ClaudeResearch

last30days

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.

31,392 stars
Complexity: easy

About this skill

The 'last30days' skill empowers AI agents to perform focused, timely research on any given topic within the past month. It meticulously scans discussions on Reddit, X (formerly Twitter), and the broader web to identify current trends, opinions, recommendations, and debates. By synthesizing this information, the skill becomes an 'expert' on the chosen subject, capable of distilling complex information into actionable insights. Its primary output is a set of optimized, copy-paste-ready prompts tailored for the user's specified AI tool (e.g., Midjourney, ChatGPT, Nano Banana Pro), making it invaluable for content creators, marketers, researchers, and anyone needing quick, relevant, and tool-specific content generation.

Best use case

Generate optimized prompts for AI image generation tools (e.g., 'photorealistic people in Nano Banana Pro', 'Midjourney prompts', 'ChatGPT image generation'). Discover trending recommendations for products, services, or tools (e.g., 'best Claude Code skills', 'top AI tools'). Stay updated on current events and announcements within specific industries or topics (e.g., 'what's happening with OpenAI', 'latest AI announcements'). Understand public sentiment and discussions around a recent event, product launch, or policy. Formulate content strategies based on what's currently resonating with online communities.

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.

A concise summary of the chosen topic, reflecting current online discussions and trends, followed by a list of high-quality, copy-paste-ready prompts specifically designed for your target AI tool to facilitate further content generation or exploration.

Practical example

Example input

Research the latest trends in 'AI video generation tools' over the last 30 days across Reddit, X, and the web. Become an expert and provide copy-paste-ready prompts for generating short, engaging marketing videos using 'RunwayML' and 'Pika Labs'.

Example output

## Latest Trends in AI Video Generation Tools (Last 30 Days)

The past month has seen significant buzz around more accessible and higher-quality AI video generation tools. Key trends include:
- **Increased Realism & Consistency**: Users are reporting better temporal consistency and less 'flickering' in generated clips, making them suitable for short-form content.
- **Integration with Other AI Tools**: Many discussions revolve around combining AI video with AI audio/music generation and advanced scripting AI for full workflow automation.
- **Focus on Marketing & Social Media**: A major use case highlighted is the creation of engaging short ads, explainers, and social media clips, especially for niche products.
- **Text-to-Video advancements**: New models are better interpreting nuanced text prompts, allowing for more creative control over style, mood, and camera angles.

### Expert-Level Prompts for RunwayML & Pika Labs:

**For RunwayML:**
*   `Prompt: A sleek, futuristic electric car accelerating through a neon-lit city at dusk. Dynamic camera angle, smooth motion blur, cinematic lighting. Style: Sci-fi commercial. Target: 15-second promo.`
*   `Prompt: Close-up of hands crafting a delicate piece of jewelry in a sun-drenched workshop. Focus on intricate details and artisan skill. Emotional, warm tone. Target: 10-second craft tutorial intro.`

**For Pika Labs:**
*   `Prompt: An animated character (friendly robot) explaining a complex concept simply, with minimalist graphics floating around it. Background: clean, bright studio. Style: Explainer video, educational. Target: 20-second educational clip.`
*   `Prompt: Fast-paced montage of diverse individuals experiencing joy outdoors – hiking, laughing, picnicking. Vibrant colors, upbeat music suggestions. Style: Lifestyle advertisement, energetic. Target: 30-second brand awareness.`

When to use this skill

  • When you need current, community-driven insights on a topic.
  • When creating content or prompts for other AI tools and want them to be highly relevant and effective.
  • When researching recent trends, opinions, or recommendations (up to 30 days old).
  • When you want to quickly become familiar with a recent development or popular discussion.

When not to use this skill

  • When the topic requires historical data or information older than 30 days.
  • For highly academic, scientific, or deeply specialized research that requires peer-reviewed sources exclusively.
  • For real-time breaking news that might change minute-by-minute, as the 'last 30 days' focus implies a slight delay.
  • When the information needs to be sourced solely from proprietary or private databases.

Installation

Claude Code / Cursor / Codex

$curl -o ~/.claude/skills/last30days/SKILL.md --create-dirs "https://raw.githubusercontent.com/sickn33/antigravity-awesome-skills/main/plugins/antigravity-awesome-skills-claude/skills/last30days/SKILL.md"

Manual Installation

  1. Download SKILL.md from GitHub
  2. Place it in .claude/skills/last30days/SKILL.md inside your project
  3. Restart your AI agent — it will auto-discover the skill

How last30days Compares

Feature / Agentlast30daysStandard Approach
Platform SupportClaudeLimited / Varies
Context Awareness High Baseline
Installation ComplexityeasyN/A

Frequently Asked Questions

What does this skill do?

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.

Which AI agents support this skill?

This skill is designed for Claude.

How difficult is it to install?

The installation complexity is rated as easy. You can find the installation instructions above.

Where can I find the source code?

You can find the source code on GitHub using the link provided at the top of the page.

Related Guides

SKILL.md Source

# 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:

- **Prompting**: "photorealistic people in Nano Banana Pro", "Midjourney prompts", "ChatGPT image generation" → learn techniques, get copy-paste prompts
- **Recommendations**: "best Claude Code skills", "top AI tools" → get a LIST of specific things people mention
- **News**: "what's happening with OpenAI", "latest AI announcements" → current events and updates
- **General**: any topic you're curious about → understand what the community is saying

## 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]`

---

## 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
TOPIC_FILE="$(mktemp)"
trap 'rm -f "$TOPIC_FILE"' EXIT
cat <<'LAST30DAYS_TOPIC' > "$TOPIC_FILE"
$ARGUMENTS
LAST30DAYS_TOPIC
python3 ~/.claude/skills/last30days/scripts/last30days.py "$(cat "$TOPIC_FILE")" --emit=compact 2>&1
```

The script will automatically:

- Detect available API keys
- Show a promo banner if keys are missing (this is intentional marketing)
- Run Reddit/X searches if keys exist
- Signal if WebSearch is needed

**Step 2: Check the output mode**

The script output will indicate the mode:

- **"Mode: both"** or **"Mode: reddit-only"** or **"Mode: x-only"**: Script found results, WebSearch is supplementary
- **"Mode: web-only"**: No API keys, Claude must do ALL research via WebSearch

**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"):

- 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
  - 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
- 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

**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):

- `--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? THIS IS CRITICAL.
- 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

**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:**

- Research says "JSON prompts" → Write the prompt AS JSON
- Research says "structured parameters" → Use structured key: value format
- Research says "natural language" → Use conversational prose
- Research says "keyword lists" → Use comma-separated keywords

**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:

- [ ] **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

---

## 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
- **If they ask a question** - answer it from your research findings

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
```

## When to Use
This skill is applicable to execute the workflow or actions described in the overview.

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