referral-program
by Eronredreferral-program helps you design, launch, and improve an in-app referral or invite system for conversion. Use it to choose rewards, define invite mechanics, assess deep-link dependencies, reduce fraud risk, and size incentives against CAC and LTV. It’s a practical referral-program guide for products with real sharing behavior.
This skill scores 84/100, which means it is a solid directory listing for users who want an AI-guided referral-program specialist rather than a generic growth prompt. The repository gives enough trigger terms, workflow structure, and decision logic for agents to start correctly and reduce guesswork, though it would still benefit from more supporting files and examples.
- Strong triggerability: the description explicitly covers referral, invite, share-to-earn, viral loop, K-factor, and related phrasings, helping agents recognize when to use it.
- Operational workflow is present: the body includes an initial assessment with concrete questions about value proposition, CAC, LTV, deep link infra, and audience fit.
- Trustworthy structure: valid frontmatter, substantial body length, no placeholder markers, and repo/file references suggest a real skill rather than a stub.
- No install command or supporting files, so adopters must infer some setup and context from SKILL.md alone.
- The evidence shows solid guidance, but the repository appears to rely on one markdown file without scripts or references, limiting deeper execution support.
Overview of referral-program skill
The referral-program skill helps you design, launch, and improve an in-app referral or invite system that actually changes acquisition, not just adds a “share” button. It is best for teams that need a practical referral-program guide for conversion: reward design, invite mechanics, deep-link dependencies, fraud risk, and whether the program is worth shipping at all.
What referral-program is for
Use the referral-program skill when the job is to turn existing users into acquisition channels through invite-to-earn, refer-a-friend, double-sided rewards, or viral loops. It is especially useful when you need to decide if a referral-program install makes sense for a product with real sharing behavior, such as social, collaboration, savings, marketplace, or multiplayer apps.
When this skill is a good fit
This skill fits readers who already have a product and want to answer: what should people get, who should get it, how do we measure it, and what will stop abuse? It is most useful when the referral program needs to support measurable install growth, not just brand awareness.
What makes it different
The referral-program skill is decision-oriented. It forces the key inputs that determine success: customer value, CAC, LTV, deep-link infrastructure, and natural sharing moments. That means the output should help you choose a reward structure and avoid common traps like overspending on incentives or rewarding low-quality invites.
How to Use referral-program skill
Start with the right inputs
A strong referral-program usage prompt should include your product type, the action you want referred users to complete, your current acquisition cost, and any reward constraints. For example: “Design a referral-program for a budgeting app. Existing users can invite friends after they connect a bank account. CAC is $18, LTV is about $120, and we want a double-sided reward under $10 total value.”
Install and read the skill in order
Use the referral-program install path from your skill workflow, then read SKILL.md first. If you are working from the repository directly, inspect README.md, AGENTS.md, metadata.json, and any supporting folders if they exist. In this repo, the key source topics surfaced in the skill are the ones that matter most for execution: initial assessment, whether a referral program is right, reward structure patterns, and reward sizing.
Turn a vague ask into a useful prompt
If the user says “make our app viral,” translate that into the actual referral-program problem: what is the trigger, what is the reward, who is eligible, what counts as a successful referral, and what guardrails prevent fraud. The skill works best when the prompt includes the conversion event, the invite surface, and the unit economics target.
Workflow that improves output quality
Use the skill as a sequence, not a single brainstorm. First validate fit, then size rewards against CAC and LTV, then define the invite flow and measurement plan, and only then polish the messaging. If you skip the sizing step, the referral-program skill can still generate ideas, but it will be less reliable for conversion and margin control.
referral-program skill FAQ
Is referral-program only for consumer apps?
No. The referral-program skill can also fit B2B, marketplace, and subscription products if there is a real reason for users to invite others. The key question is not industry but whether the product creates obvious value from more participants, better collaboration, or shared savings.
Does referral-program replace ordinary growth prompts?
Not exactly. A normal growth prompt may produce generic campaign ideas, while a referral-program skill is focused on program design, reward economics, and invite mechanics. If you need viral coefficient thinking, invite-link implementation, or fraud-aware reward logic, this skill is the better starting point.
What if I do not have LTV or CAC yet?
That is a warning sign for referral-program install. Without those numbers, reward sizing becomes guesswork and the program can easily become unprofitable. In that case, the skill should push you to estimate unit economics first or route you to a metrics-focused workflow before finalizing the referral design.
Is this skill beginner-friendly?
Yes, if you can answer a few business questions. The referral-program guide is most useful when the user is willing to provide product context, current acquisition data, and the specific referral action they want to optimize. It is less helpful when the request is only “add referrals” with no product details.
How to Improve referral-program skill
Give the skill better unit economics
The biggest upgrade to referral-program output is sharper economic input. Share CAC by channel, rough LTV or ARPU, expected conversion rate after invite, and any margin limits. Those numbers let the skill size rewards in a way that supports referral-program for Conversion instead of random incentive inflation.
Specify the referral behavior you already have
Tell the skill where invites happen today: after a successful action, after a social milestone, on onboarding completion, in a share sheet, or inside a collaborative workflow. That helps the referral-program skill design around existing behavior instead of inventing a flow that users will not naturally trigger.
State your abuse and rollout constraints
If you care about fraud, include self-referrals, multi-accounting, device reuse, or reward farming concerns. If you care about implementation, mention your deep-link stack such as Branch, AppsFlyer OneLink, or Adjust. If you care about launch risk, ask for a staged rollout and success metrics so the referral-program guide can stay practical.
Iterate from one clear success metric
The best refinement loop is to ask for one outcome at a time: more invites sent, higher invite-to-install conversion, better activated referrals, or lower reward cost per acquired user. The referral-program skill improves when each iteration is tied to a measurable bottleneck rather than a broad “make it better” request.