Find relevant community threads (Reddit, Hacker News, ProductHunt) and draft contextual, value-first responses. NOT spam — genuine helpful answers that naturally mention the product.
\nweb_search(query, engines, include_raw_content) — search Reddit, HN, webweb_extract(url, size, page) — read one thread or article as clean markdownkb_search(query) — find related methodologyproject_info(name) — get project detailsIf MCP tools are not available, use WebSearch/WebFetch as fallback.
\nParse project from $ARGUMENTS.
Extract search keywords:
\nSearch communities (run searches in parallel):
\nFor each keyword group, search via MCP web_search(query) or WebSearch:
\"{problem} reddit\" — pain point threads\"{solution category} recommendations reddit\" — recommendation requests\"{competitor} alternative reddit\" — competitor frustration\"{competitor} vs reddit\" — comparison threadsFor each result, extract: subreddit, title, URL, post date, comment count.\nFilter: prefer threads < 6 months old, > 5 comments (active).
\nSearch via site:news.ycombinator.com:
\"Show HN: {similar product category}\" — similar launches\"Ask HN: {problem domain}\" — questions in the space\"{competitor name} site:news.ycombinator.com\" — competitor mentionsExtract: title, URL, points, comment count.
\nSearch via site:producthunt.com:
\"{product category} site:producthunt.com\" — similar launches\"{competitor} site:producthunt.com\" — competitor pagesExtract: product names, launch dates, upvote counts, taglines.
\nsite:indiehackers.com \"{problem}\" — Indie Hackerssite:dev.to \"{solution category}\" — Dev.to (if technical product)Forced reasoning — outreach strategy:\nBefore drafting, write out:
\nDraft responses for top 5 threads:
\nFor each thread:
\n### Thread: {title}\n**URL:** {url}\n**Subreddit/Community:** {community}\n**Why relevant:** {1 sentence}\n\n**Draft response:**\n{2-4 paragraph response that:\n- Directly addresses the question/problem\n- Provides genuine value (tips, experience, data)\n- Mentions the product naturally (last paragraph)\n- Includes \"disclaimer: I'm the developer\" for transparency\n}\nGenerate ProductHunt launch checklist:
\n## ProductHunt Launch Checklist\n\n### Pre-Launch (1 week before)\n- [ ] Hunter identified (or self-hunting)\n- [ ] Tagline ready (< 60 chars): \"{tagline}\"\n- [ ] Description ready (< 260 chars)\n- [ ] 5+ screenshots/GIF prepared\n- [ ] Maker comment drafted (story + problem + solution)\n- [ ] Launch day scheduled (Tuesday-Thursday, 00:01 PST)\n\n### Launch Day\n- [ ] Post live and verified\n- [ ] Maker comment posted immediately\n- [ ] Share in relevant communities (not vote-begging)\n- [ ] Respond to all comments within 1 hour\n- [ ] Share progress on Twitter/LinkedIn\n\n### Post-Launch\n- [ ] Thank supporters\n- [ ] Collect feedback from comments\n- [ ] Update product based on feedback\nWrite outreach plan to docs/outreach-plan.md:
# Community Outreach Plan: {Project Name}\n\n**Generated:** {YYYY-MM-DD}\n**Product:** {one-line description}\n**ICP:** {target persona}\n\n## Target Communities\n\n| Community | Relevant Threads Found | Priority |\n|-----------|----------------------|----------|\n| r/{subreddit} | N | high/medium/low |\n| Hacker News | N | high/medium/low |\n| ProductHunt | N | high/medium/low |\n\n## Top Threads to Engage\n\n{5 thread drafts from step 5}\n\n## ProductHunt Launch Checklist\n\n{checklist from step 6}\n\n## Search Keywords Used\n- {keyword1}: N results\n- {keyword2}: N results\n\n---\n*Generated by /community-outreach. Review all drafts before posting.*\nOutput summary — communities found, top 3 threads to engage, PH readiness.
\nCause: MCP web_search tool not configured or WebSearch not accessible.\nFix: Use WebSearch/WebFetch as primary. For better results with engine routing (Reddit, HN), set up SearXNG (private, self-hosted, free) and configure solograph MCP.
\nCause: Niche too small or wrong keywords.\nFix: Broaden search terms. Try competitor names, problem descriptions, or adjacent categories.
\nCause: Product mention too prominent or lacks genuine value.\nFix: Rewrite with value-first approach: 80% helpful answer, 20% product mention. Always include builder disclosure.
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