Pain Point Finder
by @yanji84
Discover pain points, frustrations, and unmet needs on Reddit using PullPush API. No API keys required. Use to find startup ideas backed by real user complai...
clawhub install pain-point-finderπ About This Skill
name: pain-point-finder description: >- Discover pain points, frustrations, and unmet needs on Reddit using PullPush API. No API keys required. Use to find startup ideas backed by real user complaints. metadata: {"clawdbot":{"emoji":"π¬","requires":{"bins":["node"]}}}
Pain Point Finder
Discover validated pain points on Reddit. Searches for frustrations, complaints, and unmet needs, then analyzes comment threads for agreement signals and failed solutions. Powered by PullPush API β no API keys needed.
Workflow
Follow these 4 phases in order. Each phase builds on the previous.
Phase 1: Discover Subreddits
Find the right subreddits for the user's domain.
node {baseDir}/scripts/pain-points.mjs discover --domain "" --limit 8
Example:
node {baseDir}/scripts/pain-points.mjs discover --domain "project management" --limit 8
Take the top 3-5 subreddits from the output for phase 2.
Phase 2: Scan for Pain Points
Broad search across discovered subreddits.
node {baseDir}/scripts/pain-points.mjs scan \
--subreddits ",," \
--domain "" \
--days 90 \
--limit 20
Example:
node {baseDir}/scripts/pain-points.mjs scan \
--subreddits "projectmanagement,SaaS,smallbusiness" \
--domain "project management" \
--days 90 \
--limit 20
Review the scored posts. Posts with high painScore and high num_comments are the best candidates for deep analysis.
Phase 3: Deep-Dive Analysis
Analyze comment threads of top posts for agreement and solution signals.
Single post:
node {baseDir}/scripts/pain-points.mjs deep-dive --post
Top N from scan output:
node {baseDir}/scripts/pain-points.mjs deep-dive --from-scan --top 5
Look at the validationStrength field:
Phase 4: Synthesis (you do this)
For each validated pain point, present a structured proposal:
1. Problem: One-sentence description of the pain
2. Evidence: Top quotes + agreement count + subreddit
3. Who feels this: Type of person/business affected
4. Current solutions & gaps: What people have tried (from solutionAttempts) and why it fails
5. Competitive landscape: Tools mentioned (from mentionedTools)
6. Opportunity: What's missing in current solutions
7. Idea sketch: Brief product/service concept
8. Validation: strong/moderate/weak + data backing it
Options Reference
discover
| Flag | Default | Description | |------|---------|-------------| |--domain | required | Domain to explore |
| --limit | 10 | Max subreddits to return |scan
| Flag | Default | Description | |------|---------|-------------| |--subreddits | required | Comma-separated subreddit list |
| --domain | | Domain for extra search queries |
| --days | 365 | How far back to search |
| --minScore | 1 | Min post score filter |
| --minComments | 3 | Min comment count filter |
| --limit | 30 | Max posts to return |
| --pages | 2 | Pages per query (more = deeper, slower) |deep-dive
| Flag | Default | Description | |------|---------|-------------| |--post | | Single post ID or Reddit URL |
| --from-scan | | Path to scan output JSON |
| --stdin | | Read scan JSON from stdin |
| --top | 10 | How many posts to analyze from scan |
| --maxComments | 200 | Max comments to fetch per post |Rate Limits
The script self-limits to 1 request/sec, 30/min, 300/run. If PullPush is slow or returns errors, it retries with exponential backoff. Progress is logged to stderr.
Tips
--days 90 then narrow to --days 30 for recent trendsnum_comments + high score = validated pain (many people agree)painScore + low num_comments = niche pain (worth investigating)mentionedTools in deep-dive output maps the competitive landscapevalidationStrength: "strong" are the best startup candidatesπ Tips & Best Practices
--days 90 then narrow to --days 30 for recent trendsnum_comments + high score = validated pain (many people agree)painScore + low num_comments = niche pain (worth investigating)mentionedTools in deep-dive output maps the competitive landscapevalidationStrength: "strong" are the best startup candidates