<objective> Search for academic papers matching natural language queries using the Asta MCP server's semantic search capabilities. This skill leverages Allen AI's scientific corpus containing 225M+ papers and 285M+ searchable passages to find relevant research. </objective>

<quick_start> To search for papers:

code

/asta:paper-search "transformer architectures for computer vision"

The skill will use the mcp__asta__snippet_search tool to find relevant passages, then format results with titles, authors, venues, and relevance snippets. </quick_start>

<success_criteria>

•Returns ranked list of relevant papers with metadata
•Each result includes: title, authors, year, venue, and relevance snippet
•Results are ordered by semantic relevance to the query
•Paper IDs (DOI/ArXiv) are included for verification </success_criteria>

<context> **Prerequisites:** - Asta MCP server must be configured (see plugin README) - API key required for higher rate limits

Data Coverage:

•225M+ papers from all scientific disciplines
•12M+ full-text papers (285M+ passages)
•Sources: Semantic Scholar, arXiv, PubMed, major conferences </context>

<workflow> **Step 1: Parse Query** Extract the user's search intent and any filters: - Main search terms - Venue filters (e.g., "ACL", "NeurIPS") - Date range (e.g., "2023-2024") - Result limit (default: 10)

Step 2: Execute Search Use mcp__asta__snippet_search with parameters:

•query: The search query
•limit: Number of results (default 10, max 100)
•venues: Comma-separated venue filter (optional)

Step 3: Format Results For each result, extract and display:

•Paper title (bold)
•Authors (first 3 + "et al." if more)
•Year and venue
•Relevance snippet (the matching passage)
•Paper link and citation count

Step 4: Offer Follow-up If user wants more details on a specific paper, use mcp__asta__get_paper to fetch full metadata. </workflow>

<output_format> Present results in this structure:

markdown

## Paper Search Results for: "{query}"

**Found {n} relevant papers:**

1. **{Title}** ({Year})
   *{Author1}, {Author2}, et al.* — {Venue}
   > "{Relevant snippet from the paper...}"
   DOI: {doi} | Citations: {count}

2. **{Title}** ({Year})
   ...

</output_format>

<examples> <example number="1"> <input>/asta:paper-search "attention mechanisms in large language models" --limit 5</input> <output> ## Paper Search Results for: "attention mechanisms in large language models"

Found 5 relevant papers:

•
Attention Is All You Need (2017) Vaswani, Ashish et al. — NeurIPS

"We propose a new simple network architecture, the Transformer, based solely on attention mechanisms..." arXiv:1706.03762 | Citations: 95,000+
•
BERT: Pre-training of Deep Bidirectional Transformers (2019) Devlin, Jacob et al. — NAACL

"BERT uses a multi-head self-attention mechanism that allows the model to jointly attend to information..." arXiv:1810.04805 | Citations: 78,000+
</output>

</example> </examples>

<anti_patterns>

•Don't guess paper details - Always use MCP tools to retrieve actual data
•Don't return too many results - Default to 10, respect user limits
•Don't omit paper IDs - Always include DOI/ArXiv for verification
•Don't fabricate citations - Only report actual citation counts from the API </anti_patterns>