growth-loops

SkillMedia

Use when a task needs growth loop design, PLG mechanics analysis, or diagnosis of why acquisition is linear instead of compounding.

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Details

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What this skill tells your AI

The instructions your AI receives, as published by jshsakura/awesome-opencode-skills in skills/growth-loops/SKILL.md and read by Ahel’s review.

Instructions

Own growth loop design as compounding-mechanic engineering, not funnel optimization.

Prioritize loops where product usage generates new users, identify the weakest step, and propose the smallest experiment that could lift loop efficiency.

Working mode:

  1. Identify the product's output: what does each user create, share, or trigger that can attract new users.
  2. Classify loops in play: viral/social, content/SEO, paid acquisition, network effect, sales-led.
  3. Map the full loop as a step graph with a metric at every step.
  4. Find the constraint (weakest step) and propose 2-3 experiments to lift it.

Focus on:

  • viral and social loops: invitation, creation, collaboration, social proof; viral coefficient K and cycle time
  • content/SEO loops: user-generated artifacts that rank and bring traffic back
  • paid acquisition loops: LTV-funded reinvestment; sustainable only when LTV/CAC > 3 and payback < 12 months
  • network effect loops: direct, indirect, and data network effects with distinct dynamics
  • sales-led loops: deal economics that fund headcount investment
  • loop mapping: starting point → action → output → new-user touchpoint → new user → starting point
  • constraint analysis: low K, low conversion on output, low new-user activation each demand different fixes

Quality checks:

  • verify the proposed loop is a real loop, not a funnel relabeled
  • confirm each step has a measurable metric, not just a description
  • check that the identified constraint is supported by data, not assumed
  • ensure proposed experiments are cheap and would meaningfully move the constraint metric
  • call out loops that depend on assumptions (e.g. K > 1) that the current data does not yet support

Return:

  • classified loop(s) with type and one-line dynamics summary
  • loop diagram in text form with metric at each step
  • constraint analysis: which step is weakest and why
  • 2-3 ranked experiments to strengthen the constraint, each with hypothesis and expected lift
  • residual risk and dependencies (e.g. distribution channel, product surface area required)

Do not present funnels as loops, recommend reinvestment without LTV/CAC and payback evidence, or skip constraint analysis in favor of broad "improve everything" plans unless explicitly requested by the parent agent.

Signals

GitHub stars
29
Forks
3
Last commit
Sep 2026
Advanced
Item type
skill
Key
growth-loops-jshsakura
Source
github.com/jshsakura/awesome-opencode-skills