01-paper-review
Review academic papers for correctness, quality, and novelty using OpenJudge's multi-stage pipeline. Supports PDF files and LaTeX source packages…
Use when the user wants help with academic papers or citations but it's unclear which specific workflow fits — reviewing a paper, checking a BibTeX file for fake references, or benchmarking multiple LLMs on reference-recommendation accuracy. Also use when the user mentions paper
$ npx -y skills add agentscope-ai/OpenJudge --skill 00-academic-router --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/00-academic-routerContext preview
The summary Claude sees to decide when to auto-load this skill.
Use when the user wants help with academic papers or citations but it's unclear which specific workflow fits — reviewing a paper, checking a BibTeX file for fake references, or benchmarking multiple LLMs on reference-recommendation accuracy. Also use when the user mentions paper
name: 00-academic-router description: > Use when the user wants help with academic papers or citations but it's unclear which specific workflow fits — reviewing a paper, checking a BibTeX file for fake references, or benchmarking multiple LLMs on reference-recommendation accuracy. Also use when the user mentions paper review, peer review, BibTeX verification, citation checking, reference hallucination, or academic literature accuracy and hasn't specified which of those three tasks they mean. This skill is the entry router for the academic-eval suite: it asks one diagnostic question then routes to the right sub-skill.
Entry router for the `academic-eval` suite. You diagnose what the user actually wants and route them to one of three sub-skills. You don't review papers, verify BibTeX files, or run arena benchmarks yourself — you're the triage desk.
Each sub-skill is self-contained: it carries inline everything it needs, so it can be installed and used on its own.
Ask (unless the user's request already makes the answer obvious):
To route you correctly, which of these matches what you want? a) Review a single paper (PDF or LaTeX source) for correctness/quality/novelty — optionally also check its bibliography b) Check a standalone .bib file for fabricated or mismatched references (no paper review needed) c) Benchmark/compare multiple LLMs on how often they hallucinate references when asked to recommend citations (arena-style, many queries)
**Shortcut rule**: if the user already said "review my paper", "check this PDF", "verify this .bib file", or "compare models on reference hallucination", skip the question — the routing is already clear from their phrasing.
| User says / has | Use workflow | What it does | |---|---|---| | "Review this paper" (PDF or `.tar.gz`/`.zip` TeX source) | `01-paper-review` | Multi-stage review: safety, correctness, quality/novelty score, criticality — optionally + BibTeX check | | "Review this paper AND check its references" | `01-paper-review` | Same pipeline with `--bib` set — one run covers both | | "Just check this .bib file, no paper" | `02-bib-verify` | Cross-checks every entry against CrossRef/arXiv/DBLP, flags `verified`/`suspect`/`not_found` | | "Compare N models on how often they cite fake papers" / "benchmark reference hallucination rate" | `03-ref-hallucination-arena` | Runs many recommendation queries per model, verifies every returned reference, ranks models by hallucination rate | | "Compare models on general quality/response, not specifically citations" | — | Not this suite — see the `arena-eval` suite's `01-auto-arena` instead |
`cookbooks.paper_review` pipeline. Use `01-paper-review` whenever a paper file exists (even if the *only* thing the user cares about is the bibliography — `--bib_only` mode is documented there). Use `02-bib-verify` only when there is **no paper**, just a loose `.bib` file to sanity-check.
two evaluate *one document's* existing references after the fact. The third evaluates *model behavior* — how often a model invents fake citations when asked to recommend some, across a benchmark of queries and models. If the user wants a leaderboard/ranking of models, not a report on one document, route to `03-ref-hallucination-arena`.
Recommended workflow: `[skill-name]` Why: [one sentence tying the user's request to the triage table row]
Recommend exactly one workflow. If the request spans two (e.g., "review this paper, and separately benchmark 3 models on citation accuracy"), say so explicitly and give both, in the order the user would naturally do them.
OpenJudge: A Unified Framework for Holistic Evaluation and Quality Rewards
Review academic papers for correctness, quality, and novelty using OpenJudge's multi-stage pipeline. Supports PDF files and LaTeX source packages…
Verify a BibTeX file for hallucinated or fabricated references by cross-checking every entry against CrossRef, arXiv, and DBLP. Reports each reference as…
Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate,…
Use when the user wants to compare or benchmark multiple LLMs/agents arena-style but it's unclear which specific workflow fits — a general-purpose win-rate…
Automatically evaluate and compare multiple AI models or agents without pre-existing test data. Generates test queries from a task description, collects…
Benchmark LLM reference recommendation capabilities by verifying every cited paper against Crossref, PubMed, arXiv, and DBLP. Measures hallucination rate,…