How do I install the Bib Verify skill?

Run npx skillmds@latest add aibot88/bib-verify in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

Is Bib Verify safe to use?

This skill has not completed SkillMD's automated safety review yet. Independent scanners report: SkillSpector: PASS, Skill Scanner: PASS. Capability flags: docs only. SkillMD never runs a skill's scripts for you; review the SKILL.md before installing.

Which AI agents work with Bib Verify?

This skill is tagged as working with Claude Code, Claude.ai, OpenAI Codex. SKILL.md is an open format, so most agents that read a skills directory can load it too.

Is Bib Verify free to use?

Yes. Installing skills from SkillMD is free, and the skill stays under its author's original license.

Who published Bib Verify?

aibot88 (@aibot88) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Bib Verify by aibot88 — Agent Skill

Name: Bib Verify
Rating: 4.2 (5 reviews)
Author: aibot88

Bib Verify

Verify a BibTeX file for hallucinated or fabricated references by cross-checking every entry against CrossRef, arXiv, and DBLP. Reports each reference as verified, suspect, or not found, with field-level mismatch details (title, authors, year, DOI). Use when the user wants to check a .bib file for fake citations, validate references in a paper, or audit bibliography entries for accuracy.

aibot88 Updated Sep 9, 2026 3 repo stars

File contents

BibTeX Verification Skill

Check every entry in a .bib file against real academic databases using the OpenJudge PaperReviewPipeline in BibTeX-only mode:

Parse — extract all entries from the .bib file
Lookup — query CrossRef, arXiv, and DBLP for each reference
Match — compare title, authors, year, and DOI
Report — flag each entry as verified, suspect, or not_found

Prerequisites

pip install py-openjudge litellm

Gather from user before running

Info	Required?	Notes
BibTeX file path	Yes	`.bib` file to verify
CrossRef email	No	Improves CrossRef API rate limits

Quick start

# Verify a standalone .bib file
python -m cookbooks.paper_review --bib_only references.bib

# With CrossRef email for better rate limits
python -m cookbooks.paper_review --bib_only references.bib --email your@email.com

# Save report to a custom path
python -m cookbooks.paper_review --bib_only references.bib \
  --email your@email.com --output bib_report.md

Relevant options

Flag	Default	Description
`--bib_only`	—	Path to `.bib` file (required for standalone verification)
`--email`	—	CrossRef mailto — improves rate limits, recommended
`--output`	auto	Output `.md` report path
`--language`	`en`	Report language: `en` or `zh`

Interpreting results

Each reference entry is assigned one of three statuses:

Status	Meaning
`verified`	Found in CrossRef / arXiv / DBLP with matching fields
`suspect`	Title or authors do not match any real paper — likely hallucinated or mis-cited
`not_found`	No match in any database — treat as fabricated

Field-level details are shown for suspect entries:

title_match — whether the title matches a real paper
author_match — whether the author list matches
year_match — whether the publication year is correct
doi_match — whether the DOI resolves to the right paper

Additional resources

Full pipeline options: ../paper-review/reference.md
Combined PDF review + BibTeX verification: ../paper-review/SKILL.md

---name: bib-verifydescription: Verify a BibTeX file for hallucinated or fabricated references by cross-checking every entry against CrossRef, arXiv, and DBLP. Reports each reference as verified, suspect, or not found, with field-level mismatch details (title, authors, year, DOI). Use when the user wants to check a .bib file for fake citations, validate references in a paper, or audit bibliography entries for accuracy.--- # BibTeX Verification Skill Check every entry in a `.bib` file against real academic databases using the OpenJudge `PaperReviewPipeline` in BibTeX-only mode: 1. **Parse** — extract all entries from the `.bib` file 2. **Lookup** — query CrossRef, arXiv, and DBLP for each reference 3. **Match** — compare title, authors, year, and DOI 4. **Report** — flag each entry as `verified`, `suspect`, or `not_found` ## Prerequisites ```bash pip install py-openjudge litellm ``` ## Gather from user before running | Info | Required? | Notes | |------|-----------|-------| | BibTeX file path | Yes | `.bib` file to verify | | CrossRef email | No | Improves CrossRef API rate limits | ## Quick start ```bash # Verify a standalone .bib file python -m cookbooks.paper_review --bib_only references.bib # With CrossRef email for better rate limits python -m cookbooks.paper_review --bib_only references.bib --email your@email.com # Save report to a custom path python -m cookbooks.paper_review --bib_only references.bib \ --email your@email.com --output bib_report.md ``` ## Relevant options | Flag | Default | Description | |------|---------|-------------| | `--bib_only` | — | Path to `.bib` file (required for standalone verification) | | `--email` | — | CrossRef mailto — improves rate limits, recommended | | `--output` | auto | Output `.md` report path | | `--language` | `en` | Report language: `en` or `zh` | ## Interpreting results Each reference entry is assigned one of three statuses: | Status | Meaning | |--------|---------| | `verified` | Found in CrossRef / arXiv / DBLP with matching fields | | `suspect` | Title or authors do not match any real paper — likely hallucinated or mis-cited | | `not_found` | No match in any database — treat as fabricated | **Field-level details** are shown for `suspect` entries: - `title_match` — whether the title matches a real paper - `author_match` — whether the author list matches - `year_match` — whether the publication year is correct - `doi_match` — whether the DOI resolves to the right paper ## Additional resources - Full pipeline options: [../paper-review/reference.md](../paper-review/reference.md) - Combined PDF review + BibTeX verification: [../paper-review/SKILL.md](../paper-review/SKILL.md)

Frequently asked questions