Skill: yanji84/pain-point-finder (version 1.0.0)

--- 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":"🔬","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 — 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. ```bash node {baseDir}/scripts/pain-points.mjs discover --domain "<user's domain>" --limit 8 ``` Example: ```bash 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. ```bash node {baseDir}/scripts/pain-points.mjs scan \ --subreddits "<sub1>,<sub2>,<sub3>" \ --domain "<domain>" \ --days 90 \ --limit 20 ``` Example: ```bash 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: ```bash node {baseDir}/scripts/pain-points.mjs deep-dive --post <post_id> ``` Top N from scan output: ```bash node {baseDir}/scripts/pain-points.mjs deep-dive --from-scan <scan_output.json> --top 5 ``` Look at the `validationStrength` field: - **strong**: widespread, validated pain (agreementRatio > 0.20, 10+ agreements) - **moderate**: notable pain with some validation - **weak**: some signal but limited agreement - **anecdotal**: one person's complaint, needs more evidence ### 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 - Start broad with `--days 90` then narrow to `--days 30` for recent trends - High `num_comments` + high `score` = validated pain (many people agree) - High `painScore` + low `num_comments` = niche pain (worth investigating) - The `mentionedTools` in deep-dive output maps the competitive landscape - Posts with `validationStrength: "strong"` are the best startup candidates


Security scan verdicts — ClawScan: clean | static analysis: clean | VirusTotal: clean | SkillSpector: clean (LOW)