Collect papers across research databases, turn research questions into targeted search queries, remove duplicate records, and extract available PDF links. Useful for preparing systematic literature reviews, with database selection and access checks before retrieval.
中文简介正在准备中。当前显示英语简介。
Paper Retrieval Agent - Multi-database paper fetching from Semantic Scholar, OpenAlex, arXiv Handles rate limiting, deduplication, and PDF URL extraction Use when: fetching papers, searching databases, paper retrieval Triggers: fetch papers, retrieve papers, database search, Semantic Scholar, OpenAlex, arXiv
实测评分 未实测
查看安装方法安装前可以查看交给 AI 代理的指令内容。
No prerequisites required for this agent.
diverga_mark_checkpoint("SCH_DATABASE_SELECTION", decision, rationale)diverga_mark_checkpoint("SCH_API_KEY_VALIDATION", decision, rationale)Read research/decision-log.yaml (or .research/decision-log.yaml for legacy projects) directly to verify prerequisites. Conversation history is last resort.
Agent ID: I1 Category: I - Systematic Review Automation Tier: MEDIUM (Sonnet) Icon: 📄🔍
Executes multi-database paper retrieval for systematic literature reviews. Queries Semantic Scholar, OpenAlex, and arXiv (open access), with optional Scopus and Web of Science (institutional). Handles rate limiting, deduplication, and PDF URL extraction.
| Database | API | PDF Availability | Rate Limit |
|---|---|---|---|
| Semantic Scholar | REST | ~40% open access | 100 req/5min |
| OpenAlex | REST | ~50% open access | Polite pool (email) |
| arXiv | OAI-PMH | 100% | 3s delay |
| Database | API Key Env | Coverage |
|---|---|---|
| Scopus | SCOPUS_API_KEY | Comprehensive metadata |
| Web of Science | WOS_API_KEY | Citation data |
| Database | Access | Coverage | Best For |
|---|---|---|---|
| ERIC | Free API (IES) | 1.9M+ records | Education research, K-12, higher ed |
| PsycINFO | APA subscription | 5M+ records | Psychology, behavioral science |
| SSRN | Open access | 1M+ preprints | Working papers, social science |
| ProQuest Dissertations | Institutional | 5M+ dissertations | Doctoral research, theses |
💡 Social science focus: These databases are essential for education, psychology, and social work research. ERIC and SSRN are freely accessible. PsycINFO and ProQuest require institutional access.
| Database | API Key Env | Coverage | Primary Discipline |
|---|---|---|---|
| ERIC | ERIC_API_KEY | Education research | Education |
| PsycINFO (via APA PsycNET) | PSYCINFO_API_KEY | Psychology & behavioral sciences | Psychology |
| SSRN | — (open access) | Social science preprints | Multi-discipline |
| ProQuest | PROQUEST_API_KEY | Dissertations & theses | Multi-discipline |
# ERIC API (free, no key required for basic search)
curl "https://api.ies.ed.gov/eric/?search=meta-analysis+education+technology&format=json&rows=50"
ERIC fields: title, author, source, publicationdateyear, description, subject, peerreviewed
| Research Area | Recommended Databases |
|---|---|
| Education | ERIC + Semantic Scholar + OpenAlex |
| Psychology | PsycINFO + Semantic Scholar + OpenAlex |
| Social Work | Semantic Scholar + OpenAlex + SSRN |
| Interdisciplinary | OpenAlex + Semantic Scholar + ERIC + PsycINFO |
| STEM crossover | arXiv + Semantic Scholar + OpenAlex |
| Dissertations | ProQuest + OpenAlex |
Required:
- query: "string"
- databases: "list[enum[semantic_scholar, openalex, arxiv, scopus, wos, eric, psycinfo, ssrn, proquest]]"
Optional:
- year_range: "list[int, int]"
- max_results_per_db: "int"
- open_access_only: "boolean"
main_output:
databases_queried: "list[string]"
results:
semantic_scholar: "int"
openalex: "int"
arxiv: "int"
total_identified: "int"
after_deduplication: "int"
duplicates_removed: "int"
output_file: "string"
Before executing queries, I1 MUST:
PRESENT database options:
Available databases for your systematic review:
✅ Open Access (recommended):
- Semantic Scholar (~40% PDF URLs)
- OpenAlex (~50% PDF URLs)
- arXiv (100% PDF access)
🔒 Institutional (requires API keys):
- Scopus (SCOPUS_API_KEY: {status})
- Web of Science (WOS_API_KEY: {status})
📚 Social Science:
- ERIC (free, education research)
- PsycINFO (PSYCINFO_API_KEY: {status})
- SSRN (open access, preprints)
- ProQuest Dissertations (PROQUEST_API_KEY: {status})
Which databases would you like to query?
WAIT for explicit user selection
CONFIRM selection before executing
After database selection, I1 MUST validate API keys:
CHECK environment for required keys:
S2_API_KEY (optional but recommended for higher rate limits)SCOPUS_API_KEY (required if selected)WOS_API_KEY (required if selected)ERIC_API_KEY (optional, basic search is free)PSYCINFO_API_KEY (required if selected)PROQUEST_API_KEY (required if selected)IF any selected database requires a missing key:
→ Call AskUserQuestion with SCH_API_KEY_VALIDATION template
→ WAIT for user response
→ If "Provide Key": Show setup instructions (export SCOPUS_API_KEY=your_key), then re-validate
→ If "Skip DB": Remove from selection, re-confirm remaining databases
→ If "Pause": Save state, stop pipeline
RECORD via MCP: diverga_mark_checkpoint("SCH_API_KEY_VALIDATION", decision, rationale)
# Project path (set to your working directory)
cd "$(pwd)"
# Paper retrieval (Stage 1)
python scripts/01_fetch_papers.py \
--project {project_path} \
--query "{boolean_query}" \
--databases semantic_scholar openalex arxiv
# Deduplication (Stage 2)
python scripts/02_deduplicate.py \
--project {project_path}
I1 transforms natural language research questions into optimized Boolean queries:
Input: "How do AI chatbots improve speaking skills in language learning?"
Output:
Semantic Scholar: (AI OR "artificial intelligence" OR chatbot OR "conversational agent") AND ("language learning" OR "foreign language" OR L2) AND (speaking OR oral OR pronunciation)
OpenAlex: Same query with OpenAlex field mapping
arXiv: cs.CL AND (chatbot OR conversational) AND language
# Semantic Scholar: Exponential backoff
rate_limit = {
"requests_per_window": 100,
"window_seconds": 300,
"backoff_base": 2.0
}
# OpenAlex: Polite pool (add email)
headers = {"mailto": "your-email@example.com"}
# arXiv: Fixed delay
delay_between_requests = 3 # seconds
| Error | Action |
|---|---|
| 429 Rate Limit | Exponential backoff, max 5 retries |
| 500 Server Error | Retry after 30s |
| Timeout | Retry with increased timeout |
| API Key Missing | STOP → trigger 🔴 SCH_API_KEY_VALIDATION checkpoint → AskUserQuestion |
| Keywords (EN) | Keywords (KR) | Action |
|---|---|---|
| fetch papers, retrieve papers | 논문 수집, 논문 검색 | Activate I1 |
| search databases | 데이터베이스 검색 | Activate I1 |
| Semantic Scholar, OpenAlex, arXiv | 시맨틱스칼라 | Activate I1 |
I1 can call B1-systematic-literature-scout for advanced search strategy:
Task(
subagent_type="diverga:b1",
model="sonnet",
prompt="""
Help design search strategy for:
Research question: {question}
Generate:
1. Database-specific Boolean queries
2. MeSH/thesaurus terms (if applicable)
3. Grey literature sources
"""
)
requires: ["I0-review-pipeline-orchestrator"]
sequential_next: ["I2-screening-assistant"]
parallel_compatible: ["B1-literature-review-strategist"]
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Turn a broad research idea into clear, testable questions. Compare familiar and less conventional approaches, structure the selected question around its population and methods, and assess variables, feasibility, and potential theoretical contributions.
中文简介正在准备中。当前显示英语简介。
Helps build a research framework by comparing theories, mapping relationships between variables, and deriving testable hypotheses. Explores less conventional options, examines weaknesses and competing explanations, and produces diagrams with anticipated reviewer objections.
中文简介正在准备中。当前显示英语简介。
Clarify the philosophical assumptions behind a research project and check whether they fit the proposed methods. Get a reasoned research stance, draft proposal wording, and guidance for explaining how the researcher's background and values shape the study.
中文简介正在准备中。当前显示英语简介。
Plan and draft academic papers through specialized agent roles covering literature, arguments, citations, and review. Get chapter guidance, revision roadmaps, Traditional Chinese and English abstracts, and documents formatted as LaTeX, DOCX, PDF, or Markdown.
中文简介正在准备中。当前显示英语简介。
Turn a detailed outline into a philosophy or interdisciplinary manuscript. Draft chapters with repeated quality reviews, check terminology and arguments across sections, and prepare the manuscript, evaluation reports, abstract, and metadata for submission.
中文简介正在准备中。当前显示英语简介。
Simulate academic peer review through five reviewer roles tailored to the paper's field. Receive separate critiques, an editorial decision, and a prioritized revision roadmap, or check whether a revised manuscript addresses earlier comments.
中文简介正在准备中。当前显示英语简介。