| name | literature-overview |
| description | Quick landscape scan — discover papers on a topic without full-text reading |
| type | sop |
| layer | sop |
| agents | ["alphaxiv","semantic-scholar"] |
| tools | {"alphaxiv":["discover_papers"],"semantic-scholar":["relevanceSearch"]} |
| input | query (string) |
| output | PaperList[] with title, authors, year, citationCount, abstract snippet |
| dependencies | {"sops":["literature-research","literature-search"]} |
Literature Overview SOP
Layer Rules
- Layer: sop — wraps MCP tools directly
- Called by: Any tactic or strategy requiring a quick literature landscape scan
- Calls: alphaxiv MCP tools, semantic-scholar MCP tools (never calls other SOPs)
Purpose
Fast landscape scan. Understand what papers exist on a topic, who the key authors are, and rough citation counts. No full-text reading. This skill is for orientation — getting a bird's-eye view before committing to deeper reading.
Use this when you need to:
- Quickly assess how much literature exists on a topic
- Identify key papers and authors in a field
- Get citation counts to gauge paper impact
- Decide which papers deserve deeper reading (via literature-search or literature-research)
Tools
| Tool | Purpose | Returns |
|---|
alphaxiv.discover_papers | Semantic search for arXiv papers | Ranked paper list with title, abstract snippet, arXiv ID |
ss.relevanceSearch | Keyword search across all venues | Title, abstract, authors, year, citationCount, paperId |
Tool Roles
- alphaxiv.discover_papers = primary search for arXiv-covered fields (CS, math, physics, stats, EE, quant-bio/finance)
- ss.relevanceSearch = supplementary search for non-arXiv papers (biomedical, clinical, social science, humanities)
HARD-GATE
**This skill returns abstracts and metadata ONLY.**
Do NOT draw conclusions about:
- Methodology details
- Experimental results
- Specific contributions or findings
- Comparative analysis between papers
Abstracts are for ORIENTATION — identifying what exists and what looks promising.
For any substantive analysis, escalate to:
literature-search — read AI-summarized reports (medium depth)literature-research — read raw full text (deep)
Treating abstracts as sufficient for research conclusions is PROHIBITED.
Workflow
Step 1: Search arXiv via alphaxiv
alphaxiv.discover_papers(
keywords: ["keyword1", "keyword2", "keyword3"],
question: "Detailed semantic description of desired papers",
difficulty: 3
)
