firecrawl-research
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This skill should be used when the user requests to research topics using FireCrawl, enrich notes with web sources, search and scrape information, or write scientific/academic papers. It extracts research topics from markdown files, creates research documents with scraped sources, generates BibTeX bibliographies from research results, and provides Pandoc/MyST templates for academic writing with citation management.
3installs
Sourceglebis/claude-skills
Added on
NPX Install
npx skill4agent add glebis/claude-skills firecrawl-researchTags
Translated version includes tags in frontmatterSKILL.md Content
View Translation Comparison →FireCrawl Research
Overview
Enrich research documents by automatically searching and scraping web sources using the FireCrawl API. Extract research topics from markdown files and generate comprehensive research documents with source material.
When to Use This Skill
Use this skill when the user:
- Says "Research this topic using FireCrawl"
- Requests to enrich notes or documents with web sources
- Wants to gather information about topics listed in a markdown file
- Needs to search and scrape multiple topics systematically
How It Works
1. Topic Extraction
The script automatically extracts research topics from markdown files using two methods:
Method 1: Headers
markdown
## Spatial Reasoning in AI
### Computer Vision ApplicationsBoth and become research topics.
Spatial Reasoning in AIComputer Vision ApplicationsMethod 2: Research Tags
markdown
- [research] Large Language Models for robotics
- [search] Theory of Mind in autonomous drivingBoth tagged items become research topics.
2. Search and Scrape
For each topic:
- Searches FireCrawl with the topic as query
- Retrieves up to N results (default: 5)
- Automatically scrapes full content from each result
- Extracts markdown-formatted content (main content only)
3. Output Generation
Creates new markdown files in the specified output directory:
- One file per topic
- Filename:
{topic}_{timestamp}.md - Contains: title, date, sources count, full scraped content
- Each source includes: title, URL, markdown content
Usage
Basic Usage
bash
python scripts/firecrawl_research.py research.mdOutputs to current directory.
Specify Output Directory
bash
python scripts/firecrawl_research.py research.md ./outputCreates files in folder.
./output/Limit Results Per Topic
bash
python scripts/firecrawl_research.py research.md ./output 3Retrieves maximum 3 results per topic.
Configuration
API Key Setup
-
Copyto
.env.example:.envbashcp .env.example .env -
Add FireCrawl API key:
FIRECRAWL_API_KEY=fc-your-actual-api-key
The script automatically loads the API key from the skill's file.
.envRate Limiting
The script includes automatic rate limiting for FireCrawl's free tier:
- Free tier limit: 5 requests/minute
- Built-in delay: 12 seconds between topics
- Prevents API errors and credit exhaustion
When processing multiple topics, expect:
- 5 topics: ~1 minute
- 10 topics: ~2 minutes
- 20 topics: ~4 minutes
Workflow Example
User request: "Research these AI topics using FireCrawl"
Input file ():
ai-research.mdmarkdown
# AI Research Topics
## Spatial Reasoning in Vision-Language Models
- [research] Embodied AI for robotics
- [research] Computer Use AgentsCommand:
bash
python scripts/firecrawl_research.py ai-research.md ./research_output 5Output:
research_output/
├── Spatial_Reasoning_in_Vision-Language_Models_20251122_140530.md
├── Embodied_AI_for_robotics_20251122_140542.md
└── Computer_Use_Agents_20251122_140554.mdEach file contains:
- Topic title
- Timestamp
- Source count
- Full scraped content from up to 5 sources
- Source URLs
Common Patterns
Pattern 1: Quick Research
Extract topics from existing notes, research them, save to current folder:
bash
python scripts/firecrawl_research.py my-notes.mdPattern 2: Organized Research
Create dedicated output folder for research results:
bash
python scripts/firecrawl_research.py topics.md ./research_resultsPattern 3: Deep Dive
Increase results per topic for comprehensive coverage:
bash
python scripts/firecrawl_research.py topics.md ./deep_research 10Pattern 4: Obsidian Vault Integration
Direct output to vault's research folder:
bash
python scripts/firecrawl_research.py topics.md ~/Brains/brain/ResearchError Handling
"API key not found"
Create file in skill folder with
.envFIRECRAWL_API_KEY=..."Rate limit exceeded"
- Free tier: 5 req/min
- Script has 12s delay built-in
- If still hitting limit, reduce topics or wait between runs
"Insufficient credits"
- Check FireCrawl account credits
- Upgrade plan or wait for credit reset
"No topics found"
Add topics to markdown using:
## Header format- [research] Topic format- [search] Topic format
Script Details
Location:
scripts/firecrawl_research.pyDependencies:
- - Environment variable management
python-dotenv - - HTTP requests to FireCrawl API
requests
Install dependencies:
bash
pip install python-dotenv requestsFireCrawl Features Used:
- endpoint - Search with automatic scraping
/v1/search - - Markdown output
scrapeOptions.formats: ['markdown'] - - Filter noise
scrapeOptions.onlyMainContent: true
Academic Writing Templates
This skill includes templates for writing scientific papers in markdown format.
Available Templates
1. Pandoc Scholarly Paper ()
assets/templates/pandoc-scholarly-paper.md- Standard academic paper format
- Compatible with Pandoc converter
- Supports citations via BibTeX
- Exports to PDF, DOCX, HTML
2. MyST Scientific Paper ()
assets/templates/myst-scientific-paper.md- MyST (Markedly Structured Text) format
- Advanced cross-referencing
- Professional scientific publishing
- Multi-format export (PDF, LaTeX, DOCX)
Using Templates
Copy template to your project:
bash
cp assets/templates/pandoc-scholarly-paper.md my-paper.md
# or
cp assets/templates/myst-scientific-paper.md my-paper.mdEdit content:
- Update YAML frontmatter (title, authors, affiliations)
- Write your content in sections
- Add citations using (Pandoc) or
[@AuthorYear]AuthorYear`` (MyST){cite}\
Convert to PDF/DOCX:
bash
python scripts/convert_academic.py my-paper.md pdf
python scripts/convert_academic.py my-paper.md docx
python scripts/convert_academic.py my-paper.md pdf --myst # For MySTBibliography Generation
Convert FireCrawl research results into BibTeX bibliography entries:
bash
python scripts/generate_bibliography.py research_output/*.md -o references.bibWhat it does:
- Extracts URLs and titles from FireCrawl markdown files
- Generates BibTeX entries
@misc - Creates citation keys automatically
- Adds access dates
Example workflow:
bash
# 1. Research topics
python scripts/firecrawl_research.py topics.md ./research
# 2. Generate bibliography
python scripts/generate_bibliography.py research/*.md -o refs.bib
# 3. Copy template
cp assets/templates/pandoc-scholarly-paper.md paper.md
# 4. Edit paper.md (add content, cite sources)
# 5. Convert to PDF
python scripts/convert_academic.py paper.md pdfCitation Examples
Pandoc syntax:
markdown
Recent research [@Smith2024] shows...
Multiple studies [@Jones2023; @Brown2024] indicate...MyST syntax:
markdown
Recent research {cite}`Smith2024` shows...
Multiple studies {cite}`Jones2023,Brown2024` indicate...Example Bibliography File
An example bibliography is provided in with common entry types:
assets/references.bib- Journal articles ()
@article - Conference papers ()
@inproceedings - Books ()
@book - PhD theses ()
@phdthesis - Web resources ()
@misc - Preprints (with arXiv)
@article
Tips
- Organize topics hierarchically - Use for main topics,
##for subtopics### - Use descriptive names - Topic text becomes filename, make it clear
- Batch processing - Group related topics in one file for efficiency
- Output organization - Create separate folders for different research projects
- Content review - Results are truncated at 3000 chars/source for readability
- Academic workflow - Use bibliography generator to cite research sources in papers
- Template customization - Modify templates for your field's citation style
Limitations
- No summarization - Returns raw scraped content, not summaries
- No deduplication - Duplicate sources may appear across topics
- No quality ranking - All results treated equally
- New files only - Does not append to existing files
- Free tier constraints - Rate limiting affects processing speed