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Opencite

Community
neuromechanist
opencite

Use this skill for "search for papers", "find citations", "look up a DOI", "get BibTeX", "download PDF", "convert PDF to markdown", "find canonical papers", "convert identifiers", "batch download papers", "configure opencite", "literature review", "find related papers", "what papers cite this", "export references", "read this paper", or mentions of opencite, Semantic Scholar, OpenAlex, PubMed, academic literature search, citation management, or paper retrieval.

Overview

Publisherneuromechanist
Repositoryresearch-skills
Skill nameopencite
Stars
51
Forks
9
Bundled files
3
LicenseBSD-3-Clause
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • 3 bundled files

    Scripts, templates, and references the model can read while it works. Files are read-only and never executed.

  • Open source

    Published by neuromechanist on GitHub. Read the source before you install it.

Installation

Install the Opencite AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
    https://github.com/neuromechanist/research-skills/tree/main/plugins/opencite/skills/opencite
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/neuromechanist/research-skills.git /tmp/research-skills
mkdir -p .claude/skills
cp -r /tmp/research-skills/plugins/opencite/skills/opencite .claude/skills/opencite
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Opencite in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Opencite on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Opencite is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

OpenCite CLI

OpenCite is a CLI tool for academic literature search and citation management. It aggregates results from Semantic Scholar, OpenAlex, PubMed, arXiv, and bioRxiv/medRxiv, deduplicates them, and outputs formatted results. It also supports PDF retrieval, PDF-to-markdown conversion, and batch operations.

Installation

bash
# Recommended
uv pip install opencite

# Alternative: run without installing
uvx opencite --version

PDF conversion support (markitdown and markit-mistral) is included by default. When MISTRAL_API_KEY is set, markit-mistral handles math, tables, and complex layouts. Otherwise, markitdown (free, local) is the fallback.

For development:

bash
uv sync --extra dev

Research Workflow

Follow this end-to-end workflow for literature research, paper retrieval, or reading material on a topic.

1. Search for relevant papers

Choose the search strategy based on the request:

  • Canonical/foundational papers: uvx opencite canonical "topic" --max 10
  • Recent or specific papers: uvx opencite search "query" --max 20 --sort citations
  • Citation graph exploration: uvx opencite cite "DOI" --direction both
  • Combine strategies when appropriate (e.g., canonical for background + search for recent work)

2. Evaluate and select papers

Review results considering citation count, relevance, recency, and open access availability. Present a summary and confirm which papers to retrieve.

3. Download and convert

For multiple papers (preferred): Save search results as JSON and use batch-fetch:

bash
uvx opencite search "topic" --max 10 -f json -o results.json
uvx opencite batch-fetch --from-json results.json --convert -o ./papers --summary report.json

batch-fetch --convert automatically creates this directory structure:

papers/
├── pdf/          # downloaded PDFs
└── markdown/     # converted markdown files
    └── img/      # per-paper image directories (mistral only)

For individual papers:

bash
uvx opencite pdf "10.1234/example" -o papers/pdf/ --convert

Note: pdf --convert places the markdown file next to the PDF and does not extract images. For the organized subdirectory layout with image extraction, use batch-fetch.

4. Read and synthesize

Read the converted markdown files for deeper analysis:

  • Summarize key findings across papers
  • Identify common themes and disagreements
  • When using batch-fetch, markdown is in papers/markdown/ and extracted images (markit-mistral only) are in per-paper subdirectories under papers/markdown/img/
  • Generate BibTeX for citation: uvx opencite lookup "DOI" -f bibtex --append-bib refs.bib

Command Summary

CommandPurpose
searchFind papers matching a query across multiple APIs
lookupLook up a specific paper by DOI, PMID, PMCID, or other identifier
citeGet citing/cited-by papers for a given identifier
canonicalFind the most-cited, foundational papers for a topic
pdfDownload a PDF for a paper by identifier
convertConvert a local PDF file to markdown
idsConvert between identifier types (DOI, PMID, PMCID)
batch-fetchDownload PDFs for multiple papers with optional conversion
configManage opencite configuration (init, show, path)

For full option listings, see references/cli-reference.md.

Configuration Essentials

Initialize configuration and check resolved values:

bash
uvx opencite config init   # create ~/.opencite/config.toml template
uvx opencite config show   # display resolved config (keys masked)

Key environment variables:

  • SEMANTIC_SCHOLAR_API_KEY - Semantic Scholar API
  • PUBMED_API_KEY - NCBI/PubMed API
  • OPENALEX_API_KEY - OpenAlex API (required since Feb 2026)
  • MISTRAL_API_KEY - Enhanced PDF-to-markdown conversion (optional)

For full configuration details including publisher tokens and loading priority, see references/api-keys-and-config.md.

Error Handling

  • Rate limits: Semantic Scholar has aggressive rate limiting (1 req/sec). When rate limit errors occur, wait and retry.
  • Missing API keys: Commands warn about missing keys but still query available sources.
  • Timeouts: Retry the command or try a different source with --source.
  • PDF not found: opencite reports which sources were tried and why each failed. Papers behind paywalls may need institutional access or publisher API tokens.

References

Bundled files

The model reads these on demand while the skill is loaded. They are exposed as readable files and are never executed.

Frequently asked questions

What does the Opencite AI skill do?

Use this skill for "search for papers", "find citations", "look up a DOI", "get BibTeX", "download PDF", "convert PDF to markdown", "find canonical papers", "convert identifiers", "batch download papers", "configure opencite", "literature review", "find related papers", "what papers cite this", "export references", "read this paper", or mentions of opencite, Semantic Scholar, OpenAlex, PubMed, academic literature search, citation management, or paper retrieval.

Why use Opencite on TypingMind?

Because you install it once and use it with any model. Opencite is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Opencite in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/neuromechanist/research-skills/tree/main/plugins/opencite/skills/opencite. TypingMind reads its SKILL.md and bundles its files and installs it as a skill you can enable per chat.

Which AI models can use Opencite?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Opencite?

As many as you like. As long as a model supports skills, you can use Opencite with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Opencite AI skill free?

Yes. It is published on GitHub by neuromechanist under the BSD-3-Clause license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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