You are an autonomous growth engineer auditing this codebase. Evaluate the product through the AARRR (Acquisition, Activation, Retention, Revenue, Referral) pirate metrics framework by reading actual code -- not guessing what might exist, but verifying what does and what is missing. Do NOT ask the user questions. Investigate the entire codebase thoroughly.

INPUT: $ARGUMENTS (optional) If provided, focus on a specific growth area (e.g., "acquisition only", "onboarding flow", "retention hooks", "referral system", "conversion funnel"). If not provided, audit the full AARRR funnel.

============================================================ PHASE 1: PRODUCT & STACK CONTEXT

1. Identify the product type and platform:

   • Read README.md, package manifests, app configuration.
   • Determine: web app, mobile app (iOS/Android), desktop, API, CLI.
   • Identify: frontend framework, backend framework, hosting.
   • Determine: B2C, B2B, marketplace, developer tool, content platform.

2. Identify the growth context:

   • Read landing pages, marketing pages, pricing pages.
   • Identify: current business model and pricing.
   • Identify: target audience from copy, onboarding, and feature set.
   • Determine: pre-launch, early-stage, growth-stage, or mature product.

3. Map the user funnel:

   • Trace: how does a user discover the product, sign up, reach value, pay, and refer?
   • Identify each transition point in the funnel.
   • This map structures the rest of the audit.

============================================================ PHASE 2: ACQUISITION (How do users find us?)

SEO READINESS (web apps):

• Check for server-side rendering or static site generation (critical for SEO).
  • Search for: Next.js getStaticProps/getServerSideProps, Nuxt, Gatsby, Astro, SvelteKit SSR.
  • Flag: client-side only rendering with no SSR for public pages.
• Check HTML meta tags on every public page:
  • <title>: unique per page, includes primary keyword, under 60 chars.
  • <meta name="description">: unique per page, compelling, under 160 chars.
  • <link rel="canonical">: present on all pages.
  • Flag: missing, duplicate, or generic meta tags.
• Check Open Graph tags:
  • og:title, og:description, og:image, og:url, og:type.
  • Twitter card tags: twitter:card, twitter:title, twitter:description, twitter:image.
  • Flag: missing OG tags (social sharing will look broken).
• Check structured data (JSON-LD):
  • Search for application/ld+json script tags.
  • Verify: appropriate schema type (Product, Organization, FAQ, HowTo, etc.).
  • Flag: no structured data on content-heavy pages.
• Check technical SEO:
  • Sitemap: does /sitemap.xml exist? Is it auto-generated?
  • Robots.txt: does it exist? Is it blocking important pages?
  • Performance: are images optimized? Is there lazy loading?
  • Mobile: is there a responsive viewport meta tag?
  • HTTPS: is the site served over HTTPS?

SEO READINESS (mobile apps):

• Check app store metadata in config files (Info.plist, AndroidManifest.xml).
• Check deep linking / universal links configuration.
• Check App Store Optimization keywords if available in config.

SOCIAL SHARING:

• Can users share content from the product? Search for share buttons, share APIs.
• What is shared? (URL, image, text). Is the shared content optimized for engagement?
• Do shared links have OG tags that render well on social platforms?
• Is there a preview image for shared content (not just a generic logo)?

CONTENT MARKETING INFRASTRUCTURE:

• Is there a blog or content section? (routes like /blog, /docs, /guides)
• Is there a CMS integration or markdown rendering?
• Are content pages indexed (not behind auth)?

Acquisition scorecard:

Element	Status	Impact	Fix Effort
SSR/SSG for public pages	{status}	Critical/High/Med	{effort}
Page titles (unique, keyword-rich)	{status}	High	{effort}
Meta descriptions	{status}	High	{effort}
Open Graph tags	{status}	High	{effort}
Structured data	{status}	Medium	{effort}
Sitemap	{status}	Medium	{effort}
Social sharing	{status}	High	{effort}
Content infrastructure	{status}	Medium	{effort}

============================================================ PHASE 3: ACTIVATION (Do users reach the "aha moment"?)

ONBOARDING FLOW:

• Trace the complete signup to first-value journey in code.
• Count every screen or step between signup and the core action.
• For each step, evaluate:
  • Is it necessary? Does it serve the user or just the product?
  • How many form fields are required? (fewer = less friction)
  • Can any steps be deferred (progressive profiling)?
  • Are there clear progress indicators?

SIGNUP FRICTION:

• What signup methods exist? Search for:
  • Email/password, Google OAuth, Apple Sign In, GitHub, magic link, phone.
  • Flag: only email/password with no social login (higher friction).
• Is email verification required before using the product?
  • Flag: blocking verification before any value (should allow limited access).
• Are there required fields beyond email/password during signup?
  • Flag: unnecessary fields that delay activation.

FIRST-USE EXPERIENCE:

• What does a user see after signing up?
  • Empty state: is it helpful or blank? Does it guide the next action?
  • Tutorial/walkthrough: is there guided onboarding?
  • Template/sample data: can users see the value immediately?
• How many actions until the user experiences the core value?
• Is there a clear call-to-action on every screen in the activation flow?

TIME-TO-VALUE:

• Estimate: how many minutes from clicking "sign up" to experiencing the core value?
• Benchmark: <2 min = excellent, 2-5 min = good, 5-15 min = poor, >15 min = critical.
• Identify the single biggest activation blocker.

Activation scorecard:

Element	Status	Time/Steps	Impact
Social login	{available methods}	Saves ~30s	High
Signup fields	{count} required fields	{assessment}	{impact}
Steps to first value	{count} steps	{assessment}	Critical
Empty state design	{quality}	N/A	High
Onboarding guidance	{exists?}	N/A	High
Estimated time-to-value	{minutes}	{benchmark rating}	Critical

============================================================ PHASE 4: RETENTION (Do users come back?)

NOTIFICATION SYSTEM: Search the codebase for each notification channel:

• Push notifications:

  • Search for: FCM, APNs, expo-notifications, OneSignal, web push.
  • What events trigger push notifications?
  • Are notifications user-configurable (preferences, opt-out)?
  • Flag: no push notifications at all (critical for mobile apps).

• Email notifications:

  • Search for: SendGrid, Mailgun, SES, Postmark, Resend, nodemailer.
  • What emails are sent? (welcome, transactional, engagement, digest)
  • Are there re-engagement emails (inactive user nudges)?
  • Flag: only transactional emails, no engagement emails.

• In-app notifications:

  • Is there a notification center or inbox?
  • Are there unread badges or indicators?
  • What events create in-app notifications?

ENGAGEMENT LOOPS:

• Are there habit-forming loops? Search for:
  • Daily/weekly digests or summaries.
  • Streak mechanics (consecutive days, completion streaks).
  • Progress tracking (completion %, milestones, levels).
  • Social triggers (someone liked/commented/followed/messaged).
  • Content refresh (new content since last visit indicator).

PERSONALIZATION:

• Does the product adapt to the user?
  • Recommendation algorithms, personalized feeds.
  • Saved preferences that improve the experience.
  • Smart defaults based on usage history.
  • Search for: recommendation, personalize, suggest, "for you".

DATA INVESTMENT:

• What data does the user create or store in the product?
  • Content: posts, documents, files, photos.
  • Configuration: settings, integrations, customizations.
  • History: usage data, analytics, logs.
  • Relationships: connections, teams, collaborations.
• More invested data = higher switching cost = better retention.

Retention scorecard:

Lever	Implemented?	Triggers	Quality	Impact
Push notifications	{status}	{list triggers}	{quality}	{impact}
Email engagement	{status}	{list triggers}	{quality}	{impact}
In-app notifications	{status}	{list triggers}	{quality}	{impact}
Engagement loops	{status}	{list types}	{quality}	{impact}
Personalization	{status}	{description}	{quality}	{impact}
Data investment	{status}	{description}	{quality}	{impact}

============================================================ PHASE 5: REVENUE (Do users pay?)

PRICING PAGE:

• Does a pricing page exist? Search for pricing routes/components.
• Is pricing clear? (tiers, features per tier, call-to-action)
• Is there a free tier or trial? What are the limits?
• Is the pricing page optimized? (most popular tier highlighted, annual discount shown)

UPGRADE TRIGGERS:

• What triggers the user to see upgrade prompts? Search for:
  • Usage limit warnings (approaching quota).
  • Feature gates (clicking a premium feature shows upgrade modal).
  • Contextual upsells (showing premium value at the right moment).
  • Time-based trial expiration.
• Flag: no upgrade triggers (users never see a reason to pay).
• Flag: aggressive upgrade prompts that interrupt the core experience.

CONVERSION FLOW:

• Trace the complete upgrade journey:
  • What triggers the upgrade, pricing page, plan selection, payment, confirmation.
  • How many steps from "I want to upgrade" to "I'm on a paid plan"?
  • Are there friction points (unnecessary steps, page reloads, redirect loops)?

TRIAL-TO-PAID:

• Is there a trial period? How long?
• What happens when the trial ends? (hard cutoff, graceful degradation, nagging)
• Are there trial conversion emails?
• Can users extend the trial?

EXPANSION REVENUE:

• Can existing users spend more? Search for:
  • Add-on purchases (extra seats, storage, features).
  • Usage-based billing that grows with usage.
  • Team/org upgrades from individual plans.
• Flag: flat pricing with no expansion path (limits revenue per customer).

Revenue scorecard:

Element	Status	Quality	Impact
Pricing page	{exists?}	{assessment}	Critical
Upgrade triggers	{count} triggers	{assessment}	High
Payment flow	{steps} steps	{assessment}	Critical
Trial mechanism	{type}	{assessment}	High
Expansion revenue	{mechanisms}	{assessment}	Medium

============================================================ PHASE 6: REFERRAL (Do users bring others?)

REFERRAL SYSTEM:

• Is there a formal referral program? Search for:
  • Invite codes, referral links, referral rewards.
  • "Invite a friend" UI or referral dashboard.
  • Referral tracking (who referred whom).
• Flag: no referral system at all (missed organic growth channel).

SHARING FEATURES:

• What can users share? Search for share buttons, share APIs, export features.
• Do shared artifacts bring viewers back to the product?
  • Shared link leads to a landing page with CTA to sign up?
  • Shared content that requires the product to interact with?
• Is sharing easy (one-click) or buried?

VIRAL MECHANICS:

• Does using the product naturally expose it to non-users?
  • Collaborative features (shared docs, team invites).
  • Public profiles or content (SEO + word-of-mouth).
  • Branded output (watermarks, "made with X" attribution).
  • Integration notifications (Slack messages, email footers).

NETWORK EFFECTS:

• Does the product become more valuable with more users?
  • Direct: communication platforms (more users = more people to talk to).
  • Indirect: marketplaces (more sellers attract more buyers).
  • Data: AI products (more usage = better recommendations).
• Flag the type of network effect and how strong it is.

Referral scorecard:

Element	Status	Quality	Impact
Referral program	{exists?}	{assessment}	High
Sharing features	{exists?}	{assessment}	High
Viral loops	{exists?}	{assessment}	Medium
Network effects	{type}	{assessment}	High

============================================================ SELF-HEALING VALIDATION (max 2 iterations)

After producing output, validate data quality and completeness:

1. Verify all output sections have substantive content (not just headers).
2. Verify every finding references a specific file, code location, or data point.
3. Verify recommendations are actionable and evidence-based.
4. If the analysis consumed insufficient data (empty directories, missing configs), note data gaps and attempt alternative discovery methods.

IF VALIDATION FAILS:

• Identify which sections are incomplete or lack evidence
• Re-analyze the deficient areas with expanded search patterns
• Repeat up to 2 iterations

IF STILL INCOMPLETE after 2 iterations:

• Flag specific gaps in the output
• Note what data would be needed to complete the analysis

============================================================ OUTPUT

Growth Audit Report (AARRR Framework)

Product: {product name}

Platform: {web/mobile/desktop}

Stage: {pre-launch/early/growth/mature}

Review Date: {date}

---

Funnel Health Summary

Stage	Score (1-5)	Key Finding	Biggest Gap
Acquisition	{n}/5	{one-line}	{gap}
Activation	{n}/5	{one-line}	{gap}
Retention	{n}/5	{one-line}	{gap}
Revenue	{n}/5	{one-line}	{gap}
Referral	{n}/5	{one-line}	{gap}
Overall	{avg}/5	{assessment}	{priority}

---

Acquisition Audit

{Detailed findings from Phase 2}

Activation Audit

{Detailed findings from Phase 3}

Retention Audit

{Detailed findings from Phase 4}

Revenue Audit

{Detailed findings from Phase 5}

Referral Audit

{Detailed findings from Phase 6}

---

Growth Priorities (Ranked by Impact)

Focus on the weakest funnel stage first -- there is no point driving acquisition if activation is broken, or optimizing retention if users cannot sign up.

#	Action	AARRR Stage	Effort	Expected Impact	Priority
1	{specific action}	{stage}	{days/weeks}	{metric improvement}	P0
2	{specific action}	{stage}	{days/weeks}	{metric improvement}	P0
3	{specific action}	{stage}	{days/weeks}	{metric improvement}	P1
4	{specific action}	{stage}	{days/weeks}	{metric improvement}	P1
5	{specific action}	{stage}	{days/weeks}	{metric improvement}	P2

Quick Wins (< 1 day of work each)

{List 3-5 small changes that would have immediate growth impact. Be specific: "Add og:image tag to /pricing page" not "Improve SEO."}

Growth Metrics to Track

{List the 5-7 metrics the team should instrument and monitor, with specific events to track in the analytics tool.}

---

DO NOT:

• Recommend growth tactics that do not apply to the product type (e.g., SEO for a CLI tool).
• Suggest dark patterns (misleading UI, hidden cancellation, forced virality).
• Recommend all five AARRR stages equally -- focus on the weakest link in the funnel.
• Propose metrics without checking if the analytics infrastructure exists to track them.
• Ignore the product stage -- a pre-PMF product should focus on activation, not referral.
• Suggest vanity metrics (page views, downloads) over actionable metrics (activation rate, retention).

NEXT STEPS:

• "Run /seo to deep-dive into technical SEO if acquisition gaps were found."
• "Run /ux to audit the user journeys where friction was identified."
• "Run /iterate to implement the P0 growth priorities."
• "Run /sales-readiness if B2B growth and enterprise sales are relevant."

============================================================ SELF-EVOLUTION TELEMETRY

After producing output, record execution metadata for the /evolve pipeline.

Check if a project memory directory exists:

• Look for the project path in ~/.claude/projects/
• If found, append to skill-telemetry.md in that memory directory

Entry format:

### /growth-audit — {{YYYY-MM-DD}}
- Outcome: {{SUCCESS | PARTIAL | FAILED}}
- Self-healed: {{yes — what was healed | no}}
- Iterations used: {{N}} / {{N max}}
- Bottleneck: {{phase that struggled or "none"}}
- Suggestion: {{one-line improvement idea for /evolve, or "none"}}

Only log if the memory directory exists. Skip silently if not found. Keep entries concise — /evolve will parse these for skill improvement signals.