每日IndieHackers Reddit趋势分析到Slack（Gemini AI）

• •Slack Bot Token 或 Webhook URL

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              "content": "=You are an expert analyst for startup communities who identifies hot topics, growth patterns, and actionable insights from Reddit posts, focusing on indie hackers and solopreneurs."
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              "content": "=You are given an array of Reddit posts from r/indiehackers in JSON format. Each object includes fields like title, selftext, ups, num_comments, created_utc, link_flair_text, and url. Perform a structured analysis to identify what is hot and why. Use only the provided data. Do not invent data.\n\nTasks\n\nData sanity\n\nParse the JSON array and treat each object as a post.\n\nUse these fields when available: title, selftext, ups, score, upvote_ratio, num_comments, created_utc, link_flair_text, author, subreddit_subscribers, permalink, url.\n\nIf values are null or missing, handle gracefully.\n\nHotness scoring\n\nCompute a relative Hotness Score for each post to normalize by time and engagement:\nHotness Score = (ups + 2*num_comments) * freshness_decay\nwhere freshness_decay = 1 / (1 + hours_since_post/24)\n\nIf created_utc is not comparable, assume the freshest post has hours_since_post=1 and scale others proportionally.\n\nOutput Hotness Score to one decimal place.\n\nTopic extraction\n\nExtract concise topics using title+first 500 chars of selftext.\n\nPrefer 1-5 word topics, e.g., “Mod recruitment,” “SaaS boilerplate sales,” “Competitor paywalls research,” “Cold email performance,” “Data visualization SaaS.”\n\nAssign 1–3 topics per post.\n\nTheme clustering\n\nGroup posts into higher-level themes and count frequency and total Hotness by theme.\n\nExample themes: Go-to-market tactics, Product launches, Community/Moderation, Tooling/Boilerplates, Growth/Distribution, Monetization/Pricing, Research/Validation.\n\nSignals of traction\n\nFor each post, extract any concrete traction signals (metrics, revenue, sales, subscribers, conversion, demos booked).\n\nPresent as short bullet points tied to the post.\n\nActionable insights\n\nDerive 3–7 actionable insights for indie hackers based on patterns in high-heat posts (what to build, how to launch, which channels work, what content resonates).\n\nMake each insight specific and testable (Who, What, How, Expected signal).\n\nOutput format\nReturn the following sections:\n\nHot posts (ranked)\nFor each top 5 posts by Hotness Score:\n\nRank. Title (Hotness: X.X)\n\nTopics: …\n\nFlair: …\n\nEngagement: ups=, comments=, upvote_ratio=\n\nPosted: created_utc (as UNIX)\n\nTraction signals: bullets or “None stated”\n\nLink: permalink\n\nThemes summary\n\nTheme name — posts: N, total hotness: X.X\n\nOne-line takeaway per theme\n\nWhat’s working now (actionable insights)\n\n5–7 bullets with concrete experiments\n\nEmerging opportunities\n\n3–5 bullets identifying underserved needs or repeated pain points\n\nData appendix\n\nBrief note on scoring formula and any assumptions used\n\nConstraints\n\nDo not fetch external data; analyze only provided JSON.\n\nKeep the final output under 600 words.\n\nBe concise, avoid repetition, and prefer clear, skimmable bullets.\n\nNow analyze this dataset:\n{{ JSON.stringify($json, null, 10) }}"
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        "text": "=Input\n\nposts: JSON array of Reddit posts from r/indiehackers.\n\ncontext:\n\nchannel_type: one of [company, team, project].\n\naudience: string describing who should read this.\n\ncta_link: URL for the full analysis or dashboard.\n\ntimeframe_label: human label for the period (e.g., “This week”).\n\nask_in_thread_note: short text inviting questions in thread.\n\nTasks\n\nParse and validate\n\nTreat each array element as a post.\n\nUse available fields: title, selftext, ups, num_comments, upvote_ratio, created_utc, link_flair_text, permalink, url, score, subreddit_subscribers, author.\n\nHandle nulls gracefully.\n\nScore hotness\n\nHotness = (ups + 2*num_comments) * freshness_decay\n\nfreshness_decay = 1 / (1 + hours_since_post/24)\n\nIf absolute time unavailable, scale freshness so newest post has hours_since_post=1, others proportional.\n\nRound Hotness to 1 decimal.\n\nExtract topics and traction\n\nTopics: 1–3 concise phrases (1–5 words) from title+first 500 chars of selftext.\n\nTraction: any concrete metrics (sales, revenue, demos, reply rates, etc.). If none, “None stated.”\n\nCluster into themes\n\nThemes like: Go-to-market, Product launches, Community/Moderation, Tooling/Boilerplates, Growth/Distribution, Monetization/Pricing, Research/Validation.\n\nFor each theme: count posts and sum Hotness.\n\nProduce Slack Block Kit JSON\n\nOutput MUST be a single JSON object with a top-level blocks array only (no attachments), valid per Block Kit.\n\nKeep the message compact and skimmable. Use:\n\nheader block for TL;DR headline.\n\nsection blocks with mrkdwn for summaries.\n\nfields for compact stats.\n\ncontext block for disclaimers or timestamps.\n\nactions block with one “Open Dashboard” button if cta_link provided.\n\nUse minimal, meaningful emojis (1–3 per section).\n\nInvite discussion in a thread with a short line.\n\nSlack content rules\n\nHeadline (TL;DR): bold, 1–2 emojis. Example: “🚀 Indie Hackers Trends — This Week”.\n\nCore info first: one sentence summary of the biggest takeaway this period.\n\nHot posts: top 3 posts by Hotness. Each includes title, Hotness, topics, flair, key engagement, traction, and a Reddit button.\n\nThemes summary: top 3 themes with posts count and total hotness and a one‑line takeaway.\n\nCTA: a single bold CTA to view the dashboard/report.\n\nThread prompt: “Please ask questions in the thread 👇”.\n\nInclude a small “how scored” note in context.\n\nKeep total blocks under 50; aim for brief content.\n\nRequired output schema\nReturn ONLY a JSON object with this structure:\n\n{\n\"blocks\": [\n{\n\"type\": \"header\",\n\"text\": { \"type\": \"plain_text\", \"text\": \"🚀 Indie Hackers Trends — {timeframe_label}\", \"emoji\": true }\n},\n{\n\"type\": \"section\",\n\"text\": {\n\"type\": \"mrkdwn\",\n\"text\": \"TL;DR: {single_sentence_big_takeaway}\"\n}\n},\n{\n\"type\": \"section\",\n\"fields\": [\n{ \"type\": \"mrkdwn\", \"text\": \"Audience:\\n{audience}\" },\n{ \"type\": \"mrkdwn\", \"text\": \"Posts analyzed:\\n{posts_count}\" }\n]\n},\n\ntext\n{ \"type\": \"divider\" },\n\n{\n  \"type\": \"section\",\n  \"text\": { \"type\": \"mrkdwn\", \"text\": \"*🔥 Hot Posts (Top 3)*\" }\n},\n\n// Repeat this group for up to 3 posts\n{\n  \"type\": \"section\",\n  \"text\": {\n    \"type\": \"mrkdwn\",\n    \"text\": \"*{rank}\\\\. {title}*  \\nHotness: {hotness}\"\n  }\n},\n{\n  \"type\": \"context\",\n  \"elements\": [\n    { \"type\": \"mrkdwn\", \"text\": \"*Topics:* {topics_csv}\" },\n    { \"type\": \"mrkdwn\", \"text\": \"*Flair:* {flair_or_dash}\" }\n  ]\n},\n{\n  \"type\": \"section\",\n  \"fields\": [\n    { \"type\": \"mrkdwn\", \"text\": \"*Ups:*\\n{ups_or_dash}\" },\n    { \"type\": \"mrkdwn\", \"text\": \"*Comments:*\\n{num_comments_or_dash}\" },\n    { \"type\": \"mrkdwn\", \"text\": \"*Upvote ratio:*\\n{upvote_ratio_or_dash}\" },\n    { \"type\": \"mrkdwn\", \"text\": \"*Posted (UNIX):*\\n{created_utc_or_dash}\" }\n  ]\n},\n{\n  \"type\": \"section\",\n  \"text\": { \"type\": \"mrkdwn\", \"text\": \"*Traction:*\\n{traction_bullets_or_None_stated}\" }\n},\n{\n  \"type\": \"actions\",\n  \"elements\": [\n    {\n      \"type\": \"button\",\n      \"text\": { \"type\": \"plain_text\", \"text\": \"Open Reddit\" },\n      \"url\": \"https://www.reddit.com{permalink}\"\n    }\n  ]\n},\n\n{ \"type\": \"divider\" },\n\n{\n  \"type\": \"section\",\n  \"text\": { \"type\": \"mrkdwn\", \"text\": \"*🧭 Themes Summary*\" }\n},\n\n// Up to 3 themes\n{\n  \"type\": \"section\",\n  \"text\": { \"type\": \"mrkdwn\", \"text\": \"- *{theme_name}* — posts: {n}, total hotness: {sum_hotness}  \\n_{one_line_takeaway}_\" }\n},\n\n{ \"type\": \"divider\" },\n\n{\n  \"type\": \"section\",\n  \"text\": { \"type\": \"mrkdwn\", \"text\": \"*✅ What to do now*\" }\n},\n{\n  \"type\": \"section\",\n  \"text\": { \"type\": \"mrkdwn\", \"text\": \"- {actionable_insight_1}\\n- {actionable_insight_2}\\n- {actionable_insight_3}\" }\n},\n\n{\n  \"type\": \"actions\",\n  \"elements\": [\n    {\n      \"type\": \"button\",\n      \"text\": { \"type\": \"plain_text\", \"text\": \"Open Dashboard\" },\n      \"url\": \"{cta_link}\"\n    }\n  ]\n},\n\n{\n  \"type\": \"context\",\n  \"elements\": [\n    { \"type\": \"mrkdwn\", \"text\": \"_Please ask questions in the thread 👇  -   Hotness = (ups + 2×comments) × 1/(1 + hours/24)_\" }\n  ]\n}\n]\n}\n\nConstraints\n\nOutput only the JSON object above (no extra text).\n\nUse mrkdwn and fields per Slack docs.\n\nKeep emojis purposeful and minimal.\n\nButtons must be valid Block elements.\n\nDo not exceed 50 blocks.\n\nNow analyze this dataset and produce the Slack JSON:\n\nposts: [PASTE JSON ARRAY HERE]\n\ncontext:\n{\n\"channel_type\": \"team\",\n\"audience\": \"Growth, Product, and Founders\",\n\"cta_link\": \"https://example.com/trends-dashboard\",\n\"timeframe_label\": \"This Week\",\n\"ask_in_thread_note\": \"Please ask any questions in the thread 👇\"\n}\n\n{{ JSON.stringify($json, null, 2) }}",
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