# Forum Monitor > Use when monitoring online forums (Reddit, HN, ProductHunt) for recurring user pain points, feature requests, and unmet needs. Invoke for market research, pain-point discovery, trend detection, and competitive intelligence. Designed for scheduled execution via CronCreate. - Skill: `oimiragieo/forum-monitor` (Agent Skill, multi-file: 10 files) - Install (CLI): `npx skillmds@latest add oimiragieo/forum-monitor` - Raw SKILL.md: https://api.skillmd.com/api/skills/oimiragieo/forum-monitor/raw - Safety review: pending - Works with: Claude Code, Claude.ai, OpenAI Codex - Category: Product & Planning - Author: oimiragieo (https://skillmd.com/u/oimiragieo) - Updated: 2026-09-10 - Page: https://skillmd.com/skills/oimiragieo/forum-monitor --- # Forum Monitor ## Overview Systematic workflow for monitoring online communities to discover recurring user pain points. Transforms unstructured forum discussions into ranked, evidence-backed opportunity reports suitable for automated app generation pipelines. **Core principle:** Pain points with high frequency and high engagement are the strongest product signals. Monitor, classify, rank, report. ## When to Use - Discovering product opportunities from community feedback - Running periodic (daily/weekly) market research scans - Identifying trending complaints or feature requests - Competitive intelligence gathering from user discussions - Feeding the app-generation-workflow with validated pain points ## Cron Integration This skill is designed to run on a schedule via CronCreate: ```javascript CronCreate({ name: 'weekly-forum-scan', schedule: '0 9 * * MON', // Every Monday at 9 AM prompt: 'Run forum monitor scan for [target domain]. Invoke Skill({ skill: "forum-monitor" }). Save report to .claude/context/reports/backend/', }); ``` ## Workflow ### Step 1: Configure Target Forums Define the forums to monitor based on the target domain: **Forum Selection Matrix:** | Forum | Best For | Query Pattern | | ------------- | ------------------------------- | --------------------------------------------- | | Reddit | Consumer pain points, UX issues | `site:reddit.com frustrating OR wish` | | Hacker News | Developer tools, B2B SaaS | `site:news.ycombinator.com ` | | ProductHunt | New product gaps, feature envy | `site:producthunt.com ` | | Indie Hackers | Solo dev pain points, pricing | `site:indiehackers.com ` | | Dev.to | Developer workflow friction | `site:dev.to pain OR annoy` | **Query Templates:** ``` "{topic} frustrating OR annoying OR wish OR need OR missing" "{topic} alternative to OR better than OR looking for" "{topic} feature request OR roadmap OR please add" ``` ### Step 2: Scrape and Collect For each configured forum, execute searches and extract content: ```javascript // Search for pain points WebSearch({ query: 'site:reddit.com {topic} frustrating OR wish OR need 2026' }); // Fetch specific threads with high engagement WebFetch({ url: '{thread-url}', prompt: 'Extract all complaints, feature requests, and pain points. For each, note the exact quote, upvote count, and whether others agreed.', }); ``` **Collection Requirements:** - Minimum 20 posts per forum per scan - Include posts from the last 30 days (or configurable window) - Capture: title, URL, community, engagement (upvotes + comments), date, key quotes ### Step 3: Classify Pain Points Categorize each collected item into one of these categories: | Category | Signal Words | Example | | ------------------- | --------------------------------------- | ------------------------------------ | | `missing-feature` | "wish", "need", "please add", "roadmap" | "I wish Notion had offline mode" | | `workflow-friction` | "slow", "clunky", "takes forever" | "It takes 10 clicks to export a PDF" | | `bug-report` | "broken", "crashes", "error" | "The app crashes on large files" | | `pricing` | "expensive", "not worth", "free alt" | "Too expensive for a solo dev" | | `ux-confusion` | "confusing", "can't find", "intuitive" | "I had no idea where settings were" | | `integration-gap` | "connect to", "integrate with", "API" | "No Zapier integration available" | ### Step 4: Cluster and Deduplicate Group similar pain points into clusters: 1. Exact duplicates: same complaint, different posts -> merge, sum engagement 2. Semantic duplicates: similar complaint, different wording -> cluster, note variants 3. Related but distinct: same domain, different problems -> keep separate ### Step 5: Rank by Opportunity Score For each cluster, compute: ``` Opportunity Score = (Frequency x 0.4) + (Engagement x 0.3) + (Recency x 0.2) + (Sentiment Intensity x 0.1) ``` Where: - **Frequency**: Number of unique posts mentioning this pain point (normalized 0-10) - **Engagement**: Total upvotes + comments across all posts (normalized 0-10) - **Recency**: How recent the complaints are (last 7 days = 10, last 30 days = 5, older = 2) - **Sentiment Intensity**: How strongly negative the language is (0-10) ### Step 6: Generate Report Write structured output to `.claude/context/reports/backend/forum-monitor-report-{YYYY-MM-DD}.md`: ```markdown # Forum Monitor Report **Scan Period**: {start-date} to {end-date} **Forums Monitored**: {list} **Total Posts Analyzed**: {count} **Pain Point Clusters Found**: {count} ## Top Pain Points (Ranked by Opportunity Score) | Rank | Pain Point | Category | Freq | Engagement | Score | Sources | | ---- | ---------- | -------- | ---- | ---------- | ----- | ------- | | 1 | [desc] | [cat] | [n] | [n] | [n.n] | [n] | ## Detailed Findings ### 1. [Pain Point Title] (Score: X.X) **Category**: [type] **Frequency**: [n] mentions across [n] sources **Engagement**: [total upvotes] upvotes, [total comments] comments **Forums**: [list of forums where this appeared] **Representative Quotes:** 1. "[exact quote]" - [source URL] ([n] upvotes) 2. "[exact quote]" - [source URL] ([n] upvotes) 3. "[exact quote]" - [source URL] ([n] upvotes) **App Opportunity Assessment:** - Buildable as standalone app: YES/NO - Estimated complexity: LOW/MEDIUM/HIGH - Existing solutions: [list or "none found"] - Differentiation angle: [what would make a new solution win] ``` ## Iron Laws 1. **ALWAYS cite source URLs** for every finding -- unverifiable claims are worthless 2. **NEVER fabricate engagement metrics** -- counts must come from actual collected data 3. **ALWAYS cross-reference at least 2 forums** before declaring a trend 4. **NEVER include content from private or gated forums** -- public content only 5. **ALWAYS include verbatim quotes** -- user language is more valuable than agent summaries ## Anti-Patterns | Anti-Pattern | Why It Fails | Correct Approach | | ----------------------------- | --------------------------------------------------- | --------------------------------------------- | | Single-forum reports | One community is not representative | Cross-reference 2+ forums before trending | | Subjective ranking | Personal opinion is not data | Use weighted opportunity formula | | Missing source URLs | Downstream agents cannot validate findings | Every finding must have a clickable source | | Stale data without date range | Trends from 2024 are not 2026 trends | Always specify scan period in report header | | Over-counting duplicates | Same user posting in 3 threads is not 3 data points | Deduplicate by unique user + unique complaint | ## Related Skills - `browser-automation` -- for deeper scraping when WebSearch/WebFetch are insufficient - `deep-research` -- for comprehensive investigation of specific pain points - `feedback-analysis` -- for structured sentiment and NPS analysis ## Assigned Agents | Agent | Role | | --------------------- | --------------------------------------- | | `forum-monitor-agent` | Primary -- executes the full workflow | | `researcher` | Supporting -- deeper investigation | | `app-generator-agent` | Consumer -- reads reports for app ideas | ## Memory Protocol (MANDATORY) **Before starting:** ```bash node .claude/lib/memory/memory-search.cjs "forum monitor pain points trends" ``` Read `.claude/context/memory/learnings.md` **After completing:** - New monitoring pattern -> `.claude/context/memory/learnings.md` - Forum access issue -> `.claude/context/memory/issues.md` - Scoring model decision -> `.claude/context/memory/decisions.md` > ASSUME INTERRUPTION: Your context may reset. If it's not in memory, it didn't happen.