By zongmin-yu
Research paper triage, citation graph mapping, and reading list expansion using the Semantic Scholar API for literature review workflows.
Expand one to three seed papers into nearby, bridge, foundational, methodological, recent, and survey follow-ups
Triage an ambiguous paper query into likely interpretations, a ranked shortlist, and recommended follow-up workflows
Trace the citation neighborhood around one focal paper into foundations, descendants, bridges, weak edges, and optional second-hop links
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S2-first discovery engine for AI research workflows.
Three research workflows built on the Semantic Scholar API — available as a Python library, Claude Code skills, or a 16-tool MCP server.
claude plugin install github:zongmin-yu/semantic-scholar-skills
cp -r skills/* ~/.claude/skills/
/expand-references — Discover related work from seed papersFeed 1–3 seed papers. Get back curated buckets: foundational, methodological, recent, survey, bridge papers, and closest neighbors. Powered by S2's Recommendations API with positive/negative seeds.
/trace-citations — Map a paper's citation neighborhoodPick a focal paper. Trace its citations and references with context snippets, intent labels, and influence flags. Returns foundations, descendants, bridge connections, and optional second-hop expansion.
/paper-triage — Triage an ambiguous query into a shortlistType a vague query. The engine runs autocomplete, relevance search, bulk search, and snippet extraction in parallel, then scores and ranks into a shortlist with explanations.
# Copy any skill to your personal skills directory
cp -r skills/expand-references ~/.claude/skills/
# Then in Claude Code:
/expand-references Attention Is All You Need
Each skill is fully self-contained — no pip install required. The bundled standalone runtime uses only Python stdlib.
pip install semantic-scholar-skills
core library only: installs core/, engine/, and the stdlib-backed standalone/ runtime.
import asyncio
from semantic_scholar_skills.core import get_default_client, cleanup_client
from semantic_scholar_skills.engine import paper_triage
async def main():
client = get_default_client()
try:
result = await paper_triage(client, "retrieval augmented generation")
for paper in result.shortlist[:5]:
print(f"{paper.score:.2f} {paper.paper.title}")
finally:
await cleanup_client()
asyncio.run(main())
pip install "semantic-scholar-skills[mcp]"
semantic-scholar-skills-mcp
full MCP stack: installs fastmcp, fastapi, and uvicorn in addition to the core library.
16 tools covering papers, authors, citations, recommendations, and snippets. Works with Claude Desktop, Cursor, and any MCP client.
Claude Code Skills MCP Server (16 tools)
│ │
▼ ▼
┌─────────────┐ ┌─────────────┐
│ skills-src/ │ │ mcp/ │
│ (SKILL.md) │ │ (FastMCP) │
└──────┬───────┘ └──────┬──────┘
│ │
▼ ▼
┌──────────────────────────────────────┐
│ engine/ — Workflow Logic │
│ expand_references · trace_citations │
│ paper_triage · resolve · scoring │
└──────────────────┬───────────────────┘
│
┌───────────┴───────────┐
▼ ▼
┌─────────────┐ ┌─────────────┐
│ core/ │ │ standalone/ │
│ (httpx) │ │ (urllib) │
└─────────────┘ └─────────────┘
│ │
└───────────┬───────────┘
▼
Semantic Scholar API
Source is shared, artifacts are self-contained. The engine/ and standalone/ layers are vendored into each skill bundle by bundle_skills.py, so users can copy a single folder and it just works.
export SEMANTIC_SCHOLAR_API_KEY=your-key-here
Without a key: 100 requests per 5 minutes. With a key: up to 10 req/s. Get one free at semanticscholar.org/product/api.
The skills/ directory contains pre-built, self-contained bundles for Claude Code:
Move active Claude Code workflows between machines without losing the thread
Use Codex as a sub-agent inside Claude Code skills
npx claudepluginhub zongmin-yu/semantic-scholar-skillsAcademic literature search, citation management, PDF retrieval, and literature review synthesis
Systematic literature searching and review toolkit for Claude Code. Search PubMed, screen papers, extract data, traverse citations, and synthesize findings from scientific literature.
Use when the user needs academic paper retrieval — searching scientific literature by author/year/journal, finding paper chunks for RAG-style citations, or expanding original text around a known paper offset. Provides three Sciverse tools (search_papers, semantic_search, read_content) via the sciverse-mcp-server MCP server.
Annotated research paper collection management — retrieve, read, extract, cross-reference scientific papers
深度研究 — 13 agent 协作:研究问题定义、系统性检索、偏差评估、综合分析、引用编译
Academic research tools for scholarly workflow