From ai-frontier
Search Semantic Scholar for papers with rich metadata — citation counts, AI-generated TLDRs, influence scores, citation graphs. Use for finding established research, tracing citation chains, understanding paper impact and field structure.
How this skill is triggered — by the user, by Claude, or both
Slash command
/ai-frontier:semantic-scholar-searchThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Search 200M+ papers with rich metadata. No API key required (100 req/sec).
Search 200M+ papers with rich metadata. No API key required (100 req/sec).
Two modes:
SCRIPT=$(find ~/.claude/plugins -path "*/ai-frontier/skills/semantic-scholar-search/scripts/search.mjs" 2>/dev/null | head -1)
# Search mode
node "$SCRIPT" "your query" [maxResults] [--year=2024] [--open-access]
# Detail mode (get paper + citations + references)
node "$SCRIPT" --detail=<s2PaperId|DOI|ArXiv:id>
| Arg | Default | Description |
|---|---|---|
| query | (required) | Natural language search query |
| maxResults | 10 | Number of results (1-100) |
| --year=YYYY | none | Only papers from YYYY onward |
| --open-access | false | Only papers with free PDF |
| --detail=ID | n/a | Get full details for a specific paper |
results[].tldr — AI-generated one-sentence summary (from S2)results[].citations — total citation countresults[].source_specific.influential_citations — citations from influential papersresults[].source_specific.fields_of_study — e.g., ["Computer Science", "Mathematics"]paper.top_references and paper.recent_citations for citation graph# Find influential papers on RLHF
node "$SCRIPT" "reinforcement learning from human feedback" 10
# Recent papers only (2025+)
node "$SCRIPT" "mixture of experts scaling" 15 --year=2025
# Get details + citation graph for a specific paper
node "$SCRIPT" --detail=ArXiv:2210.11416
npx claudepluginhub flight505/ai-frontierFinds research papers answering a query using Firecrawl: semantic search, related-paper expansion, and in-body verification. Supports single-paper lookups and full multi-paper sets.
Performs deep research over Semantic Scholar's Graph API — references, recommendations, batch paper lookup (up to 500 IDs), snippet search, and multi-hop BFS citation graph traversal. Use for building citation networks, expanding literature seeds, finding related work, or resolving many DOI/arXiv/S2 IDs.
Retrieves academic papers via MCP tools: structured search by author/journal/year, semantic chunk search for RAG citations, and byte-range content expansion by doc_id.