sci-trending-research

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更新时间2026年4月26日 20:03

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.

安装

用 Codex 或 Claude 帮你安装复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。

来源

krmdel

krmdel/organon

打开 GitHub 仓库查看创作者相关仓库

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相关职业SOC

基于 SOC 职业分类

生物化学家和生物物理学家生命、物理与社会科学类职业·SOC 19-1021

文件资源管理器

21 个文件

SKILL.md

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同仓库更多 Skills

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sci-writing

krmdel/organon

Draft manuscript sections, format citations, and get AI peer review. Natural language invocation -- describe what you need and the skill routes to drafting, citation formatting, or peer review. Reads research profile, data analysis outputs, and literature search results for context-aware writing. After drafting, offers to generate supporting figures via viz skills. Triggers on: "draft introduction", "write methods", "format citations", "APA style", "bibliography", "peer review", "review my draft", "write abstract". Does NOT trigger for: literature search (use sci-literature-research), data analysis (use sci-data-analysis), image generation (use viz-nano-banana), repurpose/blog/lay summary (use sci-communication).

2026-07-028

viz-figure-mirror

krmdel/organon

Transfer the visual style of a reference paper figure onto the user's own data. Takes a screenshot of a figure from a paper plus tabular data and produces an editable matplotlib script in that figure's register, gated by a mechanical quality floor and a Drawer/Reviewer refinement loop. Output is a self-contained .py + PNG + Type-42 PDF. Triggers on: "match this figure style", "figure in the style of", "make my plot look like this paper", "publication figure from reference", "style transfer figure", "reproduce this figure with my data", "NeurIPS-quality version of this chart". Does NOT trigger for: plain data plots with no reference image (use sci-data-analysis), AI-generated illustrations (use viz-nano-banana), flowcharts/architecture/sequence diagrams (use viz-diagram-code), hand-drawn sketches (use viz-excalidraw-diagram).

2026-07-028

tool-substack

krmdel/organon

Publish and edit markdown blog posts on Substack as drafts — converts markdown to Substack's ProseMirror schema, uploads local images to Substack's CDN, pre-renders mermaid diagrams to PNG, and creates or updates drafts via Substack's private API. Draft-only by design — publish is always a human click. Triggers on: "push to substack", "substack draft", "publish to substack", "create substack draft", "send to substack", "substack this post", "update substack", "edit substack draft", "list substack drafts". Does NOT trigger for: reading existing Substack posts, subscriber management, newsletter scheduling. Does NOT publish — only creates/updates drafts you review and publish by hand.

2026-05-128

meta-skill-creator

krmdel/organon

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

2026-04-268

meta-wrap-up

krmdel/organon

End-of-session checklist that reviews deliverables, collects feedback, fixes skills, updates learnings, and commits work. Use when the user says "wrap up", "close session", "end session", "wrap things up", "we're done", "that's it for today", "session done", or invokes /wrap-up. Run at the end of any working session or after completing a major deliverable. Does NOT trigger for content writing, voice extraction, positioning, or audience research.

2026-04-268

ops-cron

krmdel/organon

Schedule recurring tasks that run automatically via a system-level watchdog, even when Claude Code is closed. Job definitions persist in cron/jobs/ as the registry. The watchdog (launchd on Mac, Task Scheduler on Windows) checks every hour and runs due jobs headlessly via claude -p. Triggers on: "schedule a job", "cron job", "run this every morning", "automate daily", "recurring task", "set up a scheduled job", "check scheduled jobs", "list scheduled jobs", "install watchdog", "uninstall watchdog". Does NOT trigger for one-off tasks or in-session reminders.

2026-04-268

name

sci-trending-research

description

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

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?"
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?"

Rules

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

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.

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.