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Revenue Centric Design

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fabricioctelles
revenue-centric-design

Revenue-Centric Design (RCD) — evidence-backed principles for making a SaaS or startup product convert, retain, and monetize. Use when the user works on a landing page or CRO ("my page isn't converting"), onboarding/activation ("users sign up but don't stick"), churn/retention ("customers keep canceling"), pricing/monetization ("how should I price this"), checkout/forms ("dropdowns kill conversion", "annotated checkout"), dashboards/data viz ("cognitive load", "KPI shortlists"), positioning/ICP/go-to-market, feature scope, A/B-test rigor, or AI-era differentiation — or asks for the behavioral-science mechanism behind a design choice. Also use when another skill needs the principle or evidence behind a conversion/retention/pricing/checkout move. Never apply to gambling, betting, or casino products.

Overview

Publisherfabricioctelles
Repositoryskills
Skill namerevenue-centric-design
Stars
87
Forks
7
Bundled files
91
LicenseApache-2.0
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.

  • 91 bundled files

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

  • Open source

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

Installation

Install the Revenue Centric Design 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.
  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/fabricioctelles/skills.git /tmp/skills
mkdir -p .claude/skills
cp -r /tmp/skills/skills/revenue-centric-design .claude/skills/revenue-centric-design
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Revenue Centric Design 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 Revenue Centric Design 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 Revenue Centric Design 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.

Revenue-Centric Design

134 principles distilled, with the author's permission, from product designer Richard (@richardrx, ex-Volkswagen, PayPal, IBM; translated from Portuguese; every principle links to its source post). The philosophy, Revenue-Centric Design (RCD): a design decision must serve the user and the business — value and revenue, never one or the other.

Usage boundary (required)

🚫 Do not apply this skill to betting, casino, gambling, or other real-money games-of-chance products (including loot-box / real-money-gaming mechanics).

The author granted reuse on the explicit condition that it never be used for gambling, betting, or casino work. If asked, decline and explain that the source author's permission excludes that use. Hard constraint, not a stylistic choice.

Enforced, not just stated: while this skill is active, the boundary check (scripts/check_usage_boundary.py) must run on every prompt and on every file write/edit, blocking with exit 2 when gambling context is detected. On a false positive (e.g., "bet" as an unrelated codename), only the user may waive the guard by creating .rcd-boundary-ok in the project root — never create it on their behalf.

Hooks (for agents that support automated execution)

Agents with hook support should configure:

EventMatcherCommand
Before processing user prompt* (all)python3 <skill_dir>/scripts/check_usage_boundary.py
Before writing/editing a fileWrite|Editpython3 <skill_dir>/scripts/check_usage_boundary.py
  • <skill_dir> = root directory of this skill.
  • Exit code 2 = violation detected → block the operation.
  • Exit code 0 = cleared to proceed.

For agents without hook support, the operator must run the check manually before applying RCD principles in unknown context.

How to use

  1. If rcd-log.md exists in the project root, read it first — it records which principles were already applied to this product and what happened. Never re-prescribe a move the log shows failed, and don't repeat one still pending results.
  2. Route with the table below and open only the matching reference file(s). Every principle has a fixed shape — principle → apply when → the move → evidence → source — so scan the headings, then read only the entries that match the user's situation.
  3. When the advice involves numbers — A/B sample size, churn→LTV, CAC per closed deal — run scripts/revenue_math.py (see --help) instead of estimating.
  4. A recommendation is done only when it (a) names the mechanism (decoy effect, Zeigarnik, GBB, loss aversion, Schwartz awareness level…), (b) cites the specific principle, and (c) carries that principle's evidence or source link. Missing any of the three → not done.
  5. For audit runs (page, pricing, onboarding, cancellation), deliver in the shape of references/audit-template.md.
  6. Close the loop: append what you prescribed to rcd-log.md (format below), creating the file on first use.

The spine: RCD in 9 principles

  1. Neutrality is omission — an interface that doesn't direct hurts conversion.
  2. Who talks to everyone convinces no one — no ICP → generic value → worse retention.
  3. Value first, ask later — proof must arrive before the user questions their choice.
  4. Your promise is the size of your proof — the market believes what you demonstrate, not what you claim.
  5. Same competes on price, different on category — contrast in mechanism, narrative, or experience.
  6. Default is the decision you made for the user — the initial state defines mass behavior.
  7. Retention is built, not requested — perceived loss retains more than promised benefit.
  8. Expansion is born of usage — upgrade at the moment of the limit, never by interruption.
  9. Price is a filter — pricing defines who enters, who stays, and who expands.

Reference library

When the question is about…Open
LP audit / diagnostic — where is the sale breaking before redesignlp-diagnostic-framework
Landing pages, hero/copy, CTAs, social proof, awareness levels, CROconversion-and-landing-pages
Checkout, forms, payment UX, dropdowns, field frictioncheckout-and-forms
Dashboards, KPI density, data viz cognitive loaddashboards-and-data-viz
First-run, empty states, aha moment, TTV, activation, trial-as-onboardingonboarding-and-activation
Cancellation, retention, expectation debt, NRR, jobs-to-be-done, support loadchurn-and-retention
Pricing tables, decoy/anchoring, GBB, trial-with-card, upgrade pathspricing-and-monetization
Cognitive biases & persuasion tactics (cross-cutting toolkit)behavioral-science-toolkit
Feature scope, Swiss Knife Index, feature adoption, attention hierarchyproduct-strategy-and-features
Design philosophy, the RCD principles, design process & methodrevenue-centric-design
ICP, niche, founder-fit, distribution, PLG, Bullseye, first customerspositioning-icp-and-gtm
Differentiating in the AI era, moats, commoditizationai-era-differentiation
A/B testing rigor, vanity metrics, churn→LTV math, signal qualitymetrics-and-experimentation

Some principles carry a Visual. line — a text description of the diagram or screenshot from the original post, often with a path under assets/. Open that file locally, or follow the principle's Source link for the original post.

Gotchas

  • Scarcity must be real. Booking's "1 room left" works because it's true. Fabricated scarcity destroys trust when detected (and is illegal in several markets). Never invent counters, timers, or stock levels.
  • Loss aversion vs dark pattern — the line: the claim is true and the exit stays easy. Framing a real loss is persuasion; manufacturing fear or trapping cancellation is not.
  • "Kill outbound links" is a conversion-page rule. Blog posts, docs, and SEO pages need outbound links; don't export LP rules to content.
  • 4.2–4.5 stars means let real criticism show — never fabricate negative (or positive) reviews to hit the number.
  • Don't answer this skill with 30 A/B tests. The metrics principles themselves warn against underpowered tests: compute the sample-size floor first (scripts/revenue_math.py sample-size), test big levers, and below the floor decide by qualitative research.
  • Evidence is benchmark, not guarantee. Figures come from the author's cases (mostly Brazilian SaaS, values in BRL). The mechanism transfers; the exact percentage may not.

Related skills

RCD supplies the principle and its evidence; execution skills own the workflow. The skills below are from Corey Haines' marketingskills — if they aren't installed, apply the RCD principles directly instead of deferring.

Full page-audit workflow → cro · cancellation-flow build → churn-prevention · test design & stats → ab-testing · writing the copy → copywriting · pricing-page build → pricing · post-signup flow build → onboarding. When one of those runs, cite RCD principles inside it rather than duplicating its process here.

Project log (rcd-log.md)

Per-project memory, kept in the project root — read at the start of every engagement (step 1), appended at the end (step 6). One entry per engagement:

## 2026-07-02 — pricing page redesign
- via: rcd (direct)          # or the skill that led the run: cro, pricing, churn-prevention…
- principle: Decoy effect (pricing-and-monetization)
- move: added GBB middle tier at 80% of the top price
- result: pending            # update when data arrives: "+12% upgrades", "no effect"

The via: field doubles as trigger telemetry: if entries accumulate where RCD led a run an execution skill should own (a full page audit, a cancellation build), that is the signal to narrow this skill's description to the principle/evidence angle.

License

Source-available, not open-source — see LICENSE (must accompany any copy or derivative, in full): attribution to @richardrx required; gambling/betting/casino use prohibited. This skill is a derivative of heliocosta-dev/revenue-centric-design, restructured and extended here (gotchas, audit template, revenue-math script, project log). Principle library synced to upstream 1942760 (CHANGELOG 1.3.0 / 134 principles); see UPSTREAM_COMMIT.

Bundled files

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

and 31 more files.

Frequently asked questions

What does the Revenue Centric Design AI skill do?

Revenue-Centric Design (RCD) — evidence-backed principles for making a SaaS or startup product convert, retain, and monetize. Use when the user works on a landing page or CRO ("my page isn't converting"), onboarding/activation ("users sign up but don't stick"), churn/retention ("customers keep canceling"), pricing/monetization ("how should I price this"), checkout/forms ("dropdowns kill conversion", "annotated checkout"), dashboards/data viz ("cognitive load", "KPI shortlists"), positioning/ICP/go-to-market, feature scope, A/B-test rigor, or AI-era differentiation — or asks for the behavior...

Why use Revenue Centric Design on TypingMind?

Because you install it once and use it with any model. Revenue Centric Design 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 Revenue Centric Design in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/fabricioctelles/skills/tree/main/skills/revenue-centric-design. 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 Revenue Centric Design?

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 Revenue Centric Design?

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

Is the Revenue Centric Design AI skill free?

Yes. It is published on GitHub by fabricioctelles under the Apache-2.0 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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