asta-literature-search（阿斯塔文献检索）

Find Literature

Search academic literature for papers relevant to a query. The search will return a ranked list of papers with relevance scores, summaries, and supporting snippets.

This is an advanced search, so the query can be long and complex. You may ask the user questions to clarify the topic and refine the query before running the search.

Installation

This skill requires the asta CLI:

# Install/reinstall at the correct version
PLUGIN_VERSION=0.13.0
if [ "$(asta --version 2>/dev/null | grep -oE '[0-9]+\.[0-9]+\.[0-9]+')" != "$PLUGIN_VERSION" ]; then
  uv tool install --force git+https://github.com/allenai/asta-plugins.git@v$PLUGIN_VERSION
fi

Prerequisites: Python 3.11+ and uv package manager

Tools Available

Paper Finder

Run in background for comprehensive searches (30-60s):

# Save to a temporary file with explicit -o parameter (required)
Bash(command="asta literature find 'query' -o /tmp/literature-search-result.json --timeout 300", run_in_background=true)

After the search completes, move the file to .asta/documents/literature/find/ and index it:

# Create directory if it doesn't exist
mkdir -p .asta/documents/literature/find

# Move the result file to the documents directory
mv /tmp/literature-search-result.json .asta/documents/literature/find/

# Index the file using asta-documents
Bash(command="asta documents add file://.asta/documents/literature/find/literature-search-result.json --name='Literature Search: <query>' --summary='Search results for: <query>'")

Browse results with jq:

jq '[.results | sort_by(-.relevanceScore) | .[0:10][] | {title, year, venue, corpusId, score: .relevanceScore, summary: .relevanceJudgement.relevanceSummary}]' <filename>

Go through all highly relevant papers, extracting relevance criteria, snippets, and citation contexts from each.

Semantic Scholar CLI (fast targeted searches)

# Get paper details
asta papers get ARXIV:2005.14165

# Search papers
asta papers search "transformers" --year 2023- --limit 20

# Get citations
asta papers citations ARXIV:2005.14165

# Author search
asta papers author search "Geoffrey Hinton"
asta papers author papers <author_id>

Recommended fields: --fields title,abstract,year,authors,venue,citationCount

JSON Structure

The output is a LiteratureSearchResult with the following structure:

Top level:

• query: string - the search query
• results: array of Paper objects

Each paper in results[]:

• corpusId: int - Semantic Scholar corpus ID
• title: string - paper title
• abstract: string | null - paper abstract
• year: int | null - publication year
• authors: array of {name: string, id: string}
• venue: string | null - publication venue
• url: string | null - Semantic Scholar URL
• citationCount: int | null - number of citations
• relevanceScore: float - 0-1 (higher = more relevant to query)
• relevanceJudgement: object with:

- relevance: int - overall relevance score - relevanceSummary: string - AI explanation of relevance - relevanceCriteriaJudgements: array of per-concept judgements with: - name: string - concept name - relevance: int - relevance for this concept - relevantSnippets: array of supporting text excerpts

• snippets: array of text excerpts from paper body (if open access):

- text: string - excerpt text - sectionTitle: string - section name

• citationContexts: array of citation contexts:

- text: string - how other papers cite this work - sourceCorpusId: int - corpus ID of citing paper

Example access patterns:

# Top 10 papers by relevance
jq '[.results | sort_by(-.relevanceScore) | .[0:10][] | {title, year, score: .relevanceScore}]' <filename>

# Papers with relevance summary
jq '.results[] | {title, summary: .relevanceJudgement.relevanceSummary}' <filename>

# Extract snippets from a specific paper
jq '.results[] | select(.corpusId == 123456) | .snippets[].text' <filename>

Using Results

After a search completes, results can be used by the Literature Report skill.