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

Install dependencies:
```
brew install curl jq
```
Run health check:
```
reddit.sh diagnose
```
— verifies curl, jq, network connectivity
The script auto-creates
```
.reddit/
```
with
```
reports/
```
,
```
opportunities/
```
,
```
archive/
```
Verify
```
.gitignore
```
includes
```
.reddit/
```
— the script warns if missing
Review
```
references/subreddits.json
```
— confirm subreddits match the user's domain
Review
```
references/intent_keywords.json
```
— adjust if the user targets a specific niche

First scan:

bash

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

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

Core Workflow

Phase 1: Data Collection

Run

reddit.sh fetch

for each campaign defined in

references/subreddits.json

, ordered by

scan_priority

bash

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

Phase 2: Analysis (Claude)

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

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

Phase 3: Deep Verification (score >= 8)

For opportunities scoring 8 or above:

Fetch comment trees:

reddit.sh comments <post_id> <subreddit>

Search competitive landscape:

reddit.sh search "competitor alternative" --global

Add post to
```
watched_threads
```
for ongoing monitoring
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
```
Use the templates defined below

reddit.sh Reference

Mode	Usage	Purpose
fetch	`reddit.sh fetch --campaign X --sort new --pages 2`	Fetch & enrich posts
comments	`reddit.sh comments <id> <sub>`	Comment tree for deep-dive
search	`reddit.sh search "query" [--global] [--type post\|user\|subreddit]`	Reddit search
discover	`reddit.sh discover <keyword> [--method keyword\|autocomplete]`	Find new subreddits
profile	`reddit.sh profile <user> [--enrich]`	User history analysis
crosspost	`reddit.sh crosspost [--campaign X]`	Cross-poster detection
stickied	`reddit.sh stickied [subreddit]`	Stickied post mining
firehose	`reddit.sh firehose [sub1+sub2]`	Real-time comment stream
duplicates	`reddit.sh duplicates <post_id>`	Link propagation tracking
wiki	`reddit.sh wiki <sub> [page]`	Community wiki content
stats	`reddit.sh stats`	Database / state statistics
export	`reddit.sh export [--format csv\|json]`	CRM-ready export
cleanup	`reddit.sh cleanup`	Purge expired data
diagnose	`reddit.sh diagnose`	Health check (jq, dirs, state)

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

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.

Tier	Signal	Examples
1	Direct purchase intent	"willing to pay", "budget for", "take my money"
2	Active solution seeking	"looking for a tool", "switching from", "need alternative"
3	Pain expression	"frustrated with", "too expensive", "waste of time"
4	Research	"what do you use for", "best practices", "recommendations"
5	Indirect signals	Domain discussions implying unmet need

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

markdown

## 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

markdown

# 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:

Read
```
references/subreddits.json
```
(hot reload — picks up edits between cycles)
Fetch per
```
scan_priority
```
: Tier S every loop, Tier A daily, Tier B weekly
Deduplicate against
```
seen_posts
```
in
```
.reddit/.reddit.json
```
```
watch_check
```
for watched threads with new activity
```
competitor_search
```
for configured campaigns
Analyze, score, cluster new posts
Output incremental report (append to daily scan file)
Score >= 8 -> alert:
```
OPPORTUNITY: [title] (score X.X)
```
```
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:

Key	Purpose	TTL
`seen_posts`	Deduplication	30 days
`watched_threads`	Monitor for new comments	7 days default
`opportunities`	Lifecycle tracking	Permanent
`products_seen`	Known tools/competitors	Permanent
`influencers`	High-value Reddit users	Permanent
`community_overlap`	Cross-sub posting patterns	30 days
`subreddit_quality`	Hit rate per subreddit	Permanent

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

reddit

NPX Install

Tags

SKILL.md Content