Paper Metadata Lookup
SkillDev toolsUse when the user wants full metadata for a paper — from a DOI, PMID, arXiv id, OpenAlex id, or title. Returns title, author list, first author, corresponding author(s), publication date, journal name + ISO-4 abbreviation, impact factor, volume/issue/pages, DOI/PMID, citation count, and abstract in one record. Triggers on "paper metadata", "who is the corresponding author", "first author of", "what journal / impact factor for this DOI/PMID", "cite this paper", "文献元数据", "通讯作者", "第一作者", "影响因子". PROACTIVELY USE when the user pastes a DOI/PMID/arXiv id or paper title and asks about its authors, venue, or impact.
Available today. Use it from your connected AI after setup.
No other account needed.
Connect ahel once, and every AI you use reads what you have installed.
Then ask your AI: use the Paper Metadata Lookup skill
What this skill tells your AI
The instructions your AI receives, as published by agents365-ai/365-skills in plugins/journal-meta/skills/journal-meta/SKILL.md and read by ahel’s review.
Resolve one paper identifier into a full metadata record. Primary source is OpenAlex (free, no API key); Crossref is a fallback for DOIs OpenAlex hasn't indexed. The journal name is enriched by delegating to two sibling skills when installed:
journal-abbrev→ ISO-4 / MEDLINE journal abbreviation (JabRef cache, ~25K journals)journal-if→ curated JCR impact factor
If those skills aren't found, it falls back to AbbrevISO (abbreviation) and
OpenAlex 2yr_mean_citedness (approximate IF) automatically.
Critical rule: Always use journal_meta.py. Never fabricate authors,
corresponding authors, dates, or impact factors — resolve them.
Quick Reference
| User wants... | Command |
|---|---|
| Metadata from a DOI | python3 journal_meta.py "10.1038/s41586-020-2649-2" |
| Metadata from a PMID | python3 journal_meta.py 32939066 |
| Metadata from an arXiv id | python3 journal_meta.py 1706.03762 |
| Metadata from a title | python3 journal_meta.py "Attention is all you need" |
| Process a list | python3 journal_meta.py batch papers.txt |
| Skip impact-factor lookup | python3 journal_meta.py <id> --no-if |
| Skip abbreviation lookup | python3 journal_meta.py <id> --no-abbrev |
| Machine-readable contract | python3 journal_meta.py schema |
The subcommand lookup is optional — a bare identifier works. Identifier type
(DOI / PMID / arXiv / OpenAlex id / title) is auto-detected.
Output format
Stdout is a stable JSON envelope when piped/captured, and a human key-value
view on a TTY. Force it with --format json|human|auto (--json = --format json).
Envelope: { "ok": true, "data": {...}, "meta": { "schema_version", "cli_version", "sources", "latency_ms" } }.
meta.sources records where each field came from (e.g. journal-abbrev (JabRef),
journal-if (local cache), or a fallback), so you can tell curated data from approximations.
Data fields (data)
title, authors (list), author_count, first_author, corresponding_authors
(list; empty if OpenAlex has no corresponding flag for the record),
publication_date, year, journal, journal_abbrev, impact_factor,
impact_factor_source, impact_factor_year, volume, issue, pages,
doi, pmid, openalex, issn, type, is_oa, cited_by_count, abstract.
Exit codes
| Code | Meaning |
|---|---|
0 | success |
1 | runtime / upstream error (retryable) |
2 | validation / bad input (missing file, empty query) |
3 | not found (no paper matched) |
Workflow
- Identify the input. A DOI (
10.x/...), PMID (digits), arXiv id (NNNN.NNNNN), OpenAlex id (W...), or a title string — all auto-detected. Prefer a DOI or PMID: title search returns OpenAlex's single top match, which for very common titles can be a preprint or re-indexed copy rather than the version of record. Confirm the returned DOI/year if the user gave a title. - Run
python3 journal_meta.py <id>. - Present the fields the user asked for. For a full citation, use
first_author,journal_abbrev,year,volume,issue,pages,doi. State theimpact_factor_sourcewhen reporting IF — a curated JCR number and an OpenAlex approximation are not the same thing.
Notes & caveats
- Corresponding author comes from OpenAlex's
is_correspondingflag, which is only populated when the publisher supplied it. An empty list means "not marked in the metadata," not "there is none" — say so rather than guessing. - Impact factor from
journal-ifis curated JCR; the fallback is OpenAlex's 2-year mean citedness, which differs from the official JCR IF. Cite formally only the curated value, and flag approximations. - arXiv ids resolve via the arXiv DataCite DOI (
10.48550/arXiv.<id>); if a preprint isn't indexed there, it falls back to a title search.
Environment variables
| Variable | Effect |
|---|---|
JOURNAL_META_MAILTO / OPENALEX_MAILTO | Email for OpenAlex's polite pool (faster, recommended). |
JOURNAL_ABBREV_CLI | Explicit path to journal-abbrev's jabbrv.py (skips auto-discovery). |
JOURNAL_IF_CLI | Explicit path to journal-if's journal_if.py. |
If the sibling skills live in a non-standard location, set these so enrichment uses their curated data instead of the built-in fallbacks.
Troubleshooting
| Issue | Solution |
|---|---|
| IF shows "OpenAlex ... (approx)" not JCR | journal-if not found — install it or set JOURNAL_IF_CLI. |
| Abbreviation looks wrong / same as full name | Single-word titles (Nature, Cell, Science) are not abbreviated per ISO 4. For others, journal-abbrev gives the ISO-4 form. |
| Title search returned the wrong paper | Use the DOI or PMID instead — title search takes OpenAlex's top hit only. |
not_found on a brand-new DOI | OpenAlex indexing lags; the Crossref fallback covers most, but the newest DOIs may need a day. |
corresponding_authors is empty | The publisher didn't mark it in the metadata; don't infer one. |
Signals
- GitHub stars
- 46
- Forks
- 11
- Last commit
- Sep 2026
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journal-meta- Source
- github.com/agents365-ai/365-skills