevant participation; a creator with a matching audience is a prospective partner, not a verified fan. If demand evidence is weak, research a small discovery cohort for the learning test rather than imply readiness to scale.

Rank candidates by audience fit, credible contribution, attainable value exchange, and a realistic route to a conversation. Tie proposed benefits and first-touch drafts for priority candidates to the evidence found. Use the shortlist to choose the pilot's first targets, and distinguish public facts, inferred fit, and terms still to be negotiated.

If search is unavailable or relevant evidence cannot be verified, state the limitation and give candidate profiles and a concrete verification path; do not present guessed names as researched candidates. A narrow commission calculation, offer revision, or review of a supplied deal does not require a broad search. Investigate only external facts that would materially change that answer.

Check economics and commitments

Show what is exchanged, what it costs, and when each side receives value. Treat access, customization, support, and founder time as costs even when they require no immediate payment. Track equity dilution separately from cash contribution.

Define the commission basis before calculating it. For a simple sale where both commissions apply to the same revenue base:

text
N = revenue collected after discounts and refunds, excluding pass-through taxes
C = variable delivery, support, and payment processing cost per sale
r = direct partner commission rate applied to N
s = additional recruiting/override rate applied to that same sale, if any
contribution per sale = N * (1 - r - s) - C
cash break-even sales = ceil(fixed pilot cash cost / contribution per sale)

Use break-even only when contribution is positive and costs use the same period and scope. Adapt the calculation when commission bases differ, rewards are fixed amounts, or subscriptions pay commissions on renewals. Avoid counting refunds, fees, or discounts twice. Make recurring payout duration and refund treatment explicit. Do not use speculative lifetime value to hide a cash shortfall.

Use supplied numbers when available; otherwise show a labeled scenario or the missing inputs. There is no universal commission or equity percentage. A deliberate loss on a bounded pilot needs a budget and a learning objective. Also check whether delivery expenses fall due before customer receipts, even when eventual contribution is positive.

For any proposed offer, make the partner's contribution, startup obligations, attribution method, payout timing, duration, and exit conditions concrete enough to discuss. Treat drafts as proposals. Planning or drafting does not authorize contacting partners, granting access, issuing equity, changing live program settings, or committing money; carry out external actions only within explicit user authorization.

Design a test and interpret the result

Choose a pilot size and duration that fit the available cash and team capacity. Define a hypothesis, relevant partner profile, offer, owner, deliverables, tracking method, and a decision date. Set success and stop criteria before launch; use assumed thresholds only when labeled for validation.

Measure the path that matters for the chosen model: qualified invitation, acceptance, actual participation, referred or adopted usage, paying customers, retention, and contribution after incentives. Select the relevant measures rather than forcing a large dashboard. Acceptance or content output alone does not establish profitable acquisition.

If the offer is rejected, distinguish audience mismatch, low product value, weak proof, unattractive economics, and excessive effort before changing it. Stop or revise when the pilot reaches its agreed budget, time, or failure threshold. Do not keep increasing rewards or repeating outreach indefinitely.

Strong partners accepting the offer is an early signal. Delivered outcomes and repeatable economics are stronger evidence. Neither guarantees that paid distribution will scale; propose a separate measured test if the user later wants to invest in it.

Deliver the requested result

Match the user's language and scope. For a full plan, lead with the recommended model and why it fits, then provide a compact comparison of partner value, startup value, obligations, costs, and evidence gaps. Include the sourced, ranked candidate shortlist, tailored offers and first-touch drafts for priority targets, economic assumptions, and a concrete pilot with success/stop criteria and the next action. Link the pilot's targets and activities to the research. Label an incomplete or blocked shortlist rather than present a framework-only answer as a completed recruitment plan.

For a narrow request such as revising an ambassador invitation or evaluating one deal, deliver that artifact directly and surface only the unresolved issues that change it. Do not expand every task into a complete growth strategy.

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Bootstrap Growth AI skill do?

Design partnerships for startups with little upfront cash: research fitting customers, influencers, and ambassadors, shape their offers, check economics, and plan pilots. Use for bootstrapped acquisition, founding customer deals, referral partners, and ambassador recruitment; not general content marketing or paid ad optimization.

Why use Bootstrap Growth on TypingMind?

Because you install it once and use it with any model. Bootstrap Growth is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Bootstrap Growth in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/paulklayvc/skills/tree/main/bootstrap-growth. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Bootstrap Growth?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Bootstrap Growth?

As many as you like. As long as a model supports skills, you can use Bootstrap Growth with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Bootstrap Growth AI skill free?

Yes. It is published on GitHub by paulklayvc under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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