content-access
Legal methods for accessing paywalled and geo-blocked content. Use when researching behind paywalls, accessing academic papers, bypassing geographic restrictions, or finding open access alternatives. Covers Unpaywall, library databases, VPNs, and ethical access strategies for journalists and researchers.
What this skill does
# Content access methodology
Ethical and legal approaches for accessing restricted web content for journalism and research.
## Access hierarchy (most to least preferred)
```
┌─────────────────────────────────────────────────────────────────┐
│ CONTENT ACCESS DECISION HIERARCHY │
├─────────────────────────────────────────────────────────────────┤
│ │
│ 1. FULLY LEGAL (Always try first) │
│ ├─ Library databases (PressReader, ProQuest, JSTOR) │
│ ├─ Open access tools (Unpaywall, CORE, PubMed Central) │
│ ├─ Author direct contact │
│ └─ Interlibrary loan │
│ │
│ 2. LEGAL (Browser features) │
│ ├─ Reader Mode (Safari, Firefox, Edge) │
│ ├─ Wayback Machine archives │
│ └─ Google Scholar "All versions" │
│ │
│ 3. GREY AREA (Use with caution) │
│ ├─ Archive.is for individual articles │
│ ├─ Disable JavaScript (breaks functionality) │
│ └─ VPNs for geo-blocked content │
│ │
│ 4. NOT RECOMMENDED │
│ ├─ Credential sharing │
│ ├─ Systematic scraping │
│ └─ Commercial use of bypassed content │
│ │
└─────────────────────────────────────────────────────────────────┘
```
## Open access tools for academic papers
### Unpaywall browser extension
Unpaywall finds free, legal copies of 50M+ open-access academic records.
```python
# Unpaywall API (free, requires email for identification)
import requests
def find_open_access(doi: str, email: str) -> dict:
"""Find open access version of a paper using Unpaywall API.
Args:
doi: Digital Object Identifier (e.g., "10.1038/nature12373")
email: Your email for API identification
Returns:
Dict with best open access URL if available
"""
url = f"https://api.unpaywall.org/v2/{doi}?email={email}"
response = requests.get(url, timeout=30)
if response.status_code != 200:
return {'error': f'Status {response.status_code}'}
data = response.json()
if data.get('is_oa'):
best_location = data.get('best_oa_location', {})
return {
'is_open_access': True,
'oa_url': best_location.get('url_for_pdf') or best_location.get('url'),
'oa_status': data.get('oa_status'), # gold, green, bronze, hybrid
'host_type': best_location.get('host_type'), # publisher, repository
'version': best_location.get('version') # publishedVersion, acceptedVersion
}
return {
'is_open_access': False,
'title': data.get('title'),
'journal': data.get('journal_name')
}
# Usage
result = find_open_access("10.1038/nature12373", "[email protected]")
if result.get('is_open_access'):
print(f"Free PDF at: {result['oa_url']}")
```
### CORE API (290M+ open-access works)
```python
# CORE API - requires free API key from https://core.ac.uk/
import requests
class CORESearch:
def __init__(self, api_key: str):
self.api_key = api_key
self.base_url = "https://api.core.ac.uk/v3"
def search(self, query: str, limit: int = 10) -> list:
"""Search CORE database for open access papers."""
headers = {'Authorization': f'Bearer {self.api_key}'}
params = {
'q': query,
'limit': limit
}
response = requests.get(
f"{self.base_url}/search/works",
headers=headers,
params=params,
timeout=30
)
if response.status_code != 200:
return []
data = response.json()
results = []
for item in data.get('results', []):
results.append({
'title': item.get('title'),
'authors': [a.get('name') for a in item.get('authors', [])],
'year': item.get('yearPublished'),
'doi': item.get('doi'),
'download_url': item.get('downloadUrl'),
'abstract': item.get('abstract', '')[:500]
})
return results
def get_by_doi(self, doi: str) -> dict:
"""Get paper by DOI."""
headers = {'Authorization': f'Bearer {self.api_key}'}
response = requests.get(
f"{self.base_url}/works/{doi}",
headers=headers,
timeout=30
)
return response.json() if response.status_code == 200 else {}
```
### Semantic Scholar API (220M+ papers)
```python
# Semantic Scholar API - free, but request a key from
# https://www.semanticscholar.org/product/api for anything beyond
# ad-hoc calls. Unkeyed access has been tightened to a low shared
# rate limit and is no longer reliable for batch lookups.
import requests
def search_semantic_scholar(query: str, limit: int = 10) -> list:
"""Search Semantic Scholar for papers with open access links."""
url = "https://api.semanticscholar.org/graph/v1/paper/search"
params = {
'query': query,
'limit': limit,
'fields': 'title,authors,year,abstract,openAccessPdf,citationCount'
}
response = requests.get(url, params=params, timeout=30)
if response.status_code != 200:
return []
results = []
for paper in response.json().get('data', []):
oa_pdf = paper.get('openAccessPdf', {})
results.append({
'title': paper.get('title'),
'authors': [a.get('name') for a in paper.get('authors', [])],
'year': paper.get('year'),
'citations': paper.get('citationCount', 0),
'open_access_url': oa_pdf.get('url') if oa_pdf else None,
'abstract': paper.get('abstract', '')[:500] if paper.get('abstract') else ''
})
return results
def get_paper_by_doi(doi: str) -> dict:
"""Get paper details by DOI."""
url = f"https://api.semanticscholar.org/graph/v1/paper/DOI:{doi}"
params = {
'fields': 'title,authors,year,abstract,openAccessPdf,references,citations'
}
response = requests.get(url, params=params, timeout=30)
return response.json() if response.status_code == 200 else {}
```
### OpenAlex API (250M+ scholarly works)
OpenAlex replaced Microsoft Academic Graph after MAG was retired and
has become the de-facto open scholarly data backbone — many tools
(Unpaywall companion data, Local Citation Network, OpenCitations)
now resolve via OpenAlex.
**Auth note (2026):** OpenAlex moved to API-key-required access on
February 13, 2026, with a credit-based rate model. Anonymous access
to the website is still free; API access via key has metered limits
that step up with paid tiers — verify the current model at
https://docs.openalex.org/. Get a free key from your OpenAlex account.
```python
# OpenAlex API client
# https://docs.openalex.org/
# Pricing & key issuance: https://openalex.org/
import requests
def search_openalex(query: str, api_key: str, limit: int = 25,
email: str = None) -> list:
"""Search OpenAlex for works.
Args:
query: free-text search string.
api_key: OpenAlex API key (required as of 2026-02-13).
limit: max results per page (1-200).
email: contact email for the polite pool — recommended even
with a key, since OpenAlex prioritizes requests witRelated in Writing & Docs
jax-development
IncludedUse this skill when the user is writing, debugging, profiling, refactoring, reviewing, benchmarking, parallelising, exporting, or explaining JAX code, or when they mention JAX, jax.numpy, jit, grad, value_and_grad, vmap, scan, lax, random keys, pytrees, jax.Array, sharding, Mesh, PartitionSpec, NamedSharding, pmap, shard_map, Pallas, XLA, StableHLO, checkify, profiler, or the JAX repo. It helps turn NumPy or PyTorch-style code into pure functional JAX, fix tracer/control-flow/shape/PRNG bugs, remove recompiles and host-device syncs, choose transforms and sharding strategies, inspect jaxpr/lowering/IR, and benchmark compiled code correctly.
nature-article-writer
IncludedDrafts, rewrites, diagnostically critiques, and style-calibrates primary research manuscripts for Nature and Nature Portfolio journals. Use when the user wants a Nature-style title, summary paragraph or abstract, introduction, results, discussion, methods, figure legends, presubmission enquiry, cover letter, reviewer response, or when a scientific draft sounds generic, jargon-heavy, structurally weak, or AI-ish and needs precise, broad-reader-friendly prose without inventing data, analyses, or references. Best for primary research articles and letters rather than reviews or press releases unless explicitly adapting one.
deckrd
IncludedDocument-driven framework that derives requirements, specifications, implementation plans, and executable tasks from goals through structured AI dialogue. Use when user says "write requirements", "create spec", "plan implementation", "derive tasks", "structure this feature", "break down into tasks", or "document this module". Also use for reverse engineering existing code into docs (/deckrd rev). Do NOT use for direct code writing — use /deckrd-coder after tasks are generated. Do NOT use when the user only wants to run or fix existing code without planning.
clinical-decision-support
IncludedGenerate professional clinical decision support (CDS) documents for pharmaceutical and clinical research settings, including patient cohort analyses (biomarker-stratified with outcomes) and treatment recommendation reports (evidence-based guidelines with decision algorithms). Supports GRADE evidence grading, statistical analysis (hazard ratios, survival curves, waterfall plots), biomarker integration, and regulatory compliance. Outputs publication-ready LaTeX/PDF format optimized for drug development, clinical research, and evidence synthesis.
handling-sf-data
IncludedSalesforce data operations with 130-point scoring. Use this skill to create, update, delete, bulk import/export, generate test data, and clean up org records using sf CLI and anonymous Apex. TRIGGER when: user creates test data, performs bulk import/export, uses sf data CLI commands, needs data factory patterns for Apex tests, or needs to seed/clean records in a Salesforce org. DO NOT TRIGGER when: SOQL query writing only (use querying-soql), Apex test execution (use running-apex-tests), or metadata deployment (use deploying-metadata).
accelint-ac-to-playwright
IncludedConvert and validate acceptance criteria for Playwright test automation. Use when user asks to (1) review/evaluate/check if AC are ready for automation, (2) assess if AC can be converted as-is, (3) validate AC quality for Playwright, (4) turn AC into tests, (5) generate tests from acceptance criteria, (6) convert .md bullets or .feature Gherkin files to Playwright specs, (7) create test automation from requirements. Handles both bullet-style markdown and Gherkin syntax with JSON test plan generation and validation.