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docs/automations/greenlens-pain-mining-machine.md

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+# GreenLens Pro Pain Mining Machine
+
+## Goal
+
+Turn real plant-owner pains into content, ASO, influencer, landing page, and
+product opportunities.
+
+## Why This Exists
+
+GreenLens Pro should be driven by what users actually worry about:
+yellow leaves, brown spots, root rot, overwatering, underwatering, pests,
+curling leaves, and not knowing what to do next.
+
+## Plugins And Skills
+
+| Need | Use |
+|---|---|
+| Review/comment exports | Coupler, CSV exports, Codex |
+| App Store optimization | `app-store-aso` skill |
+| Content clustering | `content-strategy` skill |
+| Copy and hooks | `copywriting` skill |
+| Support/outreach drafting | Gmail/Fyxer plugin |
+| Product issue creation | GitHub plugin |
+
+## Data Sources
+
+Use any available source, but label the source for every pain:
+
+- App Store competitor reviews
+- Google Play competitor reviews
+- Reddit plant-care threads
+- TikTok or Instagram comments
+- Google autocomplete or People Also Ask exports
+- Support emails or user feedback
+- Existing GreenLens analytics or onboarding responses
+
+## Pain Taxonomy
+
+Cluster each item into one primary category:
+
+- Yellow leaves
+- Brown spots
+- Root rot
+- Overwatering
+- Underwatering
+- Curling leaves
+- Drooping leaves
+- Pests
+- Light problems
+- Soil and repotting
+- Beginner confusion
+- Diagnosis trust
+- Price/paywall objection
+- App usability issue
+
+## Scoring Model
+
+Score each pain from 0-100:
+
+| Factor | Weight |
+|---|---:|
+| User urgency | 30 |
+| App fit | 25 |
+| Content virality | 20 |
+| ASO/search value | 15 |
+| Product learning value | 10 |
+
+Prioritize urgent, visual, diagnosis-driven pains where GreenLens can credibly
+help the user decide what to check next.
+
+## Weekly Output
+
+Produce:
+
+1. Top 20 pains.
+2. Top 10 social hooks.
+3. Top 5 ASO keyword opportunities.
+4. Top 5 blog or landing page ideas.
+5. Top 5 product issues or feature hypotheses.
+6. Top 10 influencer angles.
+
+## Codex Pain Mining Prompt
+
+```text
+Run the GreenLens Pro Pain Mining Machine.
+
+Use:
+- docs/automations/greenlens-pain-mining-machine.md
+- app-store-aso skill
+- content-strategy skill
+
+Input source: [reviews/comments/export/pasted text]
+Market: [US / DE / global]
+Platform focus: [iOS / Android / both]
+
+Tasks:
+1. Extract raw plant-owner pains.
+2. Cluster them into the GreenLens pain taxonomy.
+3. Score each pain by urgency, app fit, virality, ASO value, and product learning.
+4. Convert winners into:
+   - social hooks
+   - ASO keyword ideas
+   - blog/landing page ideas
+   - product issues
+   - influencer outreach angles
+
+Do not invent source quotes. If evidence is weak, label it as hypothesis.
+```
+
+## Output Template
+
+```markdown
+# GreenLens Pain Mining Report
+
+## Source Summary
+
+## Top Pains
+| Rank | Pain | Source | Score | Why it matters |
+|---|---|---|---:|---|
+
+## Hook Backlog
+
+## ASO Opportunities
+
+## Product Issues
+
+## Influencer Angles
+
+## Next Actions
+```
+
+## Product Issue Template
+
+```markdown
+Title: [Feature or improvement]
+
+User pain:
+[What the user is struggling with]
+
+Hypothesis:
+If GreenLens [change], users will [outcome].
+
+Acceptance criteria:
+- [criterion]
+- [criterion]
+- [criterion]
+
+Measurement:
+- activation
+- scan completion
+- paywall conversion
+- retention
+```
+
+## Success Criteria
+
+- Every recommendation traces back to a real pain or explicitly marked hypothesis.
+- Top pains can feed both ASO and social content.
+- Product issues are concrete enough for GitHub.
+