skills/43-wentorai-research-plugins/skills/literature/metadata/opencitations-api/SKILL.md
Query open citation data and reference networks via OpenCitations
npx skillsauth add brycewang-stanford/Awesome-Agent-Skills-for-Empirical-Research opencitations-apiInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
3 of 9 scanners reported clean
Some scanners were skipped, did not run, or reported a non-clean status. Review each row below.
OpenCitations is an independent infrastructure organization dedicated to open scholarship and the publication of open bibliographic and citation data. Its main product, the OpenCitations Index of Crossref open DOI-to-DOI citations (COCI), contains over 1.6 billion citation relationships harvested from CrossRef metadata. This makes it the largest fully open citation dataset in the world.
The OpenCitations API allows researchers to programmatically access citation and reference data for any DOI in the index. This is valuable for citation network analysis, bibliometric research, impact assessment, and building literature discovery tools. Unlike proprietary citation databases (Web of Science, Scopus), OpenCitations data is fully open under a CC0 public domain dedication.
The API is free, requires no authentication, and has no published rate limits. It returns data in JSON or CSV format, making it easy to integrate into data analysis pipelines.
No authentication required. The OpenCitations API is fully open and free. No API key, registration, or email is needed. There are no published rate limits, but users should implement reasonable request pacing for large-scale queries. For bulk data access, download the complete COCI dataset from https://opencitations.net/download.
GET https://api.opencitations.net/index/v1/citations/{doi}curl "https://api.opencitations.net/index/v1/citations/10.1038/nature12373"
oci: OpenCitations Identifier for the citation linkciting: DOI of the citing papercited: DOI of the cited paper (the input DOI)creation: date the citation was first recordedtimespan: time between publication of citing and cited papersjournal_sc: whether citing and cited are in the same journal (self-citation indicator)author_sc: whether any author appears in both papers (author self-citation indicator)GET https://api.opencitations.net/index/v1/references/{doi}curl "https://api.opencitations.net/index/v1/references/10.1038/nature12373"
citing is the input DOI and cited are the referenced papers.GET https://api.opencitations.net/index/v1/metadata/{doi}curl "https://api.opencitations.net/index/v1/metadata/10.1038/nature12373"
title, author, year, source_title (journal), volume, issue, page, doi, citation_count, and reference.GET https://api.opencitations.net/index/v1/citation-count/{doi}curl "https://api.opencitations.net/index/v1/citation-count/10.1038/nature12373"
count field indicating the number of citations in the index.No published rate limits. OpenCitations does not enforce strict API quotas. The service runs on academic infrastructure, so users should be respectful. Best practices include pacing requests to 1-5 per second for sustained queries, caching results, and using the bulk dataset download for large-scale network analyses. The API may return HTTP 503 under heavy load.
Map the citation relationships around a seminal paper:
# Get all papers citing the target paper
curl -s "https://api.opencitations.net/index/v1/citations/10.1145/3292500.3330672" | jq '.[].citing'
# Get all papers referenced by the target paper
curl -s "https://api.opencitations.net/index/v1/references/10.1145/3292500.3330672" | jq '.[].cited'
Filter out self-citations when computing impact metrics:
curl -s "https://api.opencitations.net/index/v1/citations/10.1038/nature12373" | jq '[.[] | select(.author_sc == "no")] | length'
Retrieve citation counts for multiple papers in a batch:
# Multiple DOIs separated by double underscore
curl -s "https://api.opencitations.net/index/v1/metadata/10.1038/nature12373__10.1126/science.aaa8685__10.1016/j.cell.2015.05.002" | jq '.[] | {doi: .doi, title: .title, citations: .citation_count}'
tools
Recommend AND run open-source AI tools, agents, Claude Code / Codex skills, and MCP servers for any stage of a literature review — searching, reading, extracting, synthesizing, screening, citation-checking, and paper writing. Use when the user asks "what tool should I use to..." OR "install/run/use <tool> to ..." for research/lit-review work: automating a survey or related-work section, PDF→Markdown extraction for LLMs (MinerU/marker/docling), PRISMA / systematic review (ASReview), citation-backed Q&A over PDFs (PaperQA2), wiring papers into Claude/Cursor via MCP (arxiv/paper-search/zotero servers), or chatting with a Zotero library. Ships a launcher (scripts/litrun.py) that installs each tool in an isolated venv and runs it. Curated catalog of 70+ vetted projects. 支持中英文(用于「文献综述工具选型」与「一键安装/运行」)。
development
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
documentation
Use when the project collects primary data or runs a field, lab, or survey experiment, before the intervention begins — write the pre-analysis plan, size the sample from a power calculation, and register with the AEA RCT Registry. Apply after the design is chosen in aer-identification and before any outcome data are seen.
tools
Guide economists to authoritative data sources with explicit, confirmed data specifications before retrieval; interfaces with Playwright MCP to navigate portals and extract real data, not articles about data.