Reddit Opportunity Hunter

Mission

Product Opportunity Hunting, NOT Lead Hunting.

• Input: Reddit discussions from high-purchasing-power markets
• Output: Actionable product opportunity reports with build assessments
• Goal: Surface 1-2 week MVP opportunities in USD/EUR/GBP markets
• You are scanning for patterns of unmet need, not individual sales leads
• Every recommendation must pass the Solo Dev Fit test before being highlighted
• Reference data lives in references/ — subreddits, keywords, seasonal patterns

Quick Start / First Run

1. Install dependencies: brew install curl jq
2. Run health check: reddit.sh diagnose — verifies curl, jq, network connectivity
3. The script auto-creates .reddit/ with reports/, opportunities/, archive/
4. Verify .gitignore includes .reddit/ — the script warns if missing
5. Review references/subreddits.json — confirm subreddits match the user's domain
6. Review references/intent_keywords.json — adjust if the user targets a specific niche
7. Configure preferences: reddit.sh config show — set language, industries, currency
8. First scan:

   reddit.sh fetch --campaign global_english --sort new --pages 1
   

9. Inspect the enriched JSON output, then proceed to Phase 2 (Analysis)

Configuration

On first run, .reddit/config.json is auto-created with defaults. Check and customize it:

reddit.sh config show          # view current config
reddit.sh config set <key> <value>   # change a setting
reddit.sh config reset         # restore defaults

First-run prompt: If no config.json exists when the skill is triggered, ask the user:

"This is your first time using Reddit Opportunity Hunter. Quick setup:

1. What language should reports be in? (default: en)
2. Any industries to focus on? (default: all)
3. What currency for revenue estimates? (default: USD)

Or say 'use defaults' to skip."

Save answers via reddit.sh config set.

Core Workflow

Two modes: broad scan (default loop) or focused investigation (user asks about a specific topic).

For focused investigation (e.g., "deep-dive QuickBooks pain points"):

1. Identify the most relevant campaign(s) — match user's topic to campaigns in subreddits.json
2. Fetch those campaigns + global_english for cross-market signal
3. Run targeted searches: reddit.sh search "<topic> frustrated" --global, reddit.sh search "<topic> alternative" --global
4. Skip straight to Phase 2-3 analysis on the focused data set
5. Produce detailed opportunity reports for the specific vertical

For broad scan (loop cycle or general scan):

Phase 1: Data Collection

Run reddit.sh fetch for each campaign defined in references/subreddits.json, ordered by scan_priority:

reddit.sh fetch --campaign global_english --sort new --pages 2
reddit.sh fetch --campaign dach_german --sort new --pages 1
reddit.sh fetch --campaign nordic_scandi --sort new --pages 1

Key details:

• Multi-sub merge: the script combines subreddits as r/A+B+C/new.json to reduce API calls
• Output is enriched JSON — jq computes _jq_enriched fields (intent matches, sentiment, age)
• Do NOT re-compute what jq already provides; read the enriched fields directly
• Rate limit budget: ~100 requests per ~260 seconds; a single fetch loop uses ~40-45
• Fetch Tier S campaigns every loop, Tier A daily, Tier B weekly
• Campaign selection: when the user specifies a domain (e.g., "DevTools and marketing"), fetch matching vertical campaigns + global_english. Don't fetch all campaigns — respect the user's focus.

Phase 2: Analysis (Claude)

Before analyzing, read user config:

• reddit.sh config show — check output_language, focus_industries, score_threshold
• CRITICAL: Write ALL reports, analysis, section headers, and commentary in the configured output_language. If output_language is zh, every line of output must be Chinese (keep only numbers, scores, URLs, subreddit names, product names, and technical terms in English). This applies to every loop cycle — not just the first one.
• If focus_industries is set, prioritize opportunities matching those industries
• If excluded_subreddits is set, skip posts from those subreddits
• Use currency_display when estimating revenue (convert from USD)
• Only include opportunities with final_score >= score_threshold
• Only include opportunities with complexity ≤ max_build_complexity

Read the enriched JSON from Phase 1. For each batch:

1. Pain point clustering — group similar complaints across posts and subreddits
2. Frequency counting — how many posts mention this pain this week?
3. Intensity assessment — use intent_keywords_matched and negative_signals from the enriched data
4. Market validation signals — look for: budget mentions, team size, already_tried products, willingness to pay
5. Score each opportunity using the scoring algorithm below
6. Deduplicate against seen_posts in .reddit/.reddit.json

Phase 3: Deep Verification (score >= 8, or high-engagement posts)

Fetch comment trees for posts that meet any of these triggers:

• Opportunity score >= 8
• High engagement: >= 20 comments or >= 30 upvotes on a niche subreddit
• Tier 1-2 intent signals with specific budget mentions

For each triggered post:

1. Fetch comment trees: reddit.sh comments <post_id> <subreddit>
2. Search competitive landscape: reddit.sh search "competitor alternative" --global
3. Add post to watched_threads for ongoing monitoring
4. Optional: use WebSearch for cross-platform validation (Twitter/X, HN, G2, Capterra)

Phase 3.5: Micro-Validation

Before promoting an opportunity to "validated":

• Suggest a landing page smoke test to the user
• Cross-platform search: Twitter/X, Hacker News, Indie Hackers for the same pain
• Search for failed attempts at similar products (important signal)
• Check Product Hunt / GitHub for recent launches in the space

Phase 4: Report

• Daily scan report -> .reddit/reports/YYYY-MM-DD-scan.md
• High-value opportunities -> .reddit/opportunities/<slug>.md
• Scoring breakdown -> include a scoring-breakdown.md when producing >= 3 opportunities, showing per-dimension scores so the user can see why each opportunity ranked where it did
• Use the templates defined below

reddit.sh Reference

Helper functions (called during loop cycles, not directly by user):

• watch_check — check watched threads for new comments since last check
• competitor_search <campaign> — expand competitor query templates from config
• update_subreddit_quality <sub> <scanned> [opportunities] — track hit rates per subreddit

Discovery → Promote Pipeline

When finding new subreddits for a campaign:

1. reddit.sh discover "<keyword>" --deep — probes candidate subs (15-25 API calls per query)
2. Review discovery results — check pain_posts, avg_comments, competitor_posts
3. Quality-score each candidate using the multi-dimension algorithm (pain density, engagement, competitor mentions, growth rate, etc.)
4. For subs scoring >= sub_quality_threshold: reddit.sh promote <sub> --campaign <campaign>
5. For borderline subs (threshold - 1.0 to threshold): flag as "monitor" for re-evaluation next week

Rate limit caution: --deep discovery uses 15-25 requests per query. Run at most 2-3 discovery queries per session. If you hit 429 rate limits, stop discovery and resume in the next cycle.

Scoring Algorithm

raw_score = intensity      * 0.20
          + competitive_gap * 0.20
          + build_feasibility * 0.20
          + market_value   * 0.20
          + frequency      * 0.15
          + timeliness     * 0.05

Each dimension is scored 1-10 individually.

Adjustments:

adjusted = raw_score
  + cross_market_bonus   (same pain in 3+ Tier S markets -> +1.5)
  + seasonal_bonus       (matches upcoming seasonal pattern -> +1.0; just passed -> -1.0)
  - false_positive_penalty (see below)

final_score = clamp(adjusted, 1, 10)

Weekly decay: if no new mentions this week: final_score *= 0.88

Market tier bonuses (applied to market_value dimension, not final score):

• Tier S (US, UK, DE, FR, NL, JP, AU, KR, Nordics): +3
• Tier A (IN, BR, SEA, LATAM, PL, CZ): +1
• Tier B (Africa, South Asia, rest): +0

Thresholds:

• = 8: Deep verification (Phase 3) + highlight in report

• = 7: Show in daily report under New Opportunities

• < 7: Aggregate only under Trending Pain Points

False positive penalties:

• Single user mention, no corroboration: -3
• One-time complaint (user has no topic history): -2
• Strong open-source alternative (>5k GitHub stars): -2
• Requires enterprise sales process: mark as "not solo dev fit", do not penalize score but flag

Intent Tiers

Reference references/intent_keywords.json for the full keyword list. You classify intent tier from context — jq only provides raw keyword matches.

Solo Dev Fit Assessment

Evaluate independently of opportunity score. All must be true for a pass:

• Build time < 2 weeks for MVP
• No ongoing compliance burden (HIPAA, SOC2, etc.)
• Self-serve distribution (no enterprise sales cycle)
• Subscription or usage-based pricing model viable
• Known tech stack (no deep domain R&D)
• No network effects required for initial value

Opportunity Report Template

## Product Opportunity: [Name]

**Score:** X.X/10 | **Intent Tier:** N | **Solo Dev Fit:** Yes/No

### Pain Point
[2-3 sentence summary of the unmet need]

### Market Evidence
- **Frequency:** N posts in last 7 days across M subreddits
- **Intensity:** [low/medium/high] — key signals: ...
- **Geography:** [primary markets]
- **Target user:** [persona]
- **Budget signals:** [quotes or indicators]

### Competitive Landscape
- **Existing paid tools:** [list with pricing]
- **Open-source alternatives:** [list with GitHub stars]
- **Why they fail:** [gap analysis]
- **Recent launches:** [last 6 months]

### Build Assessment
- **Complexity:** [low/medium/high]
- **MVP scope:** [3-5 core features]
- **Build time:** [estimate]
- **Tech stack:** [recommendation]
- **Technical moat:** [if any]
- **Solo Dev Fit:** [Yes/No + reasoning]

### Revenue Model
- **Pricing anchor:** [competitor pricing context]
- **Suggested tiers:** [USD/EUR with PPP notes]
- **Distribution:** [channels]
- **Market size estimate:** [TAM/SAM]
- **Revenue potential:** [12-month projection]
- **CAC / Payback:** [estimate]
- **Churn risk:** [assessment]

### Cross-Market Signal
[Evidence from other markets/platforms]

### Source Posts
- [post title](url) — r/subreddit — N upvotes, M comments — YYYY-MM-DD

Daily Report Template

# Reddit Opportunity Scan — YYYY-MM-DD

## New Opportunities (score >= 7)
[Opportunity cards with score, pain summary, top source post]

## Trending Pain Points
[Clusters below threshold but gaining frequency]

## Time-Sensitive (< 2h old, high intent)
[Posts needing immediate attention — Tier 1-2 intent, fresh]

## Scan Stats
- Subreddits scanned: N
- Posts analyzed: N
- New opportunities: N
- Watched threads updated: N
- API calls used: N / 100

Loop Integration

Trigger with:

/loop 30m /reddit

Each cycle follows Phases 1-4 above, with these loop-specific additions:

1. Read config first: reddit.sh config show — enforce output_language for ALL output this cycle
2. Hot-reload references/subreddits.json (picks up edits and newly promoted subs between cycles)
3. Fetch per scan_priority: Tier S every loop, Tier A daily, Tier B weekly
4. Deduplicate against seen_posts in .reddit/.reddit.json
5. watch_check for watched threads with new activity
6. competitor_search for configured campaigns
7. Analyze, score, cluster → Phase 2-4 as normal
8. Score >= 8 → alert: OPPORTUNITY: [title] (score X.X)
9. update_subreddit_quality with hit rates

Scheduled reports:

• Weekly summary: trigger on Sundays (or first loop after Sunday midnight)
• Monthly summary: last day of month (or first loop after)
• If a scheduled report was missed, generate it on next run

State Management

.reddit/.reddit.json tracks:

Opportunity lifecycle: discovered -> investigating -> validated -> building -> launched -> revenue -> archived

Safety

• Public data only — no PII beyond Reddit usernames
• Rate limit compliant — respect the ~100 req/260s budget
• .reddit/ must be in .gitignore — never commit user data
• Reply drafts always marked [REVIEW BEFORE POSTING]
• Suggest max 5 replies per day to avoid spam patterns

Skill Integration

Related skills for downstream workflows:

• content-strategy — turn validated pain points into content calendars
• copywriting — turn opportunities into landing page copy
• competitor-alternatives — deep competitive analysis
• cold-email — draft outreach / DM templates
• social-content — repurpose Reddit insights for social posts