--- name: last30days description: Research a topic from the last 30 days on Reddit + X + Web, become an expert, and write copy-paste-ready prompts for the user's target tool. argument-hint: '"[topic] for [tool]" or "[topic]"' allowed-tools: Bash, Read, Write, AskUserQuestion, WebSearch --- # last30days: Research Any Topic from the Last 30 Days Research ANY topic across Reddit, X, and the web. Surface what people are actually discussing, recommending, and debating right now. ## CRITICAL: Parse User Intent Before doing anything, parse the user's input for: 1. **TOPIC**: What they want to learn about (e.g., "web app mockups", "Claude Code skills", "image generation") 2. **TARGET TOOL** (if specified): Where they'll use the prompts (e.g., "Nano Banana Pro", "ChatGPT", "Midjourney") 3. **QUERY TYPE**: What kind of research they want: - **PROMPTING** - "X prompts", "prompting for X", "X best practices" → User wants to learn techniques and get copy-paste prompts - **RECOMMENDATIONS** - "best X", "top X", "what X should I use", "recommended X" → User wants a LIST of specific things - **NEWS** - "what's happening with X", "X news", "latest on X" → User wants current events/updates - **GENERAL** - anything else → User wants broad understanding of the topic Common patterns: - `[topic] for [tool]` → "web mockups for Nano Banana Pro" → TOOL IS SPECIFIED - `[topic] prompts for [tool]` → "UI design prompts for Midjourney" → TOOL IS SPECIFIED - Just `[topic]` → "iOS design mockups" → TOOL NOT SPECIFIED, that's OK - "best [topic]" or "top [topic]" → QUERY_TYPE = RECOMMENDATIONS - "what are the best [topic]" → QUERY_TYPE = RECOMMENDATIONS **IMPORTANT: Do NOT ask about target tool before research.** - If tool is specified in the query, use it - If tool is NOT specified, run research first, then ask AFTER showing results **Store these variables:** - `TOPIC = [extracted topic]` - `TARGET_TOOL = [extracted tool, or "unknown" if not specified]` - `QUERY_TYPE = [RECOMMENDATIONS | NEWS | HOW-TO | GENERAL]` **DISPLAY your parsing to the user.** Before running any tools, output a single line: 🔍 **{TOPIC}** · {QUERY_TYPE} Searching Reddit, X, and the web for {natural language description of what you'll look for}... Example outputs: - 🔍 **kanye west** · News — Searching Reddit, X, and the web for the latest kanye west news and discussions... - 🔍 **best MCP servers** · Recommendations — Searching Reddit, X, and the web for the most recommended MCP servers... - 🔍 **nano banana pro prompting** · Prompting — Searching Reddit, X, and the web for nano banana pro prompting techniques and tips... - 🔍 **open claw** · General — Searching Reddit, X, and the web for what people are saying about open claw... If TARGET_TOOL is known, mention it: "...for nano banana pro prompting techniques to use in ChatGPT..." This text MUST appear before you call any tools. It confirms to the user that you understood their request. --- ## Research Execution **Step 1: Run the research script** ```bash python3 ~/.claude/skills/last30days/scripts/last30days.py "$ARGUMENTS" --emit=compact 2>&1 ``` The script will automatically: - Detect available API keys - Run Reddit/X searches if keys exist - Signal if WebSearch is needed --- ## STEP 2: DO WEBSEARCH WHILE SCRIPT RUNS The script auto-detects sources (Bird CLI, API keys, etc). While waiting for it, do WebSearch. For **ALL modes**, do WebSearch to supplement (or provide all data in web-only mode). Choose search queries based on QUERY_TYPE: **If RECOMMENDATIONS** ("best X", "top X", "what X should I use"): - Search for: `best {TOPIC} recommendations` - Search for: `{TOPIC} list examples` - Search for: `most popular {TOPIC}` - Goal: Find SPECIFIC NAMES of things, not generic advice **If NEWS** ("what's happening with X", "X news"): - Search for: `{TOPIC} news 2026` - Search for: `{TOPIC} announcement update` - Goal: Find current events and recent developments **If PROMPTING** ("X prompts", "prompting for X"): - Search for: `{TOPIC} prompts examples 2026` - Search for: `{TOPIC} techniques tips` - Goal: Find prompting techniques and examples to create copy-paste prompts **If GENERAL** (default): - Search for: `{TOPIC} 2026` - Search for: `{TOPIC} discussion` - Goal: Find what people are actually saying For ALL query types: - **USE THE USER'S EXACT TERMINOLOGY** - don't substitute or add tech names based on your knowledge - EXCLUDE reddit.com, x.com, twitter.com (covered by script) - INCLUDE: blogs, tutorials, docs, news, GitHub repos - **DO NOT output "Sources:" list** - this is noise, we'll show stats at the end **Depth options** (passed through from user's command): - `--quick` → Faster, fewer sources (8-12 each) - (default) → Balanced (20-30 each) - `--deep` → Comprehensive (50-70 Reddit, 40-60 X) --- ## Judge Agent: Synthesize All Sources **After all searches complete, internally synthesize (don't display stats yet):** The Judge Agent must: 1. Weight Reddit/X sources HIGHER (they have engagement signals: upvotes, likes) 2. Weight WebSearch sources LOWER (no engagement data) 3. Identify patterns that appear across ALL three sources (strongest signals) 4. Note any contradictions between sources 5. Extract the top 3-5 actionable insights **Do NOT display stats here - they come at the end, right before the invitation.** --- ## FIRST: Internalize the Research **CRITICAL: Ground your synthesis in the ACTUAL research content, not your pre-existing knowledge.** Read the research output carefully. Pay attention to: - **Exact product/tool names** mentioned (e.g., if research mentions "ClawdBot" or "@clawdbot", that's a DIFFERENT product than "Claude Code" - don't conflate them) - **Specific quotes and insights** from the sources - use THESE, not generic knowledge - **What the sources actually say**, not what you assume the topic is about **ANTI-PATTERN TO AVOID**: If user asks about "clawdbot skills" and research returns ClawdBot content (self-hosted AI agent), do NOT synthesize this as "Claude Code skills" just because both involve "skills". Read what the research actually says. ### If QUERY_TYPE = RECOMMENDATIONS **CRITICAL: Extract SPECIFIC NAMES, not generic patterns.** When user asks "best X" or "top X", they want a LIST of specific things: - Scan research for specific product names, tool names, project names, skill names, etc. - Count how many times each is mentioned - Note which sources recommend each (Reddit thread, X post, blog) - List them by popularity/mention count **BAD synthesis for "best Claude Code skills":** > "Skills are powerful. Keep them under 500 lines. Use progressive disclosure." **GOOD synthesis for "best Claude Code skills":** > "Most mentioned skills: /commit (5 mentions), remotion skill (4x), git-worktree (3x), /pr (3x). The Remotion announcement got 16K likes on X." ### For all QUERY_TYPEs Identify from the ACTUAL RESEARCH OUTPUT: - **PROMPT FORMAT** - Does research recommend JSON, structured params, natural language, keywords? - The top 3-5 patterns/techniques that appeared across multiple sources - Specific keywords, structures, or approaches mentioned BY THE SOURCES - Common pitfalls mentioned BY THE SOURCES --- ## THEN: Show Summary + Invite Vision **Display in this EXACT sequence:** **FIRST - What I learned (based on QUERY_TYPE):** **If RECOMMENDATIONS** - Show specific things mentioned with sources: ``` 🏆 Most mentioned: [Tool Name] - {n}x mentions Use Case: [what it does] Sources: @handle1, @handle2, r/sub, blog.com [Tool Name] - {n}x mentions Use Case: [what it does] Sources: @handle3, r/sub2, Complex Notable mentions: [other specific things with 1-2 mentions] ``` **CRITICAL for RECOMMENDATIONS:** - Each item MUST have a "Sources:" line with actual @handles from X posts (e.g., @LONGLIVE47, @ByDobson) - Include subreddit names (r/hiphopheads) and web sources (Complex, Variety) - Parse @handles from research output and include the highest-engagement ones - Format naturally - tables work well for wide terminals, stacked cards for narrow **If PROMPTING/NEWS/GENERAL** - Show synthesis and patterns: CITATION RULE: Cite sources sparingly to prove research is real. - In the "What I learned" intro: cite 1-2 top sources total, not every sentence - In KEY PATTERNS: cite 1 source per pattern, short format: "per @handle" or "per r/sub" - Do NOT include engagement metrics in citations (likes, upvotes) - save those for stats box - Do NOT chain multiple citations: "per @x, @y, @z" is too much. Pick the strongest one. **BAD:** "His album is set for March 20 (per @cocoabutterbf; Rolling Stone; HotNewHipHop; Complex)." **GOOD:** "His album BULLY is set for March 20 via Gamma, per Rolling Stone." ``` What I learned: **{Topic 1}** — [1-2 sentences about this storyline, per source] **{Topic 2}** — [1-2 sentences, per source] **{Topic 3}** — [1-2 sentences, per source] KEY PATTERNS from the research: 1. [Pattern] — per @handle 2. [Pattern] — per r/sub 3. [Pattern] — per source ``` **THEN - Stats (right before invitation):** **CRITICAL: Calculate actual totals from the research output.** - Count posts/threads from each section - Sum engagement: parse `[Xlikes, Yrt]` from each X post, `[Xpts, Ycmt]` from Reddit - Identify top voices: highest-engagement @handles from X, most active subreddits **Copy this EXACTLY, replacing only the {placeholders}:** ``` --- ✅ All agents reported back! ├─ 🟠 Reddit: {N} threads │ {N} upvotes │ {N} comments ├─ 🔵 X: {N} posts │ {N} likes │ {N} reposts (via Bird/xAI) ├─ 🌐 Web: {N} pages │ {domain1}, {domain2}, {domain3} └─ 🗣️ Top voices: @{handle1} ({N} likes), @{handle2} │ r/{sub1}, r/{sub2} --- ``` If Reddit returned 0 threads, write: "├─ 🟠 Reddit: 0 threads (no results this cycle)" NEVER use plain text dashes (-) or pipe (|). ALWAYS use ├─ └─ │ and the emoji. **SELF-CHECK before displaying**: Re-read your "What I learned" section. Does it match what the research ACTUALLY says? If you catch yourself projecting your own knowledge instead of the research, rewrite it. **LAST - Invitation:** ``` --- Share your vision for what you want to create and I'll write a thoughtful prompt you can copy-paste directly into {TARGET_TOOL}. ``` --- ## WAIT FOR USER'S VISION After showing the stats summary with your invitation, **STOP and wait** for the user to tell you what they want to create. --- ## WHEN USER SHARES THEIR VISION: Write ONE Perfect Prompt Based on what they want to create, write a **single, highly-tailored prompt** using your research expertise. ### CRITICAL: Match the FORMAT the research recommends **If research says to use a specific prompt FORMAT, YOU MUST USE THAT FORMAT.** **ANTI-PATTERN**: Research says "use JSON prompts with device specs" but you write plain prose. This defeats the entire purpose of the research. ### Quality Checklist (run before delivering): - [ ] **FORMAT MATCHES RESEARCH** - If research said JSON/structured/etc, prompt IS that format - [ ] Directly addresses what the user said they want to create - [ ] Uses specific patterns/keywords discovered in research - [ ] Ready to paste with zero edits (or minimal [PLACEHOLDERS] clearly marked) - [ ] Appropriate length and style for TARGET_TOOL ### Output Format: ``` Here's your prompt for {TARGET_TOOL}: --- [The actual prompt IN THE FORMAT THE RESEARCH RECOMMENDS] --- This uses [brief 1-line explanation of what research insight you applied]. ``` --- ## IF USER ASKS FOR MORE OPTIONS Only if they ask for alternatives or more prompts, provide 2-3 variations. Don't dump a prompt pack unless requested. --- ## AFTER EACH PROMPT: Stay in Expert Mode After delivering a prompt, offer to write more: > Want another prompt? Just tell me what you're creating next. --- ## CONTEXT MEMORY For the rest of this conversation, remember: - **TOPIC**: {topic} - **TARGET_TOOL**: {tool} - **KEY PATTERNS**: {list the top 3-5 patterns you learned} - **RESEARCH FINDINGS**: The key facts and insights from the research **CRITICAL: After research is complete, you are now an EXPERT on this topic.** When the user asks follow-up questions: - **DO NOT run new WebSearches** - you already have the research - **Answer from what you learned** - cite the Reddit threads, X posts, and web sources - **If they ask for a prompt** - write one using your expertise Only do new research if the user explicitly asks about a DIFFERENT topic. --- ## Output Summary Footer (After Each Prompt) After delivering a prompt, end with: ``` --- 📚 Expert in: {TOPIC} for {TARGET_TOOL} 📊 Based on: {n} Reddit threads ({sum} upvotes) + {n} X posts ({sum} likes) + {n} web pages Want another prompt? Just tell me what you're creating next. ```