← Back to list

data-fetch
by lukeslp
Claude Code skills plugin for dr.eamer.dev workflows - session management, quality audits, UX design, and data visualization
⭐ 1🍴 0📅 Jan 15, 2026
SKILL.md
name: data-fetch description: Fetch and aggregate data from 17 external APIs including Census, arXiv, NASA, Wikipedia, PubMed, and GitHub. version: 1.0.0
Data Fetch
You are fetching and aggregating data from multiple external sources using the shared library's DataFetchingFactory. This skill provides access to 17 structured API clients.
Available Data Sources
| Source | Client | Best For |
|---|---|---|
| Academic | ||
| arXiv | arxiv | Research papers, preprints |
| Semantic Scholar | semantic_scholar | Academic citations, papers |
| PubMed | pubmed | Medical/biomedical research |
| Government | ||
| Census Bureau | census | Demographics, economic data |
| FEC | fec | Campaign finance |
| Judiciary | judiciary | Court records, cases |
| Web/News | ||
| Wikipedia | wikipedia | General knowledge |
| News APIs | news | Current events |
| Archive.org | archive | Historical web content |
| Tech | ||
| GitHub | github | Repositories, code |
| YouTube | youtube | Video content, transcripts |
| Scientific | ||
| NASA | nasa | Space, astronomy data |
| Wolfram Alpha | wolfram | Computational answers |
| Other | ||
| Finance | finance | Stock data, markets |
| Weather | weather | Weather forecasts |
| OpenLibrary | openlibrary | Books, authors |
| MyAnimeList | myanimelist | Anime/manga data |
Execution Strategy
Single Source Query
from data_fetching import DataFetchingFactory
factory = DataFetchingFactory()
client = factory.create_client('arxiv')
results = await client.search("quantum computing", max_results=10)
Multi-Source Aggregation (PARALLEL)
import asyncio
sources = ['arxiv', 'wikipedia', 'news']
tasks = [factory.create_client(s).search(query) for s in sources]
results = await asyncio.gather(*tasks)
Source Selection Guide
| Query Type | Recommended Sources |
|---|---|
| Academic research | arxiv, semantic_scholar, pubmed |
| Current events | news, wikipedia |
| Technical/code | github, stackoverflow |
| Demographics | census |
| Historical | archive, wikipedia |
| Scientific facts | nasa, wolfram |
| Books/literature | openlibrary |
Output Format
📊 DATA FETCH RESULTS
Query: {query}
Sources: {sources_used}
Date: {timestamp}
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
SOURCE: {source_name}
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Results: {count}
1. {title}
- {metadata}
- URL: {url}
2. {title}
...
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
AGGREGATED INSIGHTS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
Cross-Source Themes:
1. {theme} - Found in: {sources}
2. {theme} - Found in: {sources}
Conflicts/Discrepancies:
- {source1} says X, {source2} says Y
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
CITATIONS
━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━
[1] {citation}
[2] {citation}
Integration with Orchestrators
For complex research, combine with orchestration:
/data-fetch → provides raw data
↓
DreamCascade → synthesizes findings
↓
/data-artist → visualizes results
Key Principles
- Parallel fetching - Query multiple sources simultaneously
- Source attribution - Always cite data origins
- Deduplication - Merge overlapping results
- Rate limiting - Respect API limits per client
- Caching - Use MCP cache for repeated queries
Common Workflows
# Census demographics
/data-fetch census "housing prices by county"
# Academic research
/data-fetch arxiv,pubmed "CRISPR gene editing"
# Tech exploration
/data-fetch github "machine learning frameworks" --stars >1000
# Current events
/data-fetch news,wikipedia "climate summit 2026"
Related Skills
/data-artist- Visualize fetched data beautifully/quality-audit- Verify data quality and validate findings
Score
Total Score
70/100
Based on repository quality metrics
✓SKILL.md
SKILL.mdファイルが含まれている
+20
✓LICENSE
ライセンスが設定されている
+10
✓説明文
100文字以上の説明がある
+10
○人気
GitHub Stars 100以上
0/15
○最近の活動
3ヶ月以内に更新がある
0/10
○フォーク
10回以上フォークされている
0/5
✓Issue管理
オープンIssueが50未満
+5
✓言語
プログラミング言語が設定されている
+5
○タグ
1つ以上のタグが設定されている
0/5
Reviews
💬
Reviews coming soon