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.
Use cases:
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:
**IMPORTANT: Do NOT ask about target tool before research.**
**Store these variables:**
---
Setup Check
The skill works in three modes based on available API keys:
1. **Full Mode** (both keys): Reddit + X + WebSearch - best results with engagement metrics
2. **Partial Mode** (one key): Reddit-only or X-only + WebSearch
3. **Web-Only Mode** (no keys): WebSearch only - still useful, but no engagement metrics
**API keys are OPTIONAL.** The skill will work without them using WebSearch fallback.
First-Time Setup (Optional but Recommended)
If the user wants to add API keys for better results:
```bash
mkdir -p ~/.config/last30days
cat > ~/.config/last30days/.env << 'ENVEOF'
last30days API Configuration
Both keys are optional - skill works with WebSearch fallback
For Reddit research (uses OpenAI's web_search tool)
OPENAI_API_KEY=
For X/Twitter research (uses xAI's x_search tool)
XAI_API_KEY=
ENVEOF
chmod 600 ~/.config/last30days/.env
echo "Config created at ~/.config/last30days/.env"
echo "Edit to add your API keys for enhanced research."
```
**DO NOT stop if no keys are configured.** Proceed with web-only mode.
---
Research Execution
**IMPORTANT: The script handles API key detection automatically.** Run it and check the output to determine mode.
**Step 1: Run the research script**
```bash
python3 ~/.claude/skills/last30days/scripts/last30days.py "$ARGUMENTS" --emit=compact 2>&1
```
The script will automatically:
**Step 2: Check the output mode**
The script output will indicate the mode:
**Step 3: 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"):
**If NEWS** ("what's happening with X", "X news"):
**If PROMPTING** ("X prompts", "prompting for X"):
**If GENERAL** (default):
For ALL query types:
- If user says "ChatGPT image prompting", search for "ChatGPT image prompting"
- Do NOT add "DALL-E", "GPT-4o", or other terms you think are related
- Your knowledge may be outdated - trust the user's terminology
**Step 3: Wait for background script to complete**
Use TaskOutput to get the script results before proceeding to synthesis.
**Depth options** (passed through from user's command):
---
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:
**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:
**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:
**If research says "use JSON prompts" or "structured prompts", you MUST deliver prompts in that format later.**
---
THEN: Show Summary + Invite Vision
**CRITICAL: Do NOT output any "Sources:" lists. The final display should be clean.**
**Display in this EXACT sequence:**
**FIRST - What I learned (based on QUERY_TYPE):**
**If RECOMMENDATIONS** - Show specific things mentioned:
```
🏆 Most mentioned:
1. [Specific name] - mentioned {n}x (r/sub, @handle, blog.com)
2. [Specific name] - mentioned {n}x (sources)
3. [Specific name] - mentioned {n}x (sources)
4. [Specific name] - mentioned {n}x (sources)
5. [Specific name] - mentioned {n}x (sources)
Notable mentions: [other specific things with 1-2 mentions]
```
**If PROMPTING/NEWS/GENERAL** - Show synthesis and patterns:
```
What I learned:
[2-4 sentences synthesizing key insights FROM THE ACTUAL RESEARCH OUTPUT.]
KEY PATTERNS I'll use:
1. [Pattern from research]
2. [Pattern from research]
3. [Pattern from research]
```
**THEN - Stats (right before invitation):**
For **full/partial mode** (has API keys):
```
---
✅ All agents reported back!
├─ 🟠 Reddit: {n} threads │ {sum} upvotes │ {sum} comments
├─ 🔵 X: {n} posts │ {sum} likes │ {sum} reposts
├─ 🌐 Web: {n} pages │ {domains}
└─ Top voices: r/{sub1}, r/{sub2} │ @{handle1}, @{handle2} │ {web_author} on {site}
```
For **web-only mode** (no API keys):
```
---
✅ Research complete!
├─ 🌐 Web: {n} pages │ {domains}
└─ Top sources: {author1} on {site1}, {author2} on {site2}
💡 Want engagement metrics? Add API keys to ~/.config/last30days/.env
- OPENAI_API_KEY → Reddit (real upvotes & comments)
- XAI_API_KEY → X/Twitter (real likes & reposts)
```
**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}.
```
**Use real numbers from the research output.** The patterns should be actual insights from the research, not generic advice.
**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.
**IF TARGET_TOOL is still unknown after showing results**, ask NOW (not before research):
```
What tool will you use these prompts with?
Options:
1. [Most relevant tool based on research - e.g., if research mentioned Figma/Sketch, offer those]
2. Nano Banana Pro (image generation)
3. ChatGPT / Claude (text/code)
4. Other (tell me)
```
**IMPORTANT**: After displaying this, WAIT for the user to respond. Don't dump generic prompts.
---
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 they respond with their vision (e.g., "I want a landing page mockup for my SaaS app"), THEN write a single, thoughtful, tailored prompt.
---
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.
Output Format:
```
Here's your prompt for {TARGET_TOOL}:
---
[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.]
---
This uses [brief 1-line explanation of what research insight you applied].
```
Quality Checklist:
---
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:
**CRITICAL: After research is complete, you are now an EXPERT on this topic.**
When the user asks follow-up questions:
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:
For **full/partial mode**:
```
---
📚 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.
```
For **web-only mode**:
```
---
📚 Expert in: {TOPIC} for {TARGET_TOOL}
📊 Based on: {n} web pages from {domains}
Want another prompt? Just tell me what you're creating next.
💡 Unlock Reddit & X data: Add API keys to ~/.config/last30days/.env
```