- Add date_added to all 950+ skills for complete tracking - Update version to 6.5.0 in package.json and README - Regenerate all indexes and catalog - Sync all generated files Features from merged PR #150: - Stars/Upvotes system for community-driven discovery - Auto-update mechanism via START_APP.bat - Interactive Prompt Builder - Date tracking badges - Smart auto-categorization All skills validated and indexed. Made-with: Cursor
423 lines
14 KiB
Markdown
423 lines
14 KiB
Markdown
---
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name: last30days
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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."
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risk: unknown
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source: community
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date_added: "2026-02-27"
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---
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# last30days: Research Any Topic from the Last 30 Days
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Research ANY topic across Reddit, X, and the web. Surface what people are actually discussing, recommending, and debating right now.
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Use cases:
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- **Prompting**: "photorealistic people in Nano Banana Pro", "Midjourney prompts", "ChatGPT image generation" → learn techniques, get copy-paste prompts
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- **Recommendations**: "best Claude Code skills", "top AI tools" → get a LIST of specific things people mention
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- **News**: "what's happening with OpenAI", "latest AI announcements" → current events and updates
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- **General**: any topic you're curious about → understand what the community is saying
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## CRITICAL: Parse User Intent
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Before doing anything, parse the user's input for:
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1. **TOPIC**: What they want to learn about (e.g., "web app mockups", "Claude Code skills", "image generation")
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2. **TARGET TOOL** (if specified): Where they'll use the prompts (e.g., "Nano Banana Pro", "ChatGPT", "Midjourney")
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3. **QUERY TYPE**: What kind of research they want:
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- **PROMPTING** - "X prompts", "prompting for X", "X best practices" → User wants to learn techniques and get copy-paste prompts
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- **RECOMMENDATIONS** - "best X", "top X", "what X should I use", "recommended X" → User wants a LIST of specific things
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- **NEWS** - "what's happening with X", "X news", "latest on X" → User wants current events/updates
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- **GENERAL** - anything else → User wants broad understanding of the topic
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Common patterns:
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- `[topic] for [tool]` → "web mockups for Nano Banana Pro" → TOOL IS SPECIFIED
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- `[topic] prompts for [tool]` → "UI design prompts for Midjourney" → TOOL IS SPECIFIED
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- Just `[topic]` → "iOS design mockups" → TOOL NOT SPECIFIED, that's OK
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- "best [topic]" or "top [topic]" → QUERY_TYPE = RECOMMENDATIONS
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- "what are the best [topic]" → QUERY_TYPE = RECOMMENDATIONS
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**IMPORTANT: Do NOT ask about target tool before research.**
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- If tool is specified in the query, use it
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- If tool is NOT specified, run research first, then ask AFTER showing results
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**Store these variables:**
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- `TOPIC = [extracted topic]`
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- `TARGET_TOOL = [extracted tool, or "unknown" if not specified]`
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- `QUERY_TYPE = [RECOMMENDATIONS | NEWS | HOW-TO | GENERAL]`
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---
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## Setup Check
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The skill works in three modes based on available API keys:
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1. **Full Mode** (both keys): Reddit + X + WebSearch - best results with engagement metrics
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2. **Partial Mode** (one key): Reddit-only or X-only + WebSearch
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3. **Web-Only Mode** (no keys): WebSearch only - still useful, but no engagement metrics
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**API keys are OPTIONAL.** The skill will work without them using WebSearch fallback.
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### First-Time Setup (Optional but Recommended)
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If the user wants to add API keys for better results:
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```bash
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mkdir -p ~/.config/last30days
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cat > ~/.config/last30days/.env << 'ENVEOF'
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# last30days API Configuration
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# Both keys are optional - skill works with WebSearch fallback
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# For Reddit research (uses OpenAI's web_search tool)
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OPENAI_API_KEY=
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# For X/Twitter research (uses xAI's x_search tool)
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XAI_API_KEY=
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ENVEOF
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chmod 600 ~/.config/last30days/.env
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echo "Config created at ~/.config/last30days/.env"
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echo "Edit to add your API keys for enhanced research."
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```
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**DO NOT stop if no keys are configured.** Proceed with web-only mode.
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---
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## Research Execution
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**IMPORTANT: The script handles API key detection automatically.** Run it and check the output to determine mode.
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**Step 1: Run the research script**
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```bash
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python3 ~/.claude/skills/last30days/scripts/last30days.py "$ARGUMENTS" --emit=compact 2>&1
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```
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The script will automatically:
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- Detect available API keys
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- Show a promo banner if keys are missing (this is intentional marketing)
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- Run Reddit/X searches if keys exist
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- Signal if WebSearch is needed
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**Step 2: Check the output mode**
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The script output will indicate the mode:
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- **"Mode: both"** or **"Mode: reddit-only"** or **"Mode: x-only"**: Script found results, WebSearch is supplementary
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- **"Mode: web-only"**: No API keys, Claude must do ALL research via WebSearch
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**Step 3: Do WebSearch**
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For **ALL modes**, do WebSearch to supplement (or provide all data in web-only mode).
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Choose search queries based on QUERY_TYPE:
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**If RECOMMENDATIONS** ("best X", "top X", "what X should I use"):
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- Search for: `best {TOPIC} recommendations`
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- Search for: `{TOPIC} list examples`
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- Search for: `most popular {TOPIC}`
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- Goal: Find SPECIFIC NAMES of things, not generic advice
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**If NEWS** ("what's happening with X", "X news"):
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- Search for: `{TOPIC} news 2026`
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- Search for: `{TOPIC} announcement update`
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- Goal: Find current events and recent developments
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**If PROMPTING** ("X prompts", "prompting for X"):
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- Search for: `{TOPIC} prompts examples 2026`
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- Search for: `{TOPIC} techniques tips`
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- Goal: Find prompting techniques and examples to create copy-paste prompts
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**If GENERAL** (default):
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- Search for: `{TOPIC} 2026`
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- Search for: `{TOPIC} discussion`
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- Goal: Find what people are actually saying
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For ALL query types:
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- **USE THE USER'S EXACT TERMINOLOGY** - don't substitute or add tech names based on your knowledge
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- If user says "ChatGPT image prompting", search for "ChatGPT image prompting"
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- Do NOT add "DALL-E", "GPT-4o", or other terms you think are related
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- Your knowledge may be outdated - trust the user's terminology
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- EXCLUDE reddit.com, x.com, twitter.com (covered by script)
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- INCLUDE: blogs, tutorials, docs, news, GitHub repos
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- **DO NOT output "Sources:" list** - this is noise, we'll show stats at the end
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**Step 3: Wait for background script to complete**
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Use TaskOutput to get the script results before proceeding to synthesis.
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**Depth options** (passed through from user's command):
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- `--quick` → Faster, fewer sources (8-12 each)
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- (default) → Balanced (20-30 each)
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- `--deep` → Comprehensive (50-70 Reddit, 40-60 X)
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---
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## Judge Agent: Synthesize All Sources
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**After all searches complete, internally synthesize (don't display stats yet):**
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The Judge Agent must:
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1. Weight Reddit/X sources HIGHER (they have engagement signals: upvotes, likes)
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2. Weight WebSearch sources LOWER (no engagement data)
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3. Identify patterns that appear across ALL three sources (strongest signals)
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4. Note any contradictions between sources
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5. Extract the top 3-5 actionable insights
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**Do NOT display stats here - they come at the end, right before the invitation.**
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---
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## FIRST: Internalize the Research
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**CRITICAL: Ground your synthesis in the ACTUAL research content, not your pre-existing knowledge.**
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Read the research output carefully. Pay attention to:
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- **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)
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- **Specific quotes and insights** from the sources - use THESE, not generic knowledge
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- **What the sources actually say**, not what you assume the topic is about
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**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.
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### If QUERY_TYPE = RECOMMENDATIONS
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**CRITICAL: Extract SPECIFIC NAMES, not generic patterns.**
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When user asks "best X" or "top X", they want a LIST of specific things:
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- Scan research for specific product names, tool names, project names, skill names, etc.
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- Count how many times each is mentioned
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- Note which sources recommend each (Reddit thread, X post, blog)
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- List them by popularity/mention count
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**BAD synthesis for "best Claude Code skills":**
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> "Skills are powerful. Keep them under 500 lines. Use progressive disclosure."
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**GOOD synthesis for "best Claude Code skills":**
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> "Most mentioned skills: /commit (5 mentions), remotion skill (4x), git-worktree (3x), /pr (3x). The Remotion announcement got 16K likes on X."
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### For all QUERY_TYPEs
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Identify from the ACTUAL RESEARCH OUTPUT:
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- **PROMPT FORMAT** - Does research recommend JSON, structured params, natural language, keywords? THIS IS CRITICAL.
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- The top 3-5 patterns/techniques that appeared across multiple sources
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- Specific keywords, structures, or approaches mentioned BY THE SOURCES
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- Common pitfalls mentioned BY THE SOURCES
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**If research says "use JSON prompts" or "structured prompts", you MUST deliver prompts in that format later.**
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---
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## THEN: Show Summary + Invite Vision
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**CRITICAL: Do NOT output any "Sources:" lists. The final display should be clean.**
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**Display in this EXACT sequence:**
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**FIRST - What I learned (based on QUERY_TYPE):**
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**If RECOMMENDATIONS** - Show specific things mentioned:
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```
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🏆 Most mentioned:
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1. [Specific name] - mentioned {n}x (r/sub, @handle, blog.com)
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2. [Specific name] - mentioned {n}x (sources)
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3. [Specific name] - mentioned {n}x (sources)
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4. [Specific name] - mentioned {n}x (sources)
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5. [Specific name] - mentioned {n}x (sources)
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Notable mentions: [other specific things with 1-2 mentions]
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```
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**If PROMPTING/NEWS/GENERAL** - Show synthesis and patterns:
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```
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What I learned:
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[2-4 sentences synthesizing key insights FROM THE ACTUAL RESEARCH OUTPUT.]
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KEY PATTERNS I'll use:
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1. [Pattern from research]
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2. [Pattern from research]
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3. [Pattern from research]
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```
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**THEN - Stats (right before invitation):**
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For **full/partial mode** (has API keys):
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```
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---
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✅ All agents reported back!
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├─ 🟠 Reddit: {n} threads │ {sum} upvotes │ {sum} comments
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├─ 🔵 X: {n} posts │ {sum} likes │ {sum} reposts
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├─ 🌐 Web: {n} pages │ {domains}
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└─ Top voices: r/{sub1}, r/{sub2} │ @{handle1}, @{handle2} │ {web_author} on {site}
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```
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For **web-only mode** (no API keys):
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```
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---
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✅ Research complete!
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├─ 🌐 Web: {n} pages │ {domains}
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└─ Top sources: {author1} on {site1}, {author2} on {site2}
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💡 Want engagement metrics? Add API keys to ~/.config/last30days/.env
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- OPENAI_API_KEY → Reddit (real upvotes & comments)
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- XAI_API_KEY → X/Twitter (real likes & reposts)
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```
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**LAST - Invitation:**
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```
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---
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Share your vision for what you want to create and I'll write a thoughtful prompt you can copy-paste directly into {TARGET_TOOL}.
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```
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**Use real numbers from the research output.** The patterns should be actual insights from the research, not generic advice.
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**SELF-CHECK before displaying**: Re-read your "What I learned" section. Does it match what the research ACTUALLY says? If the research was about ClawdBot (a self-hosted AI agent), your summary should be about ClawdBot, not Claude Code. If you catch yourself projecting your own knowledge instead of the research, rewrite it.
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**IF TARGET_TOOL is still unknown after showing results**, ask NOW (not before research):
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```
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What tool will you use these prompts with?
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Options:
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1. [Most relevant tool based on research - e.g., if research mentioned Figma/Sketch, offer those]
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2. Nano Banana Pro (image generation)
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3. ChatGPT / Claude (text/code)
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4. Other (tell me)
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```
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**IMPORTANT**: After displaying this, WAIT for the user to respond. Don't dump generic prompts.
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---
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## WAIT FOR USER'S VISION
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After showing the stats summary with your invitation, **STOP and wait** for the user to tell you what they want to create.
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When they respond with their vision (e.g., "I want a landing page mockup for my SaaS app"), THEN write a single, thoughtful, tailored prompt.
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---
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## WHEN USER SHARES THEIR VISION: Write ONE Perfect Prompt
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Based on what they want to create, write a **single, highly-tailored prompt** using your research expertise.
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### CRITICAL: Match the FORMAT the research recommends
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**If research says to use a specific prompt FORMAT, YOU MUST USE THAT FORMAT:**
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- Research says "JSON prompts" → Write the prompt AS JSON
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- Research says "structured parameters" → Use structured key: value format
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- Research says "natural language" → Use conversational prose
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- Research says "keyword lists" → Use comma-separated keywords
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**ANTI-PATTERN**: Research says "use JSON prompts with device specs" but you write plain prose. This defeats the entire purpose of the research.
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### Output Format:
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```
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Here's your prompt for {TARGET_TOOL}:
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---
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[The actual prompt IN THE FORMAT THE RESEARCH RECOMMENDS - if research said JSON, this is JSON. If research said natural language, this is prose. Match what works.]
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---
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This uses [brief 1-line explanation of what research insight you applied].
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```
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### Quality Checklist:
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- [ ] **FORMAT MATCHES RESEARCH** - If research said JSON/structured/etc, prompt IS that format
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- [ ] Directly addresses what the user said they want to create
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- [ ] Uses specific patterns/keywords discovered in research
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- [ ] Ready to paste with zero edits (or minimal [PLACEHOLDERS] clearly marked)
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- [ ] Appropriate length and style for TARGET_TOOL
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---
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## IF USER ASKS FOR MORE OPTIONS
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Only if they ask for alternatives or more prompts, provide 2-3 variations. Don't dump a prompt pack unless requested.
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---
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## AFTER EACH PROMPT: Stay in Expert Mode
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After delivering a prompt, offer to write more:
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> Want another prompt? Just tell me what you're creating next.
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---
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## CONTEXT MEMORY
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For the rest of this conversation, remember:
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- **TOPIC**: {topic}
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- **TARGET_TOOL**: {tool}
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- **KEY PATTERNS**: {list the top 3-5 patterns you learned}
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- **RESEARCH FINDINGS**: The key facts and insights from the research
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**CRITICAL: After research is complete, you are now an EXPERT on this topic.**
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When the user asks follow-up questions:
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- **DO NOT run new WebSearches** - you already have the research
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- **Answer from what you learned** - cite the Reddit threads, X posts, and web sources
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- **If they ask for a prompt** - write one using your expertise
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- **If they ask a question** - answer it from your research findings
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Only do new research if the user explicitly asks about a DIFFERENT topic.
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---
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## Output Summary Footer (After Each Prompt)
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After delivering a prompt, end with:
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For **full/partial mode**:
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```
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---
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📚 Expert in: {TOPIC} for {TARGET_TOOL}
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📊 Based on: {n} Reddit threads ({sum} upvotes) + {n} X posts ({sum} likes) + {n} web pages
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Want another prompt? Just tell me what you're creating next.
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```
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For **web-only mode**:
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```
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---
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📚 Expert in: {TOPIC} for {TARGET_TOOL}
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📊 Based on: {n} web pages from {domains}
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Want another prompt? Just tell me what you're creating next.
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💡 Unlock Reddit & X data: Add API keys to ~/.config/last30days/.env
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```
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## When to Use
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This skill is applicable to execute the workflow or actions described in the overview.
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