Citation Verification logo

Citation Verification

Organization
KalarisLabs
citation-verification

Verify that every reference in a manuscript really exists and matches its metadata, catching hallucinated, corrupted or mismatched citations before submission. Use when checking a .bib file or reference list, after an AI assistant drafted citations, when a DOI may point to the wrong paper, when adding missing DOIs, or before camera-ready. Queries Crossref, OpenAlex and arXiv; zero dependencies.

Overview

PublisherKalarisLabs
Repositoryresearch-agent-skills
Skill namecitation-verification
Stars
91
Forks
8
Bundled files
1
LicenseMIT
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.

  • 1 bundled files

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

  • Open source

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

Installation

Install the Citation Verification 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/KalarisLabs/research-agent-skills/tree/main/skills/citation-verification
  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/KalarisLabs/research-agent-skills.git /tmp/research-agent-skills
mkdir -p .claude/skills
cp -r /tmp/research-agent-skills/skills/citation-verification .claude/skills/citation-verification
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Citation Verification 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 Citation Verification 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 Citation Verification 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.

Citation Verification

Language models (and tired humans) produce references that look right but are not: plausible titles that were never published, real DOIs attached to the wrong paper, wrong years, invented co-authors. Citing a paper that does not exist can lead to desk rejection, a correction, or a misconduct inquiry. This skill makes verification systematic.

Non-negotiable rules

  1. Never write a reference from memory. Every entry must come from a retrievable record (Crossref, OpenAlex, arXiv, PubMed, publisher page).
  2. A reference is verified only when its identifier resolves to a record whose title, first author and year all match. A resolving DOI alone proves nothing.
  3. If you cannot verify a reference, say so. Mark it % UNVERIFIED in the .bib, tell the user, and never quietly keep it.
  4. Verify the claim too: open the abstract or the cited section and confirm the paper actually supports the sentence citing it.

Workflow

bash
export CROSSREF_MAILTO=you@university.edu   # polite pool: faster, fewer rate limits
python scripts/verify_citations.py references.bib --json citation-report.json
python scripts/verify_citations.py --doi 10.1038/nature14539 10.1126/science.aaa8415
python scripts/verify_citations.py references.bib --keys smith2020,li2023   # re-check a subset

Each entry gets a status:

StatusMeaningAction
verifiedIdentifier resolves; title/author/year agreeNone
found-add-doiNo DOI in the entry, but an unambiguous match existsAdd the suggested doi field
mismatchDOI resolves to a different work, or year/author disagreeFix from the record, or find the intended paper
doi-not-foundDOI does not resolve anywhereTypo or fabricated: search by title
uncertainTitle matches but year/author disagree, or only a weak title matchCheck manually (reprints, errata, homonymous papers)
not-foundNo plausible match in Crossref, OpenAlex or arXivTreat as fabricated until proven otherwise (grey literature, theses and reports may legitimately be absent)

Exit code 0 means everything is verified or only missing DOIs; 1 means something needs a human.

Handling the hard cases

  • Conference papers without DOIs (NeurIPS, ICML, ICLR, many CS venues): the script falls back to arXiv. Cite the proceedings version with a url to the official proceedings page, and optionally keep eprint for the arXiv ID.
  • Preprint vs published: if both exist, cite the peer-reviewed version unless the venue asks otherwise. OpenAlex links versions of the same work.
  • Books and chapters: check ISBN via the publisher or Open Library. Crossref covers many but not all.
  • Datasets and software: verify DataCite DOIs (https://api.datacite.org/dois/{doi}) or Zenodo/Software Heritage identifiers.
  • Retractions: check each DOI against Retraction Watch data (in Crossref as update-to / relation metadata) and never cite a retracted paper as support.
  • Non-English or old literature: absence from these indexes is common. Confirm via library catalogs and document the source.

Reporting to the user

Summarize as a table: key, status, problem, and the fix you applied or propose. Apply only mechanical fixes automatically (adding a DOI for a found-add-doi match). Anything mismatch, uncertain or not-found requires the user's confirmation because only they know which paper they meant to cite.

Related skills

  • bibtex-hygiene: duplicates, missing fields, capitalization and formatting in the .bib file.
  • citation-management: finding and exporting references from literature databases.
  • literature-review: systematic searching and screening.

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 Citation Verification AI skill do?

Verify that every reference in a manuscript really exists and matches its metadata, catching hallucinated, corrupted or mismatched citations before submission. Use when checking a .bib file or reference list, after an AI assistant drafted citations, when a DOI may point to the wrong paper, when adding missing DOIs, or before camera-ready. Queries Crossref, OpenAlex and arXiv; zero dependencies.

Why use Citation Verification on TypingMind?

Because you install it once and use it with any model. Citation Verification 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 Citation Verification in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/KalarisLabs/research-agent-skills/tree/main/skills/citation-verification. 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 Citation Verification?

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 Citation Verification?

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

Is the Citation Verification AI skill free?

Yes. It is published on GitHub by KalarisLabs under the MIT 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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