Agent skill · Content & Marketing

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.

majiayu000github.com/majiayu000GitHub ↗
claude-codeMIT
Install
npx skills add majiayu000/claude-skill-registry --skill last30days-clinscott-cstar --agent claude-code

Same command for any agent — swap --agent for codex, cursor, copilot.

Facts
Files in the skill folder: 2
SKILL.md size: 14 KB
Bundled scripts: none
Path: skills/analysis/last30days-clinscott-cstar/SKILL.md
Open the folder on GitHub →
Where it comes from
Stars: 534
Language: HTML

Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.

From the SKILL.md

# 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

What's inside
Steps it walks through
  1. CRITICAL: Parse User Intent
  2. Setup Check
  3. First-Time Setup (Optional but Recommended)
  4. Research Execution
  5. Judge Agent: Synthesize All Sources
  6. FIRST: Internalize the Research
  7. If QUERYTYPE = RECOMMENDATIONS
  8. For all QUERYTYPEs
  9. THEN: Show Summary + Invite Vision
  10. WAIT FOR USER'S VISION
  11. WHEN USER SHARES THEIR VISION: Write ONE Perfect Prompt
  12. CRITICAL: Match the FORMAT the research recommends
  13. Output Format:
  14. Quality Checklist:
Ships with 1 file
  • metadata.json
Commands it runs
mkdir -p ~/.config/last30days
cat > ~/.config/last30days/.env << 'ENVEOF'
chmod 600 ~/.config/last30days/.env
echo "Config created at ~/.config/last30days/.env"
echo "Edit to add your API keys for enhanced research."
python3 ~/.claude/skills/last30days/scripts/last30days.py "$ARGUMENTS" --emit=compact 2>&1
More from claude-skill-registry
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About this skill
What does the last30days 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.

How do I install it?

Run `npx skills add majiayu000/claude-skill-registry --skill last30days-clinscott-cstar --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.

Where does this skill come from?

From majiayu000/claude-skill-registry, a repository with 534 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.

Is a popular skill a good skill?

Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.

Keep going