sci-trending-research

name

sci-trending-research

description

Research what's trending in science — emerging topics, publication surges, community discussions on academic Reddit (r/science, r/bioinformatics, r/MachineLearning, etc.), science Twitter/X, preprint servers, and the web. Surface real discussions, breakthroughs, and debates scientists are talking about right now. Produces a research brief other sci-* skills can consume. Triggers on: "what's trending in", "emerging research", "hot topics in", "recent breakthroughs", "what are researchers saying about", "field pulse", "research trends", "community sentiment on". Does NOT trigger for literature search (use sci-literature-research), data analysis, or manuscript writing.

Trending Research

Adapted from last30days by Ronnie-Nutrition. Original skill focused on research + prompt generation. This version strips the prompt layer and focuses purely on research synthesis — designed as a backend that other sci-* skills consume.

Outcome

A research brief saved to projects/sci-trending-research/{topic}_{YYYY-MM-DD}.md containing:

• What researchers are actually discussing, publishing, and debating right now
• Engagement-weighted insights (upvotes, likes, citations signal what resonates)
• Patterns across platforms (strongest signals appear everywhere)
• Actionable takeaways for research direction and hypothesis generation

Other skills (sci-hypothesis, sci-writing, sci-communication, etc.) can read the latest research brief for timely, relevant context.

Context Needs

File	Load level	How it shapes this skill
research_context/research-profile.md	Field + interests	Helps frame research through the scientist's domain lens
context/learnings.md	## sci-trending-research section	Apply previous feedback

Load if they exist. Proceed without them if not.

---

Before You Start

1. Check projects/sci-trending-research/ for recent research on the same topic. If a brief exists from the last 7 days, show the user: "I researched [topic] on [date]. Want to use that, refresh it, or research something new?"

2. Check API keys. Read .env for OPENAI_API_KEY and XAI_API_KEY. If either is missing, tell the user once before starting:

   • Both missing: "I'll use web search for this research. For much richer results with real engagement data (upvotes, likes, comments), add OPENAI_API_KEY (for Reddit — get one at platform.openai.com) and XAI_API_KEY (for X — get one at console.x.ai) to your .env file."
   • Only OpenAI missing: "I have X data but not Reddit. Add OPENAI_API_KEY to .env for Reddit threads with real upvotes and comments."
   • Only xAI missing: "I have Reddit data but not X. Add XAI_API_KEY to .env for X posts with real likes and reposts."
   • Both present: Skip this — say nothing, just proceed.

   This is informational only. Never block work because keys are missing.

---

Step 1: Parse the Request

Extract from the user's input:

• TOPIC — what scientific area or question they want to research
• QUERY TYPE — what kind of research:
  • BREAKTHROUGHS — "recent breakthroughs in X", "new discoveries in X" → wants key findings and developments
  • METHODS — "new techniques for X", "emerging methods in X" → wants trending tools, protocols, techniques
  • DEBATES — "controversies in X", "what's the debate about X" → wants disagreements and open questions
  • GENERAL — anything else → wants broad understanding of community sentiment and emerging directions
• SCOPE — quick (5-8 searches) or deep (12-18 searches). Default: balanced (8-12).

If the topic is vague, ask one clarifying question. Don't over-ask — get moving.

---

Step 2: Run the Research

Read references/research-methodology.md for the full search strategy.

Primary: Python Script (requires API keys)

The scripts/last30days.py script uses external APIs to search Reddit and X with real engagement data:

python3 .claude/skills/sci-trending-research/scripts/last30days.py "{topic}" --emit=compact

• Reddit via OpenAI Responses API (web_search tool, domain-locked to reddit.com) — returns threads with real upvotes, comments, and top comment insights
• X / Twitter via xAI API (x_search tool) — returns posts with real likes, reposts, and reply counts
• Supports --quick (fewer sources) and --deep (comprehensive) flags
• Supports --sources=reddit|x|both|auto to control which platforms to search
• Supports --include-web to add general web search alongside Reddit/X

Requires: OPENAI_API_KEY (for Reddit) and/or XAI_API_KEY (for X) in .env. Script auto-detects available keys and adapts.

Fallback: WebSearch (no API keys needed)

If neither API key is configured, use Claude's built-in WebSearch:

Reddit (academic community discussions)

Search for: {topic} site:reddit.com targeting academic subreddits (r/science, r/bioinformatics, r/MachineLearning, etc.).

X / Twitter (science community pulse)

Search for: {topic} site:x.com OR site:twitter.com targeting science accounts and discussions.

Preprints and publications

Search for: {topic} site:biorxiv.org, {topic} site:arxiv.org, {topic} site:pubmed.ncbi.nlm.nih.gov.

Science news and journals

Search for: {topic} site:nature.com, {topic} site:sciencedaily.com, {topic} site:science.org.

Web (blogs, docs, news)

Search for: {topic} with time-filtered queries. Exclude reddit.com and x.com.

WebSearch works but lacks real engagement metrics (upvotes, likes). The script provides much richer data.

---

Step 3: Synthesize Findings

Read references/synthesis-guide.md for the full methodology.

Weight sources by engagement signals:

• Reddit threads with 50+ upvotes and active discussion = strong signal
• X posts with high engagement (likes, reposts) from researchers = trending signal
• Preprints with significant social media attention = emerging signal
• Published papers with editorial/news coverage = validated signal
• Multiple sources saying the same thing = strongest signal

Synthesize by query type:

BREAKTHROUGHS → Extract specific findings, methods, and their significance:

Key breakthroughs:
1. [Discovery/finding] — [lab/group], [journal/preprint]
   - Community reaction: [sentiment from Reddit/X]
2. [Discovery/finding] — [lab/group], [source]

METHODS → Top techniques, tools, protocols ranked by adoption and discussion:

Trending methods:
1. [Technique] — discussed in 4 sources, gaining traction in [subfields]
   - Why: [what problem it solves]
   - Caveat: [limitations noted by community]

DEBATES → Key disagreements, open questions, competing hypotheses

GENERAL → Key themes, community sentiment, emerging directions

---

Step 4: Show Results

Display the synthesis in this format:

## What I found — {TOPIC} (last 30 days)

[2-4 sentence synthesis of the key insight]

### Key findings
1. [Finding with source attribution]
2. [Finding with source attribution]
3. [Finding with source attribution]

### Sources scanned
- Reddit: {n} threads across r/{sub1}, r/{sub2}
- X: {n} posts from @{handle1}, @{handle2}
- Preprints/Papers: {n} from bioRxiv, arXiv, PubMed
- Web: {n} pages from {domain1}, {domain2}

---

Step 5: Save the Brief

Save to projects/sci-trending-research/{topic-slug}_{YYYY-MM-DD}.md.

The brief format is defined in references/brief-template.md. Include:

• Research metadata (topic, date, query type, sources scanned)
• Synthesis (findings, patterns, emerging directions)
• Raw source list (URLs, engagement metrics where available)
• Research implications (how this research could inform next steps)

This file is what other skills consume. Keep it structured and scannable.

---

Step 6: Offer Next Steps

Based on the research and installed skills, recommend one action:

• "This could inform a new hypothesis — want me to generate testable hypotheses with sci-hypothesis?"
• "There's enough convergence here for a review or perspective piece — want me to draft a section with sci-writing?"
• "This would make a good tutorial or explainer — want me to route to sci-communication?"
• "I found [X] trending hard — want me to research deeper on that angle?"

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Rules

Updated automatically when the user flags issues. Read before every run.

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Self-Update

If the user flags an issue — bad sources, irrelevant results, wrong synthesis — update the ## Rules section immediately with the correction and today's date.

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Troubleshooting

Too few results: Broaden the search terms. Strip modifiers and search for the core noun. Try --deep flag. Results feel outdated: Add year to search queries. Use "2026" or "this month" qualifiers. Platform-specific content missing: Some topics are discussed more on Reddit vs X. Use --sources=reddit or --sources=x to focus. Preprint-heavy topics: Add explicit bioRxiv/arXiv searches. Some fields discuss primarily on preprint servers. User wants real engagement metrics: Use the Python script with API keys. WebSearch fallback lacks exact counts. Script errors: Check .env has valid OPENAI_API_KEY and/or XAI_API_KEY. Fall back to WebSearch if scripts fail.