Lit Review Verify

Citation Verification

Read a manuscript (.tex or .md), extract every substantive claim paired with a citation, and verify whether the cited paper actually supports that claim. Also suggest better or more appropriate references where the current citation is weak. The goal is to catch misattributions, stale references, and unsupported claims before a referee does.

Input Parsing

Parse $ARGUMENTS for:

• Path to manuscript (required): A .tex or .md file to check.
• --bib path (optional): Explicit path to the .bib file. If omitted for .tex files, look for \bibliography{...} or \addbibresource{...} and resolve relative to the .tex file's directory. For .md files, look for a .bib file with the same base name in the same directory.
• --section filter (optional): intro, litreview, or all (default: all). For .tex files, section boundaries are detected by \section{...} commands; match liberally. For .md files, use ## Section Name headers.

If no arguments provided, search the current working directory for .tex and .md files and ask which one to process.

Workflow

Phase 1: Extract Claim-Citation Pairs

Step 1: Read the manuscript and detect format

Determine if the file is LaTeX (.tex) or Markdown (.md).

For .tex files: Identify all sentences containing a citation command (\cite, \citet, \citep, \citeauthor, \citeyear, \citealt, \citealp, or natbib/biblatex variants). Extract the claim text, citation key(s), and line number.

For .md files: Identify all sentences containing inline citations in academic format:

• "Author (Year)" or "Author (Year, Journal)" e.g., "Hsieh and Klenow (2009, QJE)"
• "Author and Author (Year)" e.g., "Midrigan and Xu (2014, AER)"
• "Author, Author, and Author (Year)" e.g., "Gopinath, Kalemli-Ozcan, Karabarbounis, and Villegas-Sanchez (2017, QJE)"
• "Author et al. (Year)" e.g., "Bai et al. (2024)"
• Parenthetical: "(Author, Year)" or "(Author and Author, Year)"

For each citation, extract:

• The claim text: the sentence or clause making a substantive assertion.
• The citation metadata: author name(s), year, and journal (if present). These are used for DOI resolution.
• The location: line number in the file.

Step 2: Filter out non-substantive citations

Skip citations that don't make a verifiable claim:

• Parenthetical "see also" lists with no specific claim
• Self-citations to the current paper
• Citations in acknowledgments, appendix references to data sources, or bibliographic metadata

When in doubt, include rather than exclude.

Step 3: Classify each pair

Step 4: Proceed directly to verification

Do NOT stop for user review. The extraction is internal bookkeeping. Proceed immediately to Phase 2.

Phase 2: Resolve Citations

Step 1: Parse the .bib file (if available)

Read any .bib file(s). For each citation key, extract: title, author, year, journal, DOI, abstract (if present). If no .bib file exists (common for .md lit reviews), proceed with the metadata extracted from inline citations in Phase 1.

Step 2: Query Zotero

Use immutable URI mode to avoid locking conflicts:

sqlite3 "file:$HOME/Zotero/zotero.sqlite?mode=ro&immutable=1"

For citations WITH a DOI (from .bib), batch-query by DOI. For citations WITHOUT a DOI, use title matching (normalize: strip {} braces, lowercase, collapse whitespace, use LIKE). For .md files with only author/year, query by author last name + year.

For each citation, retrieve: (1) abstract, (2) whether it exists in Zotero, (3) PDF attachment path.

Batch queries: see references/zotero-queries.md (abstracts by DOI, PDF paths by DOI, title fallback).

Phase 2b: Resolve DOIs for Citations Without One

Many citations (especially from .md files without a .bib) will lack DOIs after Phase 2. DOIs are essential for reliable abstract retrieval. Resolve them now.

For every citation that has no DOI after Zotero lookup, use mcp__bib-cleaner__crossref_fuzzy_match with a bibliographic query string constructed from the citation metadata:

• Query = "AuthorLastName Title Year" (if title is known from .bib or Zotero)
• Query = "AuthorLastName1 AuthorLastName2 Year JournalAbbrev" (if only inline citation metadata)

Launch all fuzzy match queries in a single parallel batch. For each result, accept the DOI if the returned title similarity score is > 70 (CrossRef scores on 0-100 scale) AND the year matches. Record the resolved DOI for use in Phase 3.

Example: For an inline citation "Hsieh and Klenow (2009, QJE)", the query would be:

"Hsieh Klenow 2009 Quarterly Journal of Economics"

Phase 3: Fetch Abstracts and Verify

For each citation that still lacks an abstract after Phase 2/2b, fetch via MCP tools. The fallback chain is designed to degrade gracefully when any API is unavailable.

Pre-check: Scopus health test. Before any Scopus calls, run ONE test call with a known DOI (e.g., 10.1093/qje/qjt031). If it returns an auth error (401/403) or times out, skip ALL Scopus calls for the rest of this run and log "Scopus unavailable" in the report. Do not waste time on N failing calls.

Round 1 (parallel): For citations WITH a DOI, launch mcp__bib-cleaner__crossref_doi_lookup for all of them. CrossRef is free, requires no auth, and returns abstracts for ~60% of economics papers. Simultaneously, for citations still WITHOUT a DOI, launch mcp__bib-cleaner__crossref_fuzzy_match again with broader queries.

Round 2 (parallel, for citations still missing abstracts): Launch mcp__bib-cleaner__semantic_scholar_paper for all citations that have a DOI but no abstract. Semantic Scholar has good coverage and returns abstracts that CrossRef sometimes lacks. Also launch mcp__bib-cleaner__semantic_scholar_search for any citations still without a DOI.

Round 3 (parallel, still missing, only if Scopus passed health check): Launch mcp__bib-cleaner__scopus_abstract_retrieval for remaining citations with DOIs. Scopus has the best coverage for Elsevier journals (JFE, JDE, JIE) but requires a valid API key.

Round 4 (last resort, parallel): For any citations still without abstracts:

• Launch mcp__bib-cleaner__openalex_search for title-based search
• Launch mcp__bib-cleaner__repec_ideas_search for working papers (NBER, CEPR, Fed series)

This yields at most 4 sequential rounds, each fully parallel across citations.

Verification logic:

For each claim-citation pair, compare the claim against the abstract (and any Zotero notes). Apply different strictness levels based on claim type:

Assign a verdict to each pair:

Be conservative with MISMATCH. Abstracts are summaries; the full paper may contain supporting evidence not mentioned in the abstract. When there is ambiguity, prefer UNCERTAIN over MISMATCH.

Phase 3b: Parallel PDF Re-verification

After abstract-based verification, revisit any citation with verdict UNCERTAIN or PARTIAL that has a PDF in Zotero. The goal is to upgrade the verdict using the actual paper content.

How to resolve PDF paths: Zotero stores paths in two formats:

• attachments: prefix: Replace with ~/Library/CloudStorage/Dropbox-Matray/Adrien Matray/Zotero_Library/
• storage: prefix: Find the actual file with find ~/Zotero/storage -name "FILENAME" where FILENAME is the part after storage:

Run PDF checks in parallel using agents. For each UNCERTAIN/PARTIAL citation with a PDF, spawn an Agent with:

• The exact claim text and its location
• The citation metadata (author, year, title, journal)
• The resolved PDF path
• The current verdict and why it was UNCERTAIN/PARTIAL
• Instruction: read pages 1-5 of the PDF. If the claim references a specific table or result, read those pages too. Return a revised verdict with a one-sentence justification.

Batching: Launch up to 5 agents in a single message. Prioritize FINDING claims first, then FACTUAL, then METHOD.

Phase 3c: Search for Better References

After verification, search for potentially better or more appropriate references. This phase catches cases where a cited paper is tangentially related but a better reference exists.

When to search: Only for claims with verdicts PARTIAL, MISMATCH, UNCERTAIN, or UNVERIFIABLE. Do NOT search for SUPPORTED claims (if the citation is correct, leave it alone).

How to search:

1. For PARTIAL/MISMATCH claims: Use mcp__bib-cleaner__openalex_search with keywords extracted from the claim text to find papers whose titles/topics more directly match the claim. Also use mcp__bib-cleaner__openalex_citing_papers on the cited paper to find newer work that extends or refines the result.

2. For UNCERTAIN/UNVERIFIABLE claims: Use mcp__bib-cleaner__crossref_fuzzy_match and mcp__bib-cleaner__semantic_scholar_search with the claim keywords to find papers that might be the intended reference (typo in author name, wrong year, etc.) or a better alternative.

Criteria for suggesting an alternative:

• The alternative paper's abstract more directly supports the specific claim being made
• The alternative is published in a peer-reviewed journal (prefer published over working papers)
• The alternative has a meaningful citation count (not obscure)
• For "newer work" suggestions: the alternative is more recent AND makes the same or stronger point

Do NOT suggest alternatives when:

• The claim is SUPPORTED (the current citation works fine)
• The alternative is only marginally better
• The alternative is a working paper version of the same published paper
• The claim is GENERAL (broad literature references don't need optimization)

Launch all alternative-reference searches in parallel. Limit to 1-2 alternatives per claim.

Phase 4: Output Report

Create the output directory if needed, then save:

output/citation-verification-YYYY-MM-DD.md

Report structure: follow templates/report-template.md exactly.

Present the report summary to the user inline as well (not just the file). Only show the issues, never list SUPPORTED citations.

Implementing Suggestions

Each MISMATCH and PARTIAL issue is numbered as "Suggestion N" (sequentially). When the user says "implement suggestion N" (or "accept N", "apply N", etc.):

1. Read the current file to locate the exact text to replace.
2. Apply the suggested fix using the Edit tool.
3. If the fix introduces a new citation key, add the bib entry to the .bib file.
4. Confirm the change with the file path and line number.

Multiple suggestions can be implemented at once (e.g., "implement suggestions 1 and 3").

Writing suggested fixes:

• The suggested fix must be a drop-in replacement for the exact text shown in the "Claim" field.
• Preserve the original sentence structure and style. Only change what is necessary.
• For PARTIAL matches where the claim overstates a finding, soften the language rather than removing the citation entirely.
• Always provide a bib entry block if the fix introduces a citation key not present in the .bib file.

Rules

• Never use em dashes. Use commas, semicolons, or parentheses instead.
• Never fabricate abstracts or paper content. Every verification must be based on actual retrieved text.
• Always use immutable URI mode for Zotero queries.
• Be conservative with MISMATCH verdicts. When in doubt, mark UNCERTAIN.
• Respect the user's domain: this is applied macro/finance. Understanding econometric terminology (DiD, IV, RDD, shift-share) helps classify claims correctly.
• If MCP tools fail or are unavailable, report which citations could not be verified rather than silently skipping them. Log API status in the report summary.
• Do NOT stop after Phase 1. Run the entire pipeline (extract, resolve, verify, search alternatives, report) in one uninterrupted pass.
• The DOI resolution step (Phase 2b) is critical. Without DOIs, most abstract-retrieval APIs are useless. Always attempt CrossRef fuzzy match before declaring a citation unresolvable.