Agent skill · Documentation

early-access-designer

Use when the user asks to "design an early access program", "set up a waitlist and beta stages", or "define beta graduation criteria"; produces a waitlist→concept→alpha→beta→GA stage ladder with per-stage purpose and opt-in semantics, quantified graduation criteria per stage (labeled Estimated), a cohort-gating and invite-throttling plan, tester recruitment with launch-day social-proof prep, a feedback-loop spec where every status change notifies its subscribers, and a referral-loop mechanism spec (invite codes, anti-abuse). Not for waitlist acquisition strategy or the capture-flow spec — use

aaron-he-zhugithub.com/aaron-he-zhuGitHub ↗
claude-codeApache-2.0
Install
npx skills add aaron-he-zhu/aaron-marketing-skills --skill early-access-designer --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 1
SKILL.md size: 13 KB
Bundled scripts: none
Version: 19.1.0
Requires: Claude Code and compatible agent-skill hosts
Path: launch/research/early-access-designer/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 2,508
Language: Python
Read our review of the source →

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# Early Access Designer Designs the early-access program for a product launch — the waitlist → concept → alpha → beta → GA stage ladder, per-stage graduation criteria, cohort gating and invite throttling, the tester feedback loop, and the referral mechanics that fill the next cohort. It sits in the Research phase of the [RAMP loop](../../../references/ramp-benchmark.md) and feeds the RAMP `R` early-access sub-item (*early-access program design sound — stage gating + graduation criteria*). Because the ladder defines what each stage publicly *means*, it is the upstream of the `RAMP-R1` stage-truth veto: a beta dressed as GA fails at the gate, and the honest ladder designed here is what prevents that. The ladder follows an early-access state-machine pattern (modeled on the PostHog Early Access flow — **a pattern to follow, not a product guarantee**): interest registration and stage opt-in are phases of the same action, not separate lists; an explicit opt-in or opt-out always overrides any targeting rule; and a GA rollout must explicitly confirm whether previously opted-out users are included before it ships. **Scope guard**: this skill designs the stage ladder, graduation criteria, co

What's inside
Steps it walks through
  1. Quick Start
  2. Skill Contract
  3. Handoff Summary
  4. Data Sources
  5. Instructions
  6. Save Results
  7. Reference Materials
  8. Next Best Skill
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About this skill
What does the early-access-designer skill do?

Use when the user asks to "design an early access program", "set up a waitlist and beta stages", or "define beta graduation criteria"; produces a waitlist→concept→alpha→beta→GA stage ladder with per-stage purpose and opt-in semantics, quantified graduation criteria per stage (labeled Estimated), a cohort-gating and invite-throttling plan, tester recruitment with launch-day social-proof prep, a feedback-loop spec where every status change notifies its subscribers, and a referral-loop mechanism spec (invite codes, anti-abuse). Not for waitlist acquisition strategy or the capture-flow spec — use

How do I install it?

Run `npx skills add aaron-he-zhu/aaron-marketing-skills --skill early-access-designer --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From aaron-he-zhu/aaron-marketing-skills, a repository with 2,508 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

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