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Skills/agents365-ai/365-skills/paper-fetch
paper-fetch logo

paper-fetch

agents365-ai/365-skills
622 installs9 stars
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Installation

npx skills add https://github.com/agents365-ai/365-skills --skill paper-fetch

Summary

Use whenever the user wants to obtain, download, or fetch a paper's PDF — given a DOI, an arXiv id, a paper title, a citation, or a list of DOIs. Trigger on phrases like "download this paper", "find the PDF for [DOI]", "grab me the [Nature/bioRxiv/arXiv] paper on X", "get the open-access version", "I need this article", or any bulk/batch paper download request, even when the user doesn't explicitly say "PDF" or "DOI". Resolves via Unpaywall → Semantic Scholar → arXiv → PubMed Central → bioRxiv/medRxiv → publisher direct (institutional opt-in) → Sci-Hub mirrors as last-resort fallback.

SKILL.md

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

  1. Unpaywall — https://api.unpaywall.org/v2/{doi}?email=$UNPAYWALL_EMAIL, read best_oa_location.url_for_pdf (skipped if UNPAYWALL_EMAIL not set)
  2. Semantic Scholar — https://api.semanticscholar.org/graph/v1/paper/DOI:{doi}?fields=openAccessPdf,externalIds
  3. arXiv — if externalIds.ArXiv present, https://arxiv.org/pdf/{arxiv_id}.pdf
  4. PubMed Central OA — if PMCID present, https://www.ncbi.nlm.nih.gov/pmc/articles/{pmcid}/pdf/
  5. bioRxiv / medRxiv — if DOI prefix is 10.1101, query https://api.biorxiv.org/details/{server}/{doi} for the latest version PDF URL
  6. 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 %PDF check and fall through to step 7.
  7. Sci-Hub mirrors (on by default; disable with PAPER_FETCH_NO_SCIHUB=1) — last-resort fallback. Tries the mirror list in PAPER_FETCH_SCIHUB_MIRRORS (or built-in defaults sci-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, scrapes https://www.sci-hub.pub/ once per process for fresh mirrors. CAPTCHA / missing-paper pages have no PDF iframe and fall through silently.
  8. 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:

  1. Crossref query.title — primary; covers all major journal/conference DOIs
  2. 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 canonical 10.48550/arXiv.<id> is synthesized so the download chain stays uniform.
  3. Crossref's best guess (low-confidence) — used only when both resolvers struggled. The result envelope sets meta.title_resolution.low_confidence: true plus a low_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).

FlagDefaultDescription
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 DIRpdfsOutput directory
--formatautojson 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 already exists, no --overwrite):

{
  "doi": "10.1038/s41586-021-03819-2",
  "success": true,
  "source": "unpaywall",
  "pdf_url": "https://...",
  "file": "pdfs/Jumper_2021_...pdf",
  "skipped": true,
  "skip_reason": "file_exists",
  "sources_tried": ["unpaywall"]
}

Idempotency replay (re-run with the same --idempotency-key):

The cached envelope is returned verbatim, but meta.request_id and meta.latency_ms are re-stamped for the current call, and meta.replayed_from_idempotency_key is set. No network I/O occurs.

Stderr progress (NDJSON)

When --format json, stderr emits one JSON object per line for liveness:

{"event": "session",     "request_id": "req_...", "elapsed_ms": 0,    "cli_version": "0.13.1", "schema_version": "1.9.0"}
{"event": "start",       "request_id": "req_...", "elapsed_ms": 2,    "doi": "10.1038/..."}
{"event": "source_try",  "request_id": "req_...", "elapsed_ms": 2,    "doi": "...", "source": "unpaywall"}
{"event": "source_hit",  "request_id": "req_...", "elapsed_ms": 2036, "doi": "...", "source": "unpaywall", "pdf_url": "..."}
{"event": "download_ok", "request_id": "req_...", "elapsed_ms": 4120, "doi": "...", "file": "..."}

Event types: session, start, source_try, source_hit, source_miss, source_skip, source_enrich, source_enrich_failed, download_ok, download_error, download_skip, dry_run, not_found. All events share request_id and elapsed_ms, letting an orchestrator correlate progress across stderr and the final stdout envelope. The session event fires once per invocation, before any DOI work or network I/O, and carries cli_version / schema_version so agents can detect schema drift against a cached copy without waiting for the final envelope.

source_enrich fires when Semantic Scholar is called purely to backfill missing author / title after another source already provided the PDF URL; its fields array lists exactly which fields were filled in. source_enrich_failed fires when that enrichment call fails — the Unpaywall PDF URL is still used and the filename falls back to unknown_<year>_….

When --format text, stderr emits human-readable prose.

Exit codes

CodeMeaningRetryable class
0All DOIs resolved / previewed—
1Unresolved — one or more DOIs had no OA copy; no transport failureNot now (retry after retry_after_hours)
2Reserved for auth errors (currently unused)—
3Validation error (bad arguments, missing input)No
4Transport error (network / download / IO failure)Yes

The taxonomy lets an orchestrator route failures deterministically: exit 4 is worth retrying immediately, exit 1 is not, exit 3 is a bug in the caller.

Error codes in JSON

Every retryable error carries a retry_after_hours hint in the error object, so an orchestrator can schedule retries without guessing.

CodeMeaningRetryableretry_after_hours
validation_errorBad arguments or empty inputNo—
title_resolve_failedCrossref returned no items for the given --title query (try a longer / cleaner title, or pass the DOI directly)No—
not_foundNo open-access PDF foundYes168 (one week — OA lands on embargo / preprint timescale)
download_network_errorNetwork failure during downloadYes1
download_not_a_pdfResponse was not a PDF (HTML landing page)No—
download_host_not_allowedPDF URL failed SSRF safety check (private IP / non-http(s) / non-80,443 / blocked metadata host)No—
download_size_exceededResponse exceeded 50 MB limitYes24
download_io_errorLocal filesystem write failedYes1
internal_errorUnexpected errorNo—

The canonical mapping lives in RETRY_AFTER_HOURS in scripts/fetch.py and is surfaced in schema.error_codes.

Examples

# Single DOI (JSON output when piped; text when in a terminal)
python scripts/fetch.py 10.1038/s41586-020-2649-2

# Single title (resolved to DOI via Crossref, then downloaded)
python scripts/fetch.py --title "Highly accurate protein structure prediction with AlphaFold"

# Dry-run preview (resolve without downloading)
python scripts/fetch.py 10.1038/s41586-020-2649-2 --dry-run

# Title + dry-run — preview the resolved DOI and candidate matches
python scripts/fetch.py --title "Attention Is All You Need" --dry-run

# Force JSON (for agents even inside a terminal)
python scripts/fetch.py 10.1038/s41586-020-2649-2 --format json

# Human-readable with pretty colors in a pipeline
python scripts/fetch.py 10.1038/s41586-020-2649-2 --format text

# Batch download, safely retriable
python scripts/fetch.py --batch dois.txt --out ./papers \
    --idempotency-key monday-review-batch

# Pipe DOIs from another tool
zot -F ids.json query ... | jq -r '.[].doi' | python scripts/fetch.py --batch -

# Agent discovery
python scripts/fetch.py schema --pretty

# Streaming mode — one result per line as each DOI resolves
python scripts/fetch.py --batch dois.txt --stream

# Works without UNPAYWALL_EMAIL (skips Unpaywall, uses remaining 4 sources)
python scripts/fetch.py 10.1038/s41586-020-2649-2

Environment

VariableDefaultPurpose
UNPAYWALL_EMAILunsetContact email for Unpaywall API. Optional but recommended. Without it, Unpaywall is skipped (remaining sources still work).
PAPER_FETCH_INSTITUTIONALunsetSet to any value (e.g. 1) to opt into institutional mode — activates a 1 req/s rate limiter and the publisher-direct fallback. See below.
PAPER_FETCH_NO_SCIHUBunsetSet to any value to disable the Sci-Hub fallback (step 7).
PAPER_FETCH_SCIHUB_MIRRORSunsetComma-separated mirror hostnames to try in priority order (e.g. sci-hub.ru,sci-hub.st,sci-hub.su). Overrides built-in defaults.
PAPER_FETCH_CLOAKunsetSet to any value to enable the CloakBrowser fallback — Cloudflare-blocked PDFs (HTTP 403/429 or a non-PDF interstitial) are retried through a stealth Chromium. See CloakBrowser access below.
CLOAKBROWSER_PYTHONautoPath to a Python that can import cloakbrowser, used by the cloak fallback. Auto-detect order: this var → ~/github/CloakBrowser/.venv/bin/python → the current interpreter.
PAPER_FETCH_CLOAK_HEADEDunsetSet to any value to launch a headed (visible) browser instead of headless. Harder Cloudflare challenges (e.g. science.org) defeat headless mode and only clear in a real window — set this when the cloak fallback keeps returning HTTP 403 / "Just a moment…". Requires a display.

CloakBrowser access (opt-in)

Some publishers (e.g. science.org) sit behind Cloudflare, which answers a plain HTTP client with a 403/429 or a "Just a moment…" JS-challenge page instead of the PDF — so the default urllib download can't get through even when the URL is legitimately accessible from a browser. CloakBrowser is a stealth Chromium that passes those challenges. This skill borrows the approach from cloakFetch.

Opt in: export PAPER_FETCH_CLOAK=1 (plus a cloakbrowser-importable Python — see CLOAKBROWSER_PYTHON).

How it works: the fallback lives at the download layer, not as a new source — so it applies to any resolved URL (Unpaywall, publisher-direct, Sci-Hub, …). On a Cloudflare block, fetch.py shells out to the cloak_pdf.py companion via the resolved Python; CloakBrowser loads the PDF host's origin to solve the JS challenge, then fetches the PDF with an in-page fetch() (so the request carries the browser's real fingerprint and cf_clearance cookie) and returns the bytes on stdout. fetch.py itself stays stdlib-only — it never imports cloakbrowser.

Headless vs. headed. The companion runs headless by default. Some challenges (e.g. science.org) defeat headless Chromium and stay stuck on "Just a moment…" — set PAPER_FETCH_CLOAK_HEADED=1 to use a visible window, which clears them. Verified: a www.science.org/doi/pdf/… PDF that returns 403 to the plain client downloads cleanly via the headed cloak fallback.

Same-origin only. The in-page fetch is same-origin, so the fallback works when the resolved URL is a direct PDF link on the blocked host (e.g. www.science.org/doi/pdf/…). A URL that cross-origin-redirects (e.g. a bare doi.org/… link) or a legacy host whose challenge never clears will fail closed and fall through to the next source.

What stays the same:

  • Returned bytes are re-validated through the same %PDF magic-byte check and 50 MB size cap. SSRF defense still gates the URL before the browser is ever launched.
  • No CAPTCHA solving. CloakBrowser passes automated JS challenges, not interactive ones; an interactive Turnstile still fails closed and falls through.
  • Fails closed. No cloakbrowser-importable Python, helper missing, or any error → silent fall-through to the next source. The agent is never told a blocked fetch succeeded.
  • Agent cannot opt in on its own — PAPER_FETCH_CLOAK must be set by the human operator. Same trust boundary as institutional mode.
  • On success the per-result object carries via: "cloak" so an orchestrator can see the fallback was used.

Cost: a triggered fallback launches a real browser (~20–40 s, ~200 MB Chromium on first download). It only fires after a normal download was blocked, so the happy path is unaffected.

Institutional access (opt-in)

Many researchers have legitimate subscription access through their institution's IP range (on-campus or VPN). Paper-fetch can use that access by letting the publisher's own auth (your IP, your session cookies) decide whether to serve the PDF.

Host reachability does not differ between modes — public mode already trusts URLs returned by the OA APIs (Unpaywall, Semantic Scholar, bioRxiv, PMC) and fetches any HTTPS host that passes SSRF defense. Institutional mode adds two things: (1) a publisher-direct fallback (step 6 above) that constructs a publisher-side PDF URL by DOI prefix when every OA source missed, so your institutional IP/cookies can authorize the fetch, and (2) a 1 req/s rate limiter to keep batch jobs from getting your IP throttled or banned for "systematic downloading."

Opt in: export PAPER_FETCH_INSTITUTIONAL=1

What changes in institutional mode:

AspectPublic (default)Institutional
Host reachabilityAny public HTTPS host passing SSRF defenseSame
SSRF defenseEnforced (private IP / non-http(s) / non-80,443 / cloud metadata all blocked)Enforced — same rules
Publisher-direct fallbackOffOn — DOI-prefix → publisher PDF URL, last resort after all OA sources miss
Rate limitNone1 req/s token bucket (all outbound)
meta.auth_mode"public""institutional"

What stays the same:

  • %PDF magic-byte check and 50 MB size cap (prevents HTML landing pages and oversized responses slipping through)
  • No CAPTCHA solving, ever. If a publisher shows a challenge, the response won't start with %PDF and paper-fetch falls through to the next source.
  • Institutional mode itself uses no browser automation, no Playwright, no stealth — it is a plain HTTP fetch against publisher-direct URLs. (Browser automation is a separate opt-in: the CloakBrowser fallback above, gated by PAPER_FETCH_CLOAK.)
  • Agent cannot opt in on its own — PAPER_FETCH_INSTITUTIONAL must be set by the human operator in the shell environment. This is the trust boundary.

When paper-fetch can't find an OA copy and you're in public mode, the error envelope includes suggest_institutional: true and a hint telling the user to set the env var. Agents can surface this verbatim rather than failing silently.

ToS notice: almost every publisher subscription prohibits "systematic downloading." The 1 req/s rate limit plus the existing per-file idempotency are designed to keep individual research use within acceptable bounds. Running many parallel paper-fetch processes, or lifting the rate limit, can trigger a publisher-wide IP ban affecting your entire institution. Don't.

Notes

  • Auth is delegated. The agent never runs a login subcommand. The human or the orchestrator sets UNPAYWALL_EMAIL in the environment; the agent inherits it. Missing email degrades gracefully to the remaining 4 sources.
  • Trust is directional. CLI arguments are validated once at the entry point. SSRF defense, the %PDF magic-byte check, and the 50 MB size cap are enforced in the environment layer, not at the agent's request. An agent cannot loosen safety by passing a flag — opting into institutional mode (and its rate-limit risk profile) is an operator action via environment variable.
  • Downloads are naturally idempotent. Re-running against the same --out skips files that already exist (deterministic filename: {first_author}_{year}_{journal_abbrev}_{short_title}.pdf; the journal segment is omitted if metadata lacks a journal/venue). Pair with --idempotency-key to also replay the exact envelope without any network I/O.
  • Default output directory: ./pdfs/.

Score

0–100
63/ 100

Grade

C

Popularity15/30

622 installs — growing adoption.

Completeness27/30

Documented: full SKILL.md body, description, one-line install. Missing: category/license metadata.

Trust15/25

Community skill with a public GitHub source repository you can review.

Freshness6/15

No update timestamp is tracked for this skill in our catalog.

Scored automatically from popularity, completeness, trust, and freshness — computed only from data in our catalog, never fabricated.

Proud of your score? Add this badge to your README.

Paste a snippet into your GitHub README. The badge updates automatically and links back to this page.

Paper Fetch skill score badge previewScore badge

Markdown

[![Paper Fetch skill](https://www.remoteopenclaw.com/skills/agents365-ai/365-skills/paper-fetch/badges/score.svg)](https://www.remoteopenclaw.com/skills/agents365-ai/365-skills/paper-fetch)

HTML

<a href="https://www.remoteopenclaw.com/skills/agents365-ai/365-skills/paper-fetch"><img src="https://www.remoteopenclaw.com/skills/agents365-ai/365-skills/paper-fetch/badges/score.svg" alt="Paper Fetch skill"/></a>

Paper Fetch FAQ

How do I install the Paper Fetch skill?

Run “npx skills add https://github.com/agents365-ai/365-skills --skill paper-fetch” in your terminal. The skill is added to your agent's skills directory and picked up automatically on the next run — no restart or extra configuration needed.

What does the Paper Fetch skill do?

Use whenever the user wants to obtain, download, or fetch a paper's PDF — given a DOI, an arXiv id, a paper title, a citation, or a list of DOIs. Trigger on phrases like "download this paper", "find the PDF for [DOI]", "grab me the [Nature/bioRxiv/arXiv] paper on X", "get the open-access version", "I need this article", or any bulk/batch paper download request, even when the user doesn't explicitly say "PDF" or "DOI". Resolves via Unpaywall → Semantic Scholar → arXiv → PubMed Central → bioRxiv/medRxiv → publisher direct (institutional opt-in) → Sci-Hub mirrors as last-resort fallback. The full SKILL.md on this page shows the exact instructions the skill gives your agent.

Is the Paper Fetch skill free?

Yes. Paper Fetch is a free, open-source skill published from agents365-ai/365-skills. As with any third-party skill, review the source repository before installing it into an agent with sensitive access.

Does Paper Fetch work with Claude Code and OpenClaw?

Yes. Skills use the portable SKILL.md format, so Paper Fetch works with Claude Code, OpenClaw, Codex, Hermes, and any other agent that reads SKILL.md skills.

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Context.dev gives your agents a single API to scrape, enrich, and extract live web data — no proxies, no parsers, no maintenance.

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Your own AI agent, running 24/7 with QwikClaw logoYour own AI agent, running 24/7 with QwikClaw

QwikClaw sets up and runs an always-on OpenClaw agent for you. One click, no config files, no server setup.

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