code-reviewer
FreeDetect whether approved modeling code is Python or MATLAB/Beita Tianyuan and route it to the matching reviewer using the compact named-check review contract.
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Manage and verify references for mathematical modeling contest papers, generating BibTeX entries, checking citation completeness, and ensuring all references are traceable to actual sources.
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See how to installReview the instructions the agent will receive before you install.
Manage and verify references for mathematical modeling contest papers.
This skill checks that every cited reference corresponds to an actual source, verifies that citations are placed where evidence is needed, generates properly formatted BibTeX entries for all references, and ensures that the paper does not contain fabricated citations.
This skill does not search for new papers, write paper sections, select methods, or perform QA on modeling content.
Use this skill:
paper-section-writer has drafted paper sections with citations.quality-assurance-auditor.\cite{...} or bracketed reference markers that need verification.The following should already exist or be provided:
\cite{...} or [1], [2], etc.).workspace/papers/related_paper_analysis.md (if available).workspace/papers/ (if available).Use or request:
paper/sections/*.md or paper/sections/*.tex — paper drafts with citations.workspace/papers/related_paper_analysis.md — literature analysis with paper metadata.workspace/papers/ (PDF, etc.) for metadata extraction..bib file the user has prepared.Inventory all citations in the paper.
\cite{...} commands, [N] markers, or author-year citations.Match citations to source information.
workspace/papers/related_paper_analysis.md — if a paper was analyzed.workspace/papers/.Verify citation appropriateness.
Generate or update BibTeX entries.
@article, @book, @inproceedings, @misc, @techreport.@article: author, title, journal, year, volume, number, pages, doi (if available).@book: author/editor, title, publisher, year, edition (if applicable).@inproceedings: author, title, booktitle, year, pages, doi (if available).@misc: author, title, howpublished, year, note, url (if applicable).AuthorYear or AuthorYearKeyword.Detect potential fabrication.
Produce or update paper/refs.bib.
paper/refs.bib.%% UNVERIFIED — needs author confirmation.Produce a reference audit report.
paper/reference_audit.md.paper/refs.bib — BibTeX file with all verified references.paper/reference_audit.md — Reference audit report.paper/refs.bib% ── Verified references ──────────────────────────────────────────────
@article{Wang2023TOPSIS,
author = {Wang, X. and Li, Y. and Zhang, H.},
title = {Entropy-weight TOPSIS method for multi-criteria urban resilience evaluation},
journal = {Journal of Urban Planning and Development},
year = {2023},
volume = {149},
number = {2},
pages = {04023001},
doi = {10.1061/JUPDD.0000123}
}
@book{Xu2018Modeling,
author = {Xu, Z.},
title = {Mathematical Modeling: Methods and Applications},
publisher = {Higher Education Press},
year = {2018},
edition = {3rd}
}
@misc{COMAP2026,
author = {{COMAP}},
title = {MCM/ICM 2026 Problem A Statement},
howpublished = {Contest problem statement},
year = {2026}
}
% ── UNVERIFIED — needs author confirmation ───────────────────────────
%% UNVERIFIED @article{Someone2024Method,
%% author = {Someone, A.},
%% title = {A Method for Something},
%% journal = {Unknown Journal},
%% year = {2024}
%% }
paper/reference_audit.md# Reference Audit Report
> Last updated: [timestamp]
## 1. Citation Inventory
| # | Citation Key | Appears In | Claim Supported | Status |
|---|-------------|-----------|----------------|--------|
| 1 | `Wang2023TOPSIS` | Q1 Model Construction | "Entropy-TOPSIS is widely used..." | ✅ Verified |
| 2 | `Xu2018Modeling` | Assumptions | "Linear aggregation is common..." | ✅ Verified |
| 3 | `COMAP2026` | Problem Restatement | Problem source | ✅ Verified |
| 4 | `Someone2024Method` | Q3 Model Construction | "This method is optimal..." | ❌ UNVERIFIED |
## 2. Fabrication Risk Assessment
| Citation | Risk Level | Reason |
|----------|-----------|--------|
| `Someone2024Method` | HIGH | No source file found; author name "Someone" appears placeholder-like; no DOI or venue verifiable |
## 3. Missing Citation Suggestions
| Claim | Location | Suggested Citation |
|-------|----------|-------------------|
| "TOPSIS was first proposed by..." | Q1 Model Construction | Hwang & Yoon (1981) — Multiple Attribute Decision Making |
## 4. Recommendations
1. **BLOCKING**: Verify or remove `Someone2024Method` — appears to be fabricated.
2. **SUGGESTION**: Add Hwang & Yoon (1981) as the foundational TOPSIS reference.
3. **SUGGESTION**: Verify all DOIs resolve correctly before final submission.
\cite{...} in the paper must have a corresponding entry in paper/refs.bib.paper/refs.bib must have at minimum: author, title, year..bib file.Before handing off, verify:
\cite{...} in the paper has a BibTeX entry (verified or flagged).Stop and report a blocker if:
This skill must stop instead of guessing when:
When stopping, output:
After producing paper/refs.bib and paper/reference_audit.md, hand off to:
quality-assurance-auditor
— which will include reference verification in the final QA check.
The handoff should include:
paper/refs.bib path.paper/reference_audit.md path.## 1. Citation Inventory
| Citation Key | Status |
|-------------|--------|
| `Hwang1981TOPSIS` | ✅ Verified — from related_paper_analysis.md |
| `Wang2023Entropy` | ✅ Verified — from workspace/papers/wang2023.pdf |
| `COMAP2026` | ✅ Verified — contest problem statement |
| `Xu2018Modeling` | ✅ Verified — user-provided reference |
## 2. Fabrication Risk Assessment
| Citation | Risk | Reason |
|----------|------|--------|
| `Smith2025BestMethod` | HIGH | No paper file found. No metadata in related_paper_analysis.md. Author "Smith" + generic title "Best Method for Evaluation" looks auto-generated. Google Scholar shows no match. |
**Recommendation**: Remove this citation or provide the actual paper. Do not submit the paper with this citation.
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Detect whether approved modeling code is Python or MATLAB/Beita Tianyuan and route it to the matching reviewer using the compact named-check review contract.
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Audit whether the semantic evidence required by the active lean or submission profile exists and is current, without requiring one verbose artifact per skill or an arbitrary number of pass bullets.
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Run scoped or final cross-media consistency checks for mathematical-modeling artifacts, comparing canonical numbers, symbols, parameters, decisions, files, and paper claims without performing full-workspace audits for low-risk changes.
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Map contest attachments to subquestions, audit and clean raw data, and emit one reusable data profile with quality, coverage, imbalance, concentration, and method-readiness evidence for downstream risk screening.
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Build one compact choice card at a genuine mathematical-modeling judgment point. Use before method screening, after a meaningful experiment, or before final claim/freeze approval so the human chooses the trade-off while AI handles mechanical consequences.
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Plan the smallest set of diagnostic, comparison, paper, and appendix figures or tables needed to support verified mathematical-modeling decisions and claims.
The English summary is being prepared. Showing the original description.