PubMed Citation Verifier v5.1.0

Batch verification of PMID citations via the PubMed E-utilities API. Not just "does this PMID exist" — does this PMID point to the paper you claim? Zero dependencies, pure standard library, fully local.

When to use this skill

Invoke it whenever citation truth matters:

• "Verify / check these PMIDs / this reference list" (before submission or release)
• Auditing citations in AI-generated text (fabricated or mismatched references)
• Spot-checking a systematic review's bibliography
• "Does PMID 12345678 really say X?" — point-of-doubt verification
• Batch QA of a knowledge base's PMID/DOI citations
• Automatic invocation: trigger this skill whenever the user asks to "verify/check/audit" citations, PMIDs, DOIs, arXiv preprints or references — no flags needed for a first pass; add --claims-file when they supply the expected titles.

Trigger priority & tool choice — explicit "verify / check / audit citations, references, PMIDs, DOIs" requests invoke this skill first. cite-holmes is for deep research with machine-verified citations; when a request mixes research and verification, run the research first, then this tool for the final reference audit.

Trigger words

Use this skill when the user's request matches any of: verify PMIDs, check citations, validate references, citation audit, reference check, batch verify references, AI hallucination detection, verify DOI, DOI check, citation formatting, reference formatter, GB/T 7714, 中文文献验证 / 参考文献核查 / 文献排版. A pasted reference list, a .bib/.ris file, a Word .docx document, a PowerPoint .pptx deck, an exported .html page, or a claims CSV are all direct inputs.

Three quick mappings: "帮我验证这几个 PMID 31018962、22213727" → --pmids; "检查我论文参考文献" + a pasted list → --parse-text (or pipe it to --stdin — a pasted list IS the input, no explicit "verify" word needed); "这篇撤稿了该引什么" → --suggest on a retracted entry.

When --claims-file is required: a plain scan verifies existence plus whatever metadata the citation context carries — if a verdict will be acted on (mismatch/partial before submission), feed the expected title+authors via --claims-file for the decisive five-state verdict. Tool boundary: cite-holmes covers deep research with machine-verified citations; this skill is the verification/formatting pass — when a request mixes both, research first, then audit the final reference list here.

Use from Python

The whole tool is one stdlib module — import it without installing anything (full reference: references/python_api.md):

import sys
sys.path.insert(0, "/path/to/pubmed-verifier/scripts")
import verify_pmids as vp

info = vp.fetch_summaries(["31018962"], batch_size=1)["31018962"]
cross = vp.cross_check_citation(
    {"claimed_title": "Classification criteria for autoinflammatory recurrent fevers",
     "claimed_year": "2019"},
    {"title": info["title"], "authors": info["authors"],
     "journal": info["journal"], "pubdate": info["pubdate"]})
print(cross["verdict"], round(cross["confidence"], 2))

Know before you run

Four limits cover 95% of surprises — each has a one-flag workaround:

Everything else below expands on these.

Documentation map — what lives where, so nothing needs hunting:

The five-state verdict

Why existence checks are not enough: a large share of fabricated citations use REAL PMIDs that point to a different paper from the same year/journal/field — in one of our own audits, 4 of 5 "valid" PMIDs were wrong this way. A binary exists/not-exists check misses them all.

Quick start

# Pre-submission final pass in ONE command (v5.0.0): fresh registries
# (--no-cache) + Crossref DOI cross-check (--verify-doi) + correct-PMID
# suggestions (--suggest), no flags to remember
python3 scripts/verify_pmids.py --source /path/to/draft --quick --output report.html

# Paste-and-verify (v5.0.0): a copied reference list straight from the
# clipboard or another command — no temp file needed
pbpaste | python3 scripts/verify_pmids.py --stdin
git show HEAD:refs.txt | python3 scripts/verify_pmids.py --stdin

# Scan a project directory for PMIDs (parses citation context automatically)
python3 scripts/verify_pmids.py --source /path/to/project --output report.html

# Word documents and exported HTML pages are read directly (v4.8.0):
# .docx paragraphs/tables and .html text are extracted in-memory —
# script/style content is ignored, link targets (href) are kept
python3 scripts/verify_pmids.py --source guideline_review.docx --output report.html

# PowerPoint decks too (v4.9.0): every slide in order plus the speaker
# notes (.pptx, a:t text) — patient-education courseware audits directly
python3 scripts/verify_pmids.py --source lecture_deck.pptx --output report.html

# Verify specific PMIDs
python3 scripts/verify_pmids.py --pmids 31018962,22213727

# Mismatch demo: PMID 34078778 is actually a dental-materials paper, so the
# JIA claims below will NOT match it — expect ⚠️ mismatch verdicts
python3 scripts/verify_pmids.py --claims '[{"pmid":"34078778","title":"JIA pathogenesis","authors":["Zaripova"],"journal":"Pediatr Rheumatol Online J","year":"2021"}]' --output report.html

# Claims from a CSV file + suggest correct PMIDs for mismatches
python3 scripts/verify_pmids.py --claims-file claims.csv --suggest --output report.html

# Crossref DOI cross-verification + audit working-paper + BibTeX + full pipeline
python3 scripts/verify_pmids.py --source /path/to/files --verify-doi --suggest --output report.html --export-audit audit.json --export-bibtex refs.bib

# Verify DOIs directly (no PMIDs) + delta audit vs a previous run
python3 scripts/verify_pmids.py --dois "10.1038/nature12968,10.4012/dmj.2020-408" --workers 4 --export-audit audit.json --export-csv table.csv
python3 scripts/verify_pmids.py --source /path/to/project --diff audit.json --output report.html

# Verify arXiv IDs (preprints) — mixed audits supported
python3 scripts/verify_pmids.py --arxivs "2401.12345,cs/0211004" --no-cache

# Pre-flight: are the five data sources reachable right now?
python3 scripts/verify_pmids.py --check-net

# Audit a BibTeX or RIS bibliography file directly (PMID > DOI > arXiv routing)
python3 scripts/verify_pmids.py --bibliography refs.bib --no-cache
python3 scripts/verify_pmids.py --bibliography refs.ris --no-cache --export-ris verified.ris

# Verify a reference list copied from a paper draft (inline IDs route
# exactly; title-only entries resolve via PubMed title search)
python3 scripts/verify_pmids.py --parse-text references.txt --no-cache

# Format the verified entries as a ready-to-paste reference list
# (--citation-style: gbt | vancouver | apa | ama; default gbt)
python3 scripts/verify_pmids.py --parse-text references.txt --format-references refs_gbt.txt --citation-style gbt

# Submission evidence pack: one command, every artifact (audit + HTML +
# BibTeX/RIS + CSV + GB/T list + manifest)
python3 scripts/verify_pmids.py --parse-text references.txt --report-bundle evidence_pack

# Turn a copied reference list into a claims CSV skeleton (fill the gaps,
# then run --claims-file for exact five-state verification)
python3 scripts/verify_pmids.py --claims-template references.txt,claims_skeleton.csv

# Institutional niceties (recommended): NCBI API key + contact email
python3 scripts/verify_pmids.py --source . --verify-doi --ncbi-api-key $NCBI_API_KEY --mailto you@lab.org

What the output looks like

Terminal text report (verdict line, then per-citation evidence):

Readiness: NOT SUBMISSION-READY — 1 invalid, 1 mismatched
Results: 1/3 correct, 1 mismatch, 1 invalid, 0 partial, 0 unknown
============================================================

✅ PMID 31018962 (claims) [correct]
   Actual: Classification criteria for autoinflammatory recurrent fevers
   Claimed: Classification criteria for autoinflammatory recurrent fevers
   Evidence: title ✓ · author ✓ · journal ✓ · year ✓

⚠️ PMID 34078778 (claims) [mismatch]
   Actual: Effect of CAD/CAM materials on the marginal fit of crowds
   Claimed: JIA pathogenesis and treatment
   → Suggest: PMID 34425842 - Juvenile idiopathic arthritis: from aetio...
   Evidence: title ✗ · author ✗ · journal ✗ · year —

❌ PMID 99999999 (cli) [invalid]
   Error: PMID not found in API response

--output report.html renders a self-contained dashboard (inline CSS, no external assets): readiness banner, a filterable verdict table (✅/⚠️/🔶/❌/❓ tabs with per-field ✓✗— evidence columns, retraction and DOI-splice flags highlighted on top), a delta panel when --diff is given, the finding ledger, and a reproducibility footer (redacted command + version + data sources). Open it in any browser — it is also what --report-bundle packs for reviewers.

--output report.json carries the same verdicts plus the full evidence chain per citation (evidence.title_match / author_match / journal_match / year_match, fields tri-state, meta_source naming which registry answered, resolved_by when the title-search/OpenAlex legs matched) and a stats block with the submission-readiness verdict. --format-references writes the ready-to-paste citation list (see the v4.0.0 entry in references/CHANGELOG.md).

FAQ & common mistakes

Top 10 things NOT to do (each is detailed below or in Anti-patterns):

Large batch (hundreds of PMIDs) is slow — how to speed it up? Metadata-only verification queries in batches of 50 with 0.4 s spacing (0.12 s with --ncbi-api-key); cached re-runs are ~5 s. --verify-doi adds one Crossref call per citation and --suggest adds one search per mismatch — skip them for bulk sweeps, run them on the flagged subset.

When must I use --claims-file instead of scanning? Context parsing is heuristic (v3.3.0 guards common abbreviations, exotic formatting can still mis-split). For precise verification — or DOIs in claims (splice detection needs doi) — feed structured JSON/CSV claims.

My citation text is in Chinese — the scan parses little? GB/T 7714-style references (……标题[J]. 刊名, 年… PMID: xxx) parse since v3.9.0 — title/journal comparisons against Latin registries are skipped cross-language, so verdicts rest on year/DOI evidence. Free Chinese prose without a PMID marker still yields little — feed --claims-file for full verdicts regardless of language.

Slow or unstable network (China)? Standard HTTPS_PROXY/HTTP_PROXY env vars are honored natively; raise --timeout; --meta-source europepmc routes via Europe PMC when NCBI is unreachable (per-entry meta_source shows which was used); cached results are reused for 30 days.

More FAQs, the three worked scenarios and the complete tuning playbook live in references/usage_guide.md.

Anti-patterns — things done WRONG

Each entry: the mistake → why it fails → the right way.

1. Treating --pmids output as "fully verified" — existence-only. → Wrong: "all 5 PMIDs exist, so the citations are correct." → Right: existence-checked only; feed --claims-file with titles for real verification (the READY line says so explicitly).
2. Claims without title — author/journal/year alone can never reach correct; the report caps at partial. → Always include titles.
3. Trusting a cached verdict right after publication day — a brand-new PMID may have been cached as not-found by an earlier run, and retraction status is as of cache time. → Final pre-submission check: --no-cache.
4. Assuming "not found" always means fabricated — a Crossref 404 is re-checked at OpenAlex (DataCite/Zenodo/Chinese-registry DOIs live there), so "unknown in both registries" is now the bar; auto-extracted DOIs that 404 in both stay suspects. arXiv IDs removed by moderators also return empty. → Check doi.org / arxiv.org by hand before accusing.
5. Copying the leading ' from CSV cells — that apostrophe is the formula-injection guard, not data corruption. → Strip it after import.
6. Reading the READY line as a quality score — it only means "no problems found among the checks that ran", not "this paper is good".

Boundaries — declared limits

The capability×limit pairs — what each promise covers, where it stops, and the one-flag workaround:

Claims reference format

--claims-file accepts JSON (an array of objects) or CSV. Recognized columns: pmid, title, authors (semicolon/pipe-separated), journal, year, doi, arxiv_id. A row needs one of pmid, arxiv_id or doi; a missing title caps the verdict at partial.

pmid,title,authors,journal,year,doi,arxiv_id
31018962,Candidate criteria for diagnosis of familial...,Gattorno,Ann Rheum Dis,2019,10.1136/annrheumdis-2019-215048,
,Attention Is All You Need,Vaswani,NeurIPS,2017,,1706.03762
,City size and the spreading of COVID-19 in Brazil,Silva Junior;Other,PLOS ONE,2020,10.1371/journal.pone.0239699,

Validate any file offline first: --lint-claims file.csv reports unusable rows, ID shape errors, unknown columns, duplicates and missing titles (no network). Lint wins when combined with verification flags — only the lint runs.

Using it from mainland China — the one page

Everything network-related in one place (each item also lives where it is used):

• Pre-flight: --check-net probes all four registries + arXiv (5 s each) and prints per-host reachability with next steps.
• Registry choice: default --meta-source auto already retries a failed NCBI batch against Europe PMC (no key, generally reachable); --meta-source europepmc forces it.
• Proxy: standard HTTPS_PROXY/HTTP_PROXY env vars are honored on every request; direct-mode automation should unset them (a dead proxy env otherwise masks as unreachable registries).
• Package mirror: ModelScope carries the skill package (modelscope.cn/skills/Docsor/pubmed-verifier) — but verification itself still calls the academic registries at runtime; the mirror only removes the install friction.
• Honest failure: whatever the network does, failures grade unknown (exit 2), never "not found", and are never cached.

Best practices & tuning

Full playbook: references/usage_guide.md (caching, batching, proxies, CI usage).

Recent releases (full history in references/CHANGELOG.md)

• v5.1.0 — structured retraction detail (retraction_type across all three registries; removal newly detected and capped); explicit --pmids/--source precedence warning; mainland-China usage guide one-pager; boundary table gains scale/concurrency rows.
• v5.0.0 — paste-and-verify (--stdin reads a copied reference list straight from the pipe) and --quick, the pre-submission final pass in one flag (--no-cache + --verify-doi + --suggest); FAQ depth (a format-specific "when parsing fails" table); main doc slimmed to ~450 lines.
• v4.9.0 — PowerPoint .pptx decks are read directly (slides in order + speaker notes); verdict-ladder monotonicity: a scanned citation whose only gap is the missing author claim (title matched, journal/year never claimed) grades correct with the evidence route labeled — stronger evidence can no longer grade below a bare existence check.
• v4.8.0 — Word .docx and .html inputs are read directly by --source/--parse-text (in-memory extraction; link targets kept, script/style dropped); title-only citations get a second opinion via PubMed title search — same-PMID corroboration upgrades to correct (honestly labeled), a different-record hit surfaces a wrong-PMID signal, and the leg never manufactures a mismatch.
• Versions v4.7.0 and older — full entries in references/CHANGELOG.md.

Safety & behavior statement

• Single-run CLI: scan → verify → write report → exit. No daemon, no background task, zero runtime downloads/installs (pure standard library, zero dependencies).
• Network access is limited to these official academic registries, all HTTPS: eutils.ncbi.nlm.nih.gov, www.ebi.ac.uk (Europe PMC), api.crossref.org, api.openalex.org, export.arxiv.org — no other hosts; no telemetry, no stats, no data collection — outbound payloads are only the PMID/DOI/titles you asked to verify.
• Your files and reports stay local. Writes go only to the report paths you specify and the SQLite cache under ~/.cache/pubmed-verifier/ (disable with --no-cache).
• The optional NCBI_API_KEY / PUBMED_VERIFIER_MAILTO env vars authenticate/sign YOUR API requests only — they go nowhere else.
• No OS integration: no subprocesses, no services, no permission changes, no scheduled tasks.

How it works

1. Extract + parse context — finds PMID: 12345678 / PubMed URLs in .html .md .txt .htm .json, and parses the surrounding reference into claimed authors / title / journal / year.
2. Fetch metadata (cached) — PubMed esummary in batches of 50, SQLite cache (30 days, --cache-days), 3 retries with backoff. Europe PMC steps in per failed batch when NCBI is unreachable.
3. Cross-check claimed vs actual — dual fuzzy matching: word-level Jaccard overlap ≥ 50% OR SequenceMatcher ≥ 90% on titles; author surname hits; journal containment or NLM abbreviation equivalence; exact year.
4. DOI↔PMID cross-check (automatic when claims include doi) — a claimed DOI differing from the PMID's registered DOI is a splice/fabrication signal (capped at partial).
5. Crossref DOI verification (optional --verify-doi) — resolves each cited DOI via Crossref, compares the registered title with the PubMed record (doi_title_match in JSON), and detects RETRACTED papers (verdict capped at partial). A doi_verified: false with note "crossref unreachable" is a network fact, not a verdict.
6. Suggest the right PMID (optional --suggest) — for mismatches, searches PubMed with the claimed metadata and proposes top-3 candidates. (Suggestion search always uses NCBI, even with --meta-source europepmc.)

Context parsing is heuristic — since v3.3.0, common abbreviations ("U.S.", "e.g.", "vs.") no longer split a title, but exotic formatting still can. For precise verification, feed structured claims via --claims-file.

Performance

Measured on a 225-PMID audit (5 esummary batches): metadata-only verification runs in seconds; cached re-runs take ~5 s. Each batch waits 0.4 s between calls (0.12 s with --ncbi-api-key). Optional extras are per-citation: --verify-doi adds one Crossref call (~0.5–1 s) per cited DOI, and --suggest adds one PubMed search per mismatch.

When to use which tool

• pubmed-verifier (this skill) — fast, batch, targeted: I have a list of PMIDs/DOIs and need to know if they are real and correctly cited.
• cite-holmes — deep research: interrogate every citation of a whole document across multiple databases, with graded confidence reports.

They share the same five-state philosophy and are safe to use together.

Use cases

• Systematic review / meta-analysis reference audits
• Verifying citations in AI-generated content
• Pre-submission self-check of a manuscript's reference list
• Medical knowledge base / teaching material QA
• Pharmacovigilance literature verification

Related tools

Each tool solves one step of reference work; use whichever fits the task.

• cn-med-oa — free Chinese medical literature full-text download & metadata
• cite-holmes — deep research with machine-verified citations
• paper-polisher-pro — academic polishing, terminology & journal precheck
• academic-figures — publication-ready scientific figures in one command
• doc-holmes — layout-preserving PDF translation (in testing)

Typical order: get papers (cn-med-oa), verify citations (this tool or cite-holmes), polish (paper-polisher-pro), make figures (academic-figures), translate PDFs (doc-holmes) — pick whichever step you need.

Files

License

MIT-0 — free to use, modify and redistribute, no attribution required.