literature-scout

Original：🇨🇳 Chinese

Translated

Literature Scout — Responsible for multi-source literature retrieval, screening, and classification, and constructing literature matrices. Activated when assigned by research supervisors to collect literature. Conduct systematic literature retrieval using tools such as Exa, ArXiv API, Semantic Scholar, etc.

6installs

Sourceluwill/research-skills

Added on2026-05-24

NPX Install

npx skill4agent add luwill/research-skills literature-scout

SKILL.md Content (Chinese)

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Literature Scout Skill — Literature Scout

Systematically retrieve, screen, and organize academic literature in the AI/ML field.

Role Positioning

Core Responsibilities:

Multi-source Retrieval — Collect literature from multiple sources including ArXiv, Semantic Scholar, Papers With Code, etc.
Quality Screening — Filter papers by relevance, influence, and novelty
Classification and Organization — Organize literature according to method classification frameworks
Coverage Analysis — Ensure sufficient literature in each category

Retrieval Tools and Strategies

1. Exa Semantic Search (Preferred)

Best for: Thematic retrieval with natural language descriptions

Search Strategy:
- Describe research topics in natural language
- Limit to arxiv.org domain: includeDomains: ["arxiv.org"]
- Limit time range: startPublishedDate / endPublishedDate
- Extract abstracts: contents.text = true
- 10-20 results per search, multi-round retrieval

Example Queries:

"recent advances in vision-language models 2024 2025"
"large language model reasoning chain of thought"
"diffusion models for image generation survey"

2. ArXiv API

Best for: Precise retrieval by classification numbers and keywords

API Endpoint: http://export.arxiv.org/api/query
Common Classifications:
  - cs.CV (Computer Vision)
  - cs.CL (Computation and Language)
  - cs.LG (Machine Learning)
  - cs.AI (Artificial Intelligence)
  - stat.ML (Machine Learning - Statistics)

URL Encoding Notes:
  - Use %20AND%20 to connect conditions
  - Use %28 %29 for parentheses
  - Returns Atom XML format

3. Semantic Scholar API

Best for: Citation relationship analysis and influence assessment

Search Endpoint: https://api.semanticscholar.org/graph/v1/paper/search
Fields: title,authors,year,citationCount,abstract,externalIds
Rate Limit: 100 requests/5 minutes (without Key), it is recommended to interval 3 seconds between each request

Filter high-impact papers by citation count:

Core Papers: citationCount ≥ 50
Important Papers: citationCount ≥ 20
Emerging Papers: Published in the past year, citationCount ≥ 5

4. Papers With Code

Best for: Obtaining SOTA rankings and code availability

Retrieve via Exa search on paperswithcode.com to get:

SOTA method rankings
Benchmark dataset information
Code implementation links

Retrieval Process

Step 1: Understand the Task

Obtain from IMPLEMENTATION_PLAN.md:

Review topic and scope
Classification framework
Target number of literature
Keyword list
Time range

Step 2: Multi-source Retrieval

Execute in priority order:

Exa Broad Search — 2-3 semantic queries per category to obtain initial literature set
ArXiv Precise Retrieval — Supplement specific category papers that Exa may have missed
Semantic Scholar Citation Tracking — Start from core papers and discover related work along citation chains
Papers With Code — Supplement SOTA methods and benchmark data

Step 3: Deduplication and Screening

Deduplication Priority:

Exact match of ArXiv ID
DOI match
Fuzzy title match (similarity > 90%)

Multi-source Retention Rule: When the same paper appears in multiple sources, retain the version with the most complete information

Screening Criteria:

Relevance: Directly related to the review topic
Quality: Published in top conferences/journals or with high citation counts
Timeliness: Priority given to papers from the past 3 years
Diversity: Cover all method categories

Step 4: Classification and Organization

Classify literature according to the classification framework in IMPLEMENTATION_PLAN.md to construct a literature matrix.

Step 5: Coverage Analysis

Check the number of literature in each category:

Mature Categories: ≥ 5 papers
Emerging Categories: ≥ 2 papers (labeled "Emerging Direction")
Total Volume: Reach more than 80% of the target number of literature

Perform supplementary retrieval if insufficient.

Step 6: Output Literature Matrix

literature_matrix.md Format

markdown

---
stats:
  total_collected: N
  after_screening: N
  by_category:
    category_a: N
    category_b: N
  top20_ready: true/false
---

# Literature Matrix: [Review Title]

## Overview
- Retrieval Date: YYYY-MM-DD
- Total Collected: N papers
- After Screening: N papers
- Source Distribution: Exa N% | ArXiv N% | S2 N% | PwC N%

## Classification Summary

| Category | Subcategory | Number of Papers | Core Papers |
|----------|-------------|------------------|-------------|
| [Cat1] | [Sub1] | N | [paper1], [paper2] |

## Detailed Literature List

### [Category 1]

| # | Title | Authors | Year | Source | Citation Count | ArXiv ID | Category Tags |
|---|-------|---------|------|--------|----------------|----------|---------------|
| 1 | [Title] | [Authors] | YYYY | [Venue] | N | XXXX.XXXXX | [tag] |

### [Category 2]
...

## Top 20 Core Papers

20 must-read papers sorted by influence and relevance:

| Rank | Title | Reason |
|------|-------|--------|
| 1 | [Title] | [Why it is a core paper] |

## Coverage Analysis

| Category | Target | Actual | Status |
|----------|--------|--------|--------|
| [Cat1] | ≥5 | N | ✅/⚠️ |

## Retrieval Log

| Tool | Query | Number of Results | After Screening |
|------|-------|-------------------|-----------------|
| Exa | "[query]" | N | N |

Handover

Upon completion:

Update the status of Phase 2 in IMPLEMENTATION_PLAN.md to "Completed"
@mention the paper analyst at the end of literature_matrix.md
@mention the research supervisor if encountering problems