Install
openclaw skills install @emp-tca/biomedical-reference-verifierVerify or normalize biomedical and life-science reference lists only when the task is about AI-caused reference errors: whether references really exist, whether DOI/PMID/title/authors/journal/year are wrong, whether a bibliography has false or corrupted entries, or whether references should be reformatted into APA/AMA/GB/T 7714/Vancouver without judging topical relevance. Trigger examples: 帮我核验这些参考文献是不是真实存在; 检查这批 references 里有没有 AI 编造的文献; 这些文献可能是 AI 生成的,请查一下哪些是假的; 请验证这些 APA 引用的 DOI、作者、题名是否对应; 帮我审查参考文献真实性; 检查这些 AMA references 的 DOI 和期刊年份是否正确; 请把这些参考文献改成 AMA 格式; 帮我把参考文献统一成 APA. Do not trigger for general article review, manuscript logic, literature relevance, citation support, or whether papers are suitable for the article.
openclaw skills install @emp-tca/biomedical-reference-verifierUse this skill only for reference-list authenticity checking, AI-caused reference cleanup, and citation-format normalization. Do not use it to judge whether papers are relevant, suitable, or correctly used in the manuscript body unless the user explicitly asks for reference authenticity plus body cleanup.
Always reduce the task to this sequence:
biomedical-reference-verifier.records.v1.Load references/verification_policy.md before classifying authenticity errors, changing severe items, or explaining network/query policy.
--pipeline format-only. Do not query Crossref/PubMed/OpenAlex.verify pipeline.verify with the requested --citation-style; the fixed copy is generated after verification.Do not run AI-assisted per-paper web searching by default. Stop after batch verification and title recovery, then ask the user whether to continue.
Prefer biomedical-reference-verifier.records.v1 JSON/JSONL. If the source is free text, convert it to records first using only values present in the user source. Do not fill missing source fields from Crossref, PubMed, OpenAlex, memory, or plausible guesses.
Minimal record:
{
"schema": "biomedical-reference-verifier.records.v1",
"records": [
{
"index": 1,
"source": {
"original_text": "exact source reference",
"title": "title from source, or empty string",
"authors": ["First Author"],
"year": "2024",
"journal": "Journal from source",
"identifiers": {"doi": "10.xxxx/example", "pmid": "", "urls": []},
"source_lines": [12],
"context": ""
}
}
]
}
Use --input-mode records for standardized JSON/JSONL. Use Markdown worksheet and doi-context modes only for compatibility.
Run from this skill directory:
python3 scripts/verify_references.py refs.md --output-dir /tmp/reference-audit --citation-style ama
Common variants:
python3 scripts/verify_references.py refs.md --pipeline format-only --citation-style ama
python3 scripts/verify_references.py records.json --input-mode records --citation-style ama
python3 scripts/verify_references.py refs.md --pubmed-mode off --openalex-mode off
python3 scripts/verify_references.py refs.md --doi-output append
python3 scripts/verify_references.py refs.md --keep-process-json
python3 scripts/verify_references.py refs.md --cleanup-process-files all
python3 scripts/verify_references.py refs.md --cleanup-process-files normalized_input,extracted_references
Result files:
reference-audit-summary.md: concise chat-ready summary.reference-audit-detail.md: detailed report with evidence links.references.auto-fixed.md or document.auto-fixed.md: fixed/formatted copy; never overwrites the source.Process files retained by default:
reference-normalized-records.json: machine-readable records.reference-normalized-input.md: human-readable parser inspection table.references.extracted.md: raw references extracted before verification.Process files skipped by default:
reference-audit.json: write only with --keep-process-json.Never delete user-requested result files. Delete only process files generated by the script in the selected output directory, and only when the user chooses deletion or --cleanup-process-files is explicit.
After running:
reference-audit-summary.md.