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quick-topic-researcher

quick-topic-researcher

github.com/drshailesh88Productivity647 installsUpdated 24w ago
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About quick-topic-researcher

quick-topic-researcher is a rapid research skill for content creators preparing videos or writing. It builds a focused brief from five questions and parallel searches, using PubMed for citable medical evidence and Perplexity for context discovery.

Key features

  1. 01Generate five research questions for a topic
  2. 02Search in parallel and organize findings
  3. 03Retrieve citable medical evidence from PubMed
  4. 04Add context from guidelines and web search
  5. 05Produce a structured Markdown brief

Use cases

  1. 01Prepare a topic before recording a YouTube video
  2. 02Find key points before writing a tweet thread
  3. 03Refresh topic knowledge before a podcast
  4. 04Get a quick research overview for a newsletter

MCP support

The skill uses MCP to search PubMed articles and fetch their contents, and Perplexity MCP to explore context. The README identifies PubMed as the citable evidence source and Perplexity as a discovery tool, not a citation source.

Install

Copy the command and run it in a terminal.

$npx skills add https://github.com/drshailesh88/integrated_content_os --skill quick-topic-researcher

After installing, type/quick-topic-researcherin Claude Code to confirm it loaded.

Bundled filesrequirements.txtscripts/quick_research.py

Details

From the project README

Quick Topic Researcher

5 minutes to topic mastery. This skill generates a focused research brief you can use immediately before recording a video or writing content.

Different from deep-researcher: That skill is comprehensive (5+ sources, file-based, 30+ minutes). This skill is FAST (5 questions, parallel search, 5 minutes).


When to Use

Use CaseThis Skill
Prepping for a YouTube videoYes
Writing a quick tweet threadYes
Refreshing knowledge on a topicYes
Before a podcast discussionYes
Comprehensive literature reviewNo → Use deep-researcher
Writing a formal editorialNo → Use deep-researcher first

How It Works

TOPIC: "GLP-1 agonists in heart failure"
DOMAIN: "Cardiology"

    │
    ▼
┌─────────────────────────────────────────────────────┐
│ STEP 1: Generate 5 Research Questions               │
│                                                      │
│ 1. Do GLP-1 agonists reduce heart failure           │
│    hospitalization in diabetic patients?            │
│ 2. Is there evidence of direct cardiac benefit?     │
│ 3. What are the key trials showing CV outcomes?     │
│ 4. Are there safety concerns in existing HF?        │
│ 5. What do current guidelines recommend?            │
└─────────────────────────────────────────────────────┘
    │
    ▼
┌─────────────────────────────────────────────────────┐
│ STEP 2: Parallel Research (5 searches at once)      │
│                                                      │
│ [PubMed Q1] [PubMed Q2] [PubMed Q3] [Perplexity Q4] │
│ [Perplexity Q5]                                      │
│                                                      │
│ ~30 seconds total                                    │
└─────────────────────────────────────────────────────┘
    │
    ▼
┌─────────────────────────────────────────────────────┐
│ STEP 3: McKinsey-Style Brief                         │
│                                                      │
│ EXECUTIVE SUMMARY                                    │
│ • Key finding with strongest PMID                   │
│                                                      │
│ ANALYSIS                                             │
│ • Theme 1: Trial evidence (PMIDs)                   │
│ • Theme 2: Mechanisms (PMIDs)                       │
│ • Theme 3: Guidelines                               │
│                                                      │
│ CLINICAL IMPLICATIONS                                │
│ • What this means for your content                  │
│                                                      │
│ KEY PMIDS TO CITE                                    │
│ • List of 5-7 citation-ready references             │
└─────────────────────────────────────────────────────┘

Usage

Interactive Mode (Recommended)

Ask Claude:

Use quick-topic-researcher for [TOPIC] in [DOMAIN]

Example:

Use quick-topic-researcher for "SGLT2 inhibitors in CKD" in "Cardiology/Nephrology"
CLI Mode (Coming Soon)
python skills/cardiology/quick-topic-researcher/scripts/quick_research.py \
    --topic "GLP-1 agonists in heart failure" \
    --domain "Cardiology"

Research Sources

Primary (Citable)
SourceToolPurpose
PubMed MCPpubmed_search_articles, pubmed_fetch_contentsAll medical evidence
GuidelinesDirect URL fetch to ACC/ESC/ADARecommendations
Discovery (Not Citable)
SourceToolPurpose
Perplexityperplexity_ask via MCPQuick context, trend discovery
Web SearchWebSearchBackground, non-medical context

Rule: You can USE Perplexity to understand context, but you CITE only PubMed.


Output Format

The skill outputs a structured brief:

# Quick Research Brief: [TOPIC]

**Domain:** [DOMAIN]
**Generated:** [DATE]
**Time to Read:** 3 minutes

---

## Executive Summary

[2-3 sentences: What you need to know before recording/writing]

Key takeaway: [ONE sentence with strongest PMID]

---

## Research Questions & Findings

### Q1: [Question]
**Answer:** [Concise answer]
**Evidence:** [Study name, PMID, key stat (HR, CI, p-value)]

### Q2: [Question]
**Answer:** [Concise answer]
**Evidence:** [Study name, PMID, key stat]

[... Q3-Q5 ...]

---

## Clinical Context

### What Guidelines Say
[ACC/ESC/ADA recommendations with class/level]

### Practice Implications
[What this means for real patients]

---

## Content Hooks

For your video/content, consider these angles:
1. [Hook 1 based on findings]
2. [Hook 2 based on findings]
3. [Hook 3 based on findings]

---

## Citation-Ready References

1. Author A, et al. TRIAL-NAME. Journal. Year. PMID: XXXXXXXX
2. Author B, et al. Study Name. Journal. Year. PMID: XXXXXXXX
3. [5-7 total references]

---

## Gaps & Caveats

- [What the evidence doesn't cover]
- [Patient populations with limited data]

Integration with Content Pipeline

Before YouTube Script
1. Run quick-topic-researcher on your video topic
2. Review the brief (3 min read)
3. Open youtube-script-master with the brief in context
4. Script now has verified facts and PMIDs
Before Tweet Thread
1. Run quick-topic-researcher
2. Pick 1-2 key findings from the brief
3. Use x-post-creator-skill with specific PMIDs
Before Newsletter
1. Run quick-topic-researcher for quick take
2. If topic is complex, follow up with deep-researcher
3. Write with cardiology-newsletter-writer

Example Session

User: Use quick-topic-researcher for "colchicine in cardiovascular prevention" in "Cardiology"

Claude:

I'll research this topic rapidly using PubMed and generate a brief.

Step 1: Generating 5 research questions...

  1. Does colchicine reduce major cardiovascular events in CAD patients?
  2. What are the key RCTs (COLCOT, LoDoCo2, CLEAR SYNERGY)?
  3. What is the proposed anti-inflammatory mechanism?
  4. What are the safety concerns and contraindications?
  5. What do current guidelines recommend?

Step 2: Parallel research...

[Executes 5 PubMed searches in parallel] [Fetches key article abstracts] [Searches Perplexity for context]

Step 3: Generating McKinsey-style brief...


Quick Research Brief: Colchicine in CV Prevention

Domain: Cardiology Generated: 2026-01-01 Time to Read: 3 minutes

Executive Summary

Low-dose colchicine (0.5mg daily) reduces cardiovascular events in patients with established coronary artery disease through anti-inflammatory mechanisms. COLCOT and LoDoCo2 showed consistent benefit; CLEAR SYNERGY was neutral but in a different population.

Key takeaway: In stable CAD patients, colchicine 0.5mg daily reduces CV events by ~25% (HR 0.69-0.77) (PMID: 31733140, 32865377)

Research Questions & Findings

Q1: Does colchicine reduce major CV events?

Answer: Yes, in stable CAD Evidence: LoDoCo2: HR 0.69 (0.57-0.83), p<0.001 for CV death/MI/stroke (PMID: 32865377)

Q2: What are the key trials?

Answer: COLCOT (post-MI), LoDoCo2 (chronic CAD), CLEAR SYNERGY (post-PCI) Evidence:

  • COLCOT: 0.5mg, HR 0.77 for composite (PMID: 31733140)
  • LoDoCo2: 0.5mg, HR 0.69 for composite (PMID: 32865377)
  • CLEAR SYNERGY: Neutral for primary endpoint (PMID: 37634428)
Q3: What is the mechanism?

Answer: NLRP3 inflammasome inhibition, IL-1β reduction Evidence: Reduces hsCRP; targets residual inflammatory risk (PMID: 29724838)

Q4: Safety concerns?

Answer: GI side effects, myopathy with statins, CKD dose adjustment Evidence: NNH for GI: ~50; avoid with strong CYP3A4 inhibitors (PMID: 31733140)

Q5: Guidelines?

Answer: Class IIb in ESC 2024 for chronic CAD Evidence: ESC 2024 CCS Guidelines, consider in patients with elevated hsCRP

Clinical Context

What Guidelines Say

ESC 2024: Class IIb, Level A - "Colchicine 0.5mg may be considered to reduce CV risk in chronic coronary syndrome"

Practice Implications
  • Best candidates: Stable CAD with elevated hsCRP despite optimal therapy
  • Less certain: Immediately post-MI (COLCOT positive, but smaller effect)
  • Probably not: Post-PCI without other CAD (CLEAR SYNERGY neutral)

Content Hooks

  1. "The inflammation hypothesis finally has a drug - and it's ancient"
  2. "0.5mg for 50 cents - the cheapest CV prevention we've ignored"
  3. "Why the cardiologist's gout drug became a heart drug"

Citation-Ready References

  1. Tardif JC, et al. COLCOT. NEJM. 2019. PMID: 31733140
  2. Nidorf SM, et al. LoDoCo2. NEJM. 2020. PMID: 32865377
  3. Jolly SS, et al. CLEAR SYNERGY. NEJM. 2024. PMID: 37634428
  4. Ridker PM. Residual inflammatory risk. JACC. 2018. PMID: 29724838
  5. ESC CCS Guidelines 2024

Gaps & Caveats

  • No RCT in primary prevention (only secondary prevention studied)
  • Unclear benefit in patients with normal hsCRP
  • Long-term safety (>3 years) data limited
  • CLEAR SYNERGY challenges universal applicability

Ready for your video! You now have verified facts, PMIDs, and content hooks.


Comparison with Other Skills

SkillTimeDepthUse Case
quick-topic-researcher5 minSurface + key trialsVideo prep, quick refresh
deep-researcher30-60 minComprehensiveEditorials, literature review
pubmed-database2 minSingle searchSpecific question
perplexity-search1 minTrend onlyDiscovery, non-citable

Technical Implementation

Dependencies
  • PubMed MCP (existing)
  • Perplexity MCP (existing)
  • Claude (default model)
Parallel Execution

The skill uses Claude's ability to make multiple tool calls simultaneously:

# These run in parallel (single message, multiple tool calls)
pubmed_search_articles(queryTerm="colchicine cardiovascular RCT", maxResults=10)
pubmed_search_articles(queryTerm="colchicine mechanism inflammation", maxResults=5)
perplexity_ask(messages=[{"role": "user", "content": "colchicine cardiology guidelines 2024"}])
Output
  • Markdown brief (displayed in terminal)
  • Optional: Save to ~/research_briefs/{topic}_{date}.md

This skill gets you from "I need to know about X" to "I can confidently speak about X" in 5 minutes.

Comments

Markdown supported