Agent skill

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.

Stars 538
Forks 45

Install this agent skill to your Project

npx add-skill https://github.com/agentscope-ai/OpenJudge/tree/main/skills/bib-verify

SKILL.md

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
  • Combined PDF review + BibTeX verification: ../paper-review/SKILL.md

Expand your agent's capabilities with these related and highly-rated skills.

agentscope-ai/OpenJudge

ref-hallucination-arena

Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate, per-field accuracy (title/author/year/DOI), discipline breakdown, and year constraint compliance. Supports tool-augmented (ReAct + web search) mode. Use when the user asks to evaluate, benchmark, or compare models on academic reference hallucination, literature recommendation quality, or citation accuracy.

538 45
Explore
agentscope-ai/OpenJudge

openjudge

Build custom LLM evaluation pipelines using the OpenJudge framework. Covers selecting and configuring graders (LLM-based, function-based, agentic), running batch evaluations with GradingRunner, combining scores with aggregators, applying evaluation strategies (voting, average), auto-generating graders from data, and analyzing results (pairwise win rates, statistics, validation metrics). Use when the user wants to evaluate LLM outputs, compare multiple models, design scoring criteria, or build an automated evaluation system.

538 45
Explore
agentscope-ai/OpenJudge

auto-arena

Automatically evaluate and compare multiple AI models or agents without pre-existing test data. Generates test queries from a task description, collects responses from all target endpoints, auto-generates evaluation rubrics, runs pairwise comparisons via a judge model, and produces win-rate rankings with reports and charts. Supports checkpoint resume, incremental endpoint addition, and judge model hot-swap. Use when the user asks to compare, benchmark, or rank multiple models or agents on a custom task, or run an arena-style evaluation.

538 45
Explore
agentscope-ai/OpenJudge

paper-review

Review academic papers for correctness, quality, and novelty using OpenJudge's multi-stage pipeline. Supports PDF files and LaTeX source packages (.tar.gz/.zip). Covers 10 disciplines: cs, medicine, physics, chemistry, biology, economics, psychology, environmental_science, mathematics, social_sciences. Use when the user asks to review, evaluate, critique, or assess a research paper, check references, or verify a BibTeX file.

538 45
Explore
agentscope-ai/OpenJudge

claude-authenticity

Detect whether an API endpoint is backed by genuine Claude (not a wrapper, proxy, or impersonator) using 9 weighted rule-based checks that mirror the claude-verify project. Also extracts injected system prompts from providers that override Claude's identity. Fully self-contained — copy the code below and run, no extra packages beyond httpx. Use when the user wants to verify a Claude API key or endpoint, check if a third-party Claude service is authentic, audit API providers for Claude authenticity, test multiple models in parallel, or discover what system prompt a provider has injected.

538 45
Explore
agentscope-ai/OpenJudge

rl-reward

Build RL reward signals using the OpenJudge framework. Covers choosing between pointwise and pairwise reward strategies based on RL algorithm, task type, and cost; aggregating multi-dimensional pointwise scores into a scalar reward; pairwise tournament reward for GRPO on subjective tasks (net win rate across group rollouts); generating preference pairs for DPO/RLAIF; and normalizing scores for training stability. Use when building reward models, scoring rollouts for GRPO/REINFORCE, generating preference data for DPO, or doing Best-of-N selection.

538 45
Explore

Didn't find tool you were looking for?

Be as detailed as possible for better results