
Turn any codebase, with its docs, SQL schemas, configs, and PDFs, into a queryable knowledge graph. A /graphify skill for Claude Code, Cursor, Codex, and Gemini CLI: local deterministic AST parsing, every edge explained, no vector store.
ref-downloader is a packaged skill for agents that batch-download reference PDFs from a DOI or a paper PDF. It combines Crossref reference extraction, reference validation, and browser-based downloading through your institutional Microsoft Edge session.
Builders who want their agent to gather reference PDFs from a paper or DOI using their existing institutional access.
You can turn one paper into a folder of downloaded reference PDFs without chasing each source by hand.
Pulls the reference list for a parent paper from Crossref before download starts.
Checks each reference against Crossref and classifies what can be downloaded, what failed, and what needs manual follow-up.
Uses different flows for publishers like ACS, Nature, Elsevier, Wiley, Springer, IEEE, and others instead of one generic scraper.
Runs through your existing Microsoft Edge profile so institutional logins already in the browser can carry through.
Writes per-reference status reports and can pick up where it left off after interruption.
Ships as a ready-to-copy skill under `skills/ref-downloader/` with a runbook and config template.
cd ~/.claude/skills/ref-downloader # or wherever you copied it pip install playwright pymupdf # or use the source's requirements.txt playwright install msedge cp config.example.toml config.local.toml # Edit config.local.toml — at minimum set [crossref].mailto. # Windows: notepad config.local.toml # macOS / Linux: $EDITOR config.local.toml (or vim / nano / code / ...)
python <SKILL_DIR>/scripts/run_ref_downloader.py 10.1021/jacs.5c05017
python <SKILL_DIR>/scripts/run_ref_downloader.py "C:\path\to\your_paper.pdf"
python <SKILL_DIR>/scripts/run_ref_downloader.py 10.1021/jacs.5c05017 --output-dir refs/
python <SKILL_DIR>/scripts/run_ref_downloader.py 10.1021/jacs.5c05017 --yes --auto
python <SKILL_DIR>/scripts/run_ref_downloader.py 10.1021/jacs.5c05017 --config ./alt.toml
Stop losing an afternoon to chasing dozens of reference PDFs by hand. One DOI in, every reference PDF out — using your existing institutional access.
Status: beta (v0.4.1). Windows + Microsoft Edge verified path. macOS / Linux / Chromium untested. Expect rough edges around supplementary downloads and publisher-site changes. PR-worthy issues welcome.
Heads up — not a paywall bypass. ref-downloader uses your institutional access. If your university or organization subscribes to a journal, those refs work. If they don't, those refs become
manual_pendingfor you to follow up on by hand.
$ python run_ref_downloader.py 10.1021/jacs.5c05017
=== Ref Downloader Wrapper ===
DOI: 10.1021/jacs.5c05017
PROJECT: jacs.5c05017
Config: config.example.toml + config.local.toml
>>> extract_refs.py
Title: Designing Natural Cell-Inspired Heme-Spurred Membrane...
References found: 38
>>> validate_refs.py
Total: 38 Verified: 38 Failed: 0 No DOI: 0
>>> download_refs.py
[ 1] downloaded (842 KB) Lee2016_NatEnergy.pdf
[ 2] downloaded (1.2 MB) Wang2018_AdvMater.pdf
[ 3] manual_pending (auth_redirect)
[ 4] downloaded (655 KB) Chen2019_JACS.pdf
[ 5] failed (challenge_timeout)
[ 6] ignored (ignored_institution_access)
... 31 more refs processed ...
[38] downloaded (956 KB) Park2024_JElectrochemSoc.pdf
========== Download report ==========
Total references: 38
Main PDFs: 33 downloaded · 3 manual_pending · 1 failed · 1 ignored
SI files: 12 captured
PDFs land in: ./jacs.5c05017_refs/jacs.5c05017/
=====================================
download_report.csv gives every ref a status + reason (manual_pending (auth_redirect), failed (challenge_timeout), ignored); events.jsonl keeps the per-ref event trace.Ctrl+C. State persists per project; rerunning skips already-downloaded refs and retries only the failures.--auto mode retry queue (manual-pending refs get a second async attempt 60s later, hot-session preserved).REF_DOWNLOADER_BROWSER=cloak to swap in cloakbrowser's stealth Chromium with humanized input — no code changes, same pipeline. See Configuration.The skill is self-contained under skills/ref-downloader/. Pick the install path for your agent framework:
git clone https://github.com/ltczding-gif/ref-downloader.git
# Pick ONE install destination for your agent framework:
# Claude Code: cp -r ref-downloader/skills/ref-downloader ~/.claude/skills/
# Codex CLI: cp -r ref-downloader/skills/ref-downloader ~/.codex/skills/
# Copilot CLI / VSC: cp -r ref-downloader/skills/ref-downloader .github/skills/
# Project-local: cp -r ref-downloader/skills/ref-downloader .agents/skills/
cd ~/.claude/skills/ref-downloader # or wherever you copied it
pip install playwright pymupdf
playwright install msedge
cp config.example.toml config.local.toml # then set [crossref].mailto
# In your agent: just describe the task; the skill triggers via its description.
# Direct CLI for testing: python scripts/run_ref_downloader.py 10.1021/jacs.5c05017
What you'll see: 30–80 refs discovered for a typical chemistry/physics paper, then a mix of downloaded (refs your institution covers), manual_pending (SSO bounce or paywall), and occasional failed (publisher quirk). Run on a DOI from a journal your institution actually subscribes to for the highest hit rate. Details below.
tomllib).pip install pymupdf) for DOI extraction from PDF text when Zotero lookup is unavailable.Pick the install path for your agent framework:
| Framework | Install command |
|---|---|
| Claude Code | cp -r skills/ref-downloader ~/.claude/skills/ |
| Claude Agent SDK | same (auto-discovers ~/.claude/skills/) |
| Codex CLI | cp -r skills/ref-downloader ~/.codex/skills/ |
| Copilot CLI / VS Code agent | cp -r skills/ref-downloader .github/skills/ |
| Any framework (project-local) | cp -r skills/ref-downloader .agents/skills/ |
Then install Python prereqs INSIDE the copied skill folder (the skill protocol doesn't manage Python deps):
cd ~/.claude/skills/ref-downloader # or wherever you copied it
pip install playwright pymupdf # or use the source's requirements.txt
playwright install msedge
cp config.example.toml config.local.toml
# Edit config.local.toml — at minimum set [crossref].mailto.
# Windows: notepad config.local.toml
# macOS / Linux: $EDITOR config.local.toml (or vim / nano / code / ...)
If you want to hack on the code, the skill folder is a runnable Python project:
git clone https://github.com/ltczding-gif/ref-downloader.git
cd ref-downloader
pip install -r requirements.txt -r requirements-dev.txt
playwright install msedge
cp skills/ref-downloader/config.example.toml skills/ref-downloader/config.local.toml
# Edit config.local.toml — at minimum set [crossref].mailto.
# Run the offline test suite
python -m pytest tests/ -v
# Run the tool directly
python skills/ref-downloader/scripts/run_ref_downloader.py 10.1021/jacs.5c05017
(After install — paths assume the skill is at <SKILL_DIR>, e.g. ~/.claude/skills/ref-downloader/. In source, <SKILL_DIR> = skills/ref-downloader/.)
python <SKILL_DIR>/scripts/run_ref_downloader.py 10.1021/jacs.5c05017
Default output: <cwd>/jacs.5c05017_refs/jacs.5c05017/
python <SKILL_DIR>/scripts/run_ref_downloader.py "C:\path\to\your_paper.pdf"
Default output: <pdf_dir>/your_paper_refs/<doi-derived-name>/
python <SKILL_DIR>/scripts/run_ref_downloader.py 10.1021/jacs.5c05017 --output-dir refs/
python <SKILL_DIR>/scripts/run_ref_downloader.py 10.1021/jacs.5c05017 --yes --auto
python <SKILL_DIR>/scripts/run_ref_downloader.py 10.1021/jacs.5c05017 --config ./alt.toml
All configuration lives in config.local.toml (gitignored). Copy config.example.toml to bootstrap.
| Section | Key | Purpose |
|---|---|---|
[crossref] | mailto | Your email — entry into Crossref polite pool |
[zotero] | db_path | Optional path to zotero.sqlite for DOI lookup from PDF filename |
[browser] | edge_profile_dir | Edge profile directory; empty = OS default |
[browser] | disable_extensions | Set true to launch with --disable-extensions |
[institution] | auth_hosts | Hostnames that mean "you got bounced to SSO" (e.g. ["sso.your-uni.edu"]) |
[institution] | auth_url_fragments | URL substrings indicating SSO (e.g. ["oauth", "saml"]) |
[institution] | auth_page_titles | <title> text for SSO pages (catches HTML served as PDF) |
[institution] | auth_loading_titles | Loading-page titles (also reused for AIP/AVS publisher loading detection) |
[institution] | ignored_access_dois | DOIs you know are paywalled at your institution; skipped without retry |
Environment variables override file values:
| Variable | Maps to |
|---|---|
REF_DOWNLOADER_MAILTO | crossref.mailto |
REF_DOWNLOADER_ZOTERO_DB | zotero.db_path |
REF_DOWNLOADER_EDGE_PROFILE | browser.edge_profile_dir |
REF_DOWNLOADER_DISABLE_EXTENSIONS | browser.disable_extensions (1/true to enable) |
REF_DOWNLOADER_CONFIG | Path to alternate TOML file |
See skills/ref-downloader/config.example.toml for full documentation.
What it is. CloakBrowser is a third-party Python package by CloakHQ (MIT-licensed, available on PyPI as cloakbrowser). It ships a patched Chromium build with source-level anti-fingerprint changes designed to look like a normal browser to common bot-detection layers (Cloudflare Turnstile, Radware, DataDome, FingerprintJS, etc). Its launch_persistent_context_async() API is intentionally compatible with Playwright's — that's what lets ref-downloader swap backends with a single env var instead of rewriting the download flow.
Not a dependency of ref-downloader. If you don't run pip install cloakbrowser it's never imported. The default Edge backend is unchanged. When CloakBrowser IS the active backend, ref-downloader uses Chromium under a separate persistent profile at ~/.local/cloakbrowser/profiles/ref-downloader (or REF_DOWNLOADER_CLOAK_PROFILE), so your Edge profile is not touched — Edge does NOT need to be closed.
When to use it. Sites you'd reach for it on: CCS Chemistry (10.31635, Cloudflare-protected), some Elsevier paths gated by Radware, anything where the Edge backend keeps producing manual_pending (radware_bot_manager) or failed (challenge_timeout). Don't reach for it as a default — the Edge backend is more reliable when your institutional access is the actual bottleneck, because Edge carries your authenticated cookies.
Caveats. CloakBrowser is beta third-party software; install + use at your own discretion (review its repo before pulling it). It is not a captcha solver — interactive challenges still need you. It also does not carry your institutional cookies (separate profile), so it's most useful for open-Cloudflare sites, less useful for paywalled-but-license-covered refs.
pip install cloakbrowser # one-time, separate from ref-downloader
$env:REF_DOWNLOADER_BROWSER = "cloak"
$env:REF_DOWNLOADER_CLOAK_HUMAN_PRESET = "careful" # optional: slower mouse/scroll
python skills/ref-downloader/scripts/run_ref_downloader.py 10.31635/ccsorg...
CloakBrowser env vars (all optional):
| Variable | Default | Purpose |
|---|---|---|
REF_DOWNLOADER_BROWSER | edge | Set to cloak (or cloakbrowser) to switch backend |
REF_DOWNLOADER_CLOAK_PROFILE | ~/.local/cloakbrowser/profiles/ref-downloader | Persistent Chromium profile path |
REF_DOWNLOADER_CLOAK_HUMANIZE | 1 | 0/false to disable humanized input |
REF_DOWNLOADER_CLOAK_HUMAN_PRESET | default | default or careful (slower) |
REF_DOWNLOADER_CLOAK_PROXY | unset | HTTP/SOCKS proxy URL |
REF_DOWNLOADER_CLOAK_GEOIP | auto | 1 to force GeoIP rerouting (auto when proxy is set) |
CLOAKBROWSER_PYTHONPATH | unset | sys.path hint for a local cloakbrowser source checkout |
Notes:
human_preset=careful reduces behavior-based detection but is not a captcha solver.REF_DOWNLOADER_BROWSER=cloak, it's not imported.Three-stage pipeline + a wrapper:
skills/ref-downloader/
├── SKILL.md agent runbook (slim entry)
├── references/agent-runbook.md extended manual flow + DOI fallback
├── config.example.toml config schema (copy to config.local.toml)
└── scripts/
├── run_ref_downloader.py entry — config + DOI resolution + sequencing
│ └─> extract_refs.py (1) Crossref API: fetch parent's reference list
│ └─> validate_refs.py (2) Crossref API: per-ref metadata + publisher classify
│ └─> download_refs.py (3) Playwright/Edge: download main PDF + SI per publisher
└── _config.py TOML + env-var loader
You can also run the three scripts manually for debugging or partial restarts. See the agent runbook in skills/ref-downloader/references/agent-runbook.md for the manual flow.
Agent users can install or inspect the packaged skill at skills/ref-downloader/SKILL.md. The repository root remains the human-facing Python project; the skill bundle is kept separate so Codex does not treat README, changelog, tests, and source files as always-associated skill context.
ACS, Nature, Science, Elsevier, Wiley, RSC, Springer, PNAS, ECS, IOP, AIP, AVS, IEEE, OSA, KPS, Beilstein, APS, Annual Reviews, Taylor & Francis, CCS Chemistry. Maturity varies — see docs/SUPPORTED_PUBLISHERS.md for the per-publisher tier table and known issues. CCS Chemistry sits behind Cloudflare; pair it with REF_DOWNLOADER_BROWSER=cloak for reliable access.
headless=True yields empty results for Wiley / ACS supplementary downloads. The default is headed.msedge.exe processes.manual_pending so you can sign in interactively. Configure [institution] to teach it which redirects to recognize.See CONTRIBUTING.md for guidance on:
This tool launches your real Edge profile, with all your cookies and saved sessions. Read SECURITY.md before running it against a profile you also use for daily browsing.
MIT — see LICENSE.
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