paper-fetch
Fetch the PDF for a paper given a DOI (or title). Tries multiple sources in priority order and stops at the first hit.
Resolution order
- Unpaywall —
https://api.unpaywall.org/v2/{doi}?email=$UNPAYWALL_EMAIL, readbest_oa_location.url_for_pdf(skipped ifUNPAYWALL_EMAILnot set) - Semantic Scholar —
https://api.semanticscholar.org/graph/v1/paper/DOI:{doi}?fields=openAccessPdf,externalIds - arXiv — if
externalIds.ArXivpresent,https://arxiv.org/pdf/{arxiv_id}.pdf - PubMed Central OA — if PMCID present,
https://www.ncbi.nlm.nih.gov/pmc/articles/{pmcid}/pdf/ - bioRxiv / medRxiv — if DOI prefix is
10.1101, queryhttps://api.biorxiv.org/details/{server}/{doi}for the latest version PDF URL - Publisher direct (institutional mode only —
PAPER_FETCH_INSTITUTIONAL=1) — DOI-prefix → publisher PDF template (Nature / Science / Wiley / Springer / ACS / PNAS / NEJM / Sage / T&F / Elsevier). The caller's own subscription IP / cookies / EZproxy are what authorize the fetch; unauthorized responses fail the%PDFcheck and fall through to step 7. - Sci-Hub mirrors (on by default; disable with
PAPER_FETCH_NO_SCIHUB=1) — last-resort fallback. Tries the mirror list inPAPER_FETCH_SCIHUB_MIRRORS(or built-in defaultssci-hub.ru,sci-hub.st,sci-hub.su,sci-hub.box,sci-hub.red,sci-hub.al,sci-hub.mk,sci-hub.ee) in order; on full miss, scrapeshttps://www.sci-hub.pub/once per process for fresh mirrors. CAPTCHA / missing-paper pages have no PDF iframe and fall through silently. - Otherwise → report failure with title/authors so the user can request via ILL
CloakBrowser fallback (download layer, opt-in — PAPER_FETCH_CLOAK=1). This is not a separate source: it sits at the download chokepoint, so it applies to any of the sources above. When a resolved PDF URL is blocked by Cloudflare — HTTP 403/429, or a "Just a moment…" HTML interstitial served in place of the file — and the operator opted in, the URL is retried through CloakBrowser (a stealth Chromium that passes the JS challenge) via the cloak_pdf.py companion. Bytes it returns are re-validated through the same %PDF magic-byte + 50 MB checks; on success the result carries via: "cloak". Off by default, fails closed (missing CloakBrowser → silent fall-through), and the agent cannot opt in — see CloakBrowser access below.
If only a title is given, pass it directly via --title "<title>". Resolution chain:
- Crossref
query.title— primary; covers all major journal/conference DOIs - Semantic Scholar
/paper/search/match— fallback when Crossref's top match is low-confidence (match_score < 40) or the gap to the runner-up is< 3. Critically, S2 covers arXiv-only preprints (no Crossref DOI). When S2 surfaces a paper that has only an arXiv id, the canonical10.48550/arXiv.<id>is synthesized so the download chain stays uniform. - Crossref's best guess (low-confidence) — used only when both resolvers struggled. The result envelope sets
meta.title_resolution.low_confidence: trueplus alow_confidence_reason(score_below_threshold/ambiguous_runner_up) so an agent can either bail or confirm via--dry-run.
Either way the resolved DOI, the winning resolver, the full resolvers_tried list, and the top candidate matches are all surfaced under meta.title_resolution.
If semanticscholar-skill is registered, it can serve as a richer pre-step for title → DOI resolution — useful when you also need relevance ranking, snippet search, or citation context, not just a DOI. The agent writes a Python script using the skill's match_title() to read externalIds.DOI, then runs paper-fetch <doi>. When the result has only an ArXiv id (no DOI), synthesize 10.48550/arXiv.<ArXiv> and pass that to paper-fetch.
When only the DOI is needed, --title is the single-command path — paper-fetch's built-in Crossref → S2 chain handles most cases.
Usage
python scripts/fetch.py <DOI> [options]
python scripts/fetch.py --title "<paper title>" [options]
python scripts/fetch.py --batch <FILE|-> [options]
python scripts/fetch.py schema # machine-readable self-description
Flags
The flags below are the ones an agent composes in normal use. For the complete contract — including --dry-run, --pretty, --stream, --overwrite, --timeout, --version, plus parameter types and exit-code mappings — run python scripts/fetch.py schema (machine-readable, drift-checked via schema_version).
| Flag | Default | Description |
|---|---|---|
doi | — | DOI to fetch (positional). Use - to read a single DOI from stdin |
--title TITLE | — | Paper title; resolved to a DOI via Crossref before download. Mutually exclusive with positional DOI / --batch |
--batch FILE | — | File with one DOI per line for bulk download. Use - to read from stdin |
--out DIR | pdfs | Output directory |
--format | auto | json for agents, text for humans. Auto-detects: json when stdout is not a TTY, text when it is |
--idempotency-key KEY | — | Safe-retry key. Re-running with the same key replays the original envelope from <out>/.paper-fetch-idem/ without network I/O |
Agent discovery: schema subcommand
python scripts/fetch.py schema
Emits a complete machine-readable description of the CLI on stdout (no network). Includes cli_version, schema_version, parameter types, exit codes, error codes, envelope shapes, and environment variables. Agents should read this once, cache it against schema_version, and re-read when the cached version drifts.
Output contract
stdout emits a single JSON envelope. Every envelope carries a meta slot.
Success (all DOIs resolved):
{
"ok": true,
"data": {
"results": [
{
"doi": "10.1038/s41586-021-03819-2",
"success": true,
"source": "unpaywall",
"pdf_url": "https://www.nature.com/articles/s41586-021-03819-2.pdf",
"file": "pdfs/Jumper_2021_Highly_accurate_protein_structure_predic.pdf",
"meta": {"title": "Highly accurate protein structure prediction with AlphaFold", "year": 2021, "author": "Jumper"},
"sources_tried": ["unpaywall"]
}
],
"summary": {"total": 1, "succeeded": 1, "failed": 0},
"next": []
},
"meta": {
"request_id": "req_a908f5156fc1",
"latency_ms": 2036,
"schema_version": "1.9.0",
"cli_version": "0.13.1",
"sources_tried": ["unpaywall"]
}
}
Partial (batch mode — some DOIs failed, exit code reflects the failure class):
{
"ok": "partial",
"data": {
"results": [
{ "doi": "10.1038/s41586-021-03819-2", "success": true, "source": "unpaywall", ... },
{
"doi": "10.1234/nonexistent",
"success": false,
"source": null,
"pdf_url": null,
"file": null,
"meta": {},
"sources_tried": ["unpaywall", "semantic_scholar"],
"error": {
"code": "not_found",
"message": "No open-access PDF found",
"retryable": true,
"retry_after_hours": 168,
"reason": "OA availability changes over time; retry after embargo lifts or preprint appears"
}
}
],
"summary": {"total": 2, "succeeded": 1, "failed": 1},
"next": ["paper-fetch 10.1234/nonexistent --out pdfs"]
},
"meta": { ... }
}
The next slot is an array of suggested follow-up commands: re-invoking them retries only the failed subset. Combine with --idempotency-key to make the whole batch safely retriable without re-downloading the already-succeeded items.
Failure (bad arguments, exit code 3):
{
"ok": false,
"error": {
"code": "validation_error",
"message": "Provide a DOI or --batch file",
"retryable": false
},
"meta": { ... }
}
Per-item skipped (destination al