openalex

name	openalex
description	Search academic papers via OpenAlex API for open citation data, institutional affiliations, and funding information. Use when user says "openalex search", "search openalex", "open citation graph", or wants comprehensive academic metadata beyond arXiv/Semantic Scholar.
argument-hint	[search-query]
allowed-tools	Bash(*), Read, Write

OpenAlex Academic Search

Search query: $ARGUMENTS

Role & Positioning

This skill uses OpenAlex as a comprehensive open academic graph source:

Skill	Source	Best for
/arxiv	arXiv API	Latest preprints, cutting-edge unrefereed work
/semantic-scholar	Semantic Scholar API	Published venue papers (IEEE, ACM, Springer) with citation counts
/openalex	OpenAlex API	Open citation graph, institutional affiliations, funding data, comprehensive metadata
/deepxiv	DeepXiv CLI	Layered reading: search, brief, section map, section reads
/exa-search	Exa API	Broad web search: blogs, docs, news, companies, research papers
/gemini-search	Gemini MCP / CLI	AI-powered broad literature discovery

Use OpenAlex when you want:

• Open citation data — fully open citation graph (no API key required for basic use)
• Institutional affiliations — author institutions and collaborations
• Funding information — NSF, NIH, and other funding sources
• Comprehensive metadata — topics, keywords, abstract, open access status
• Cross-database coverage — indexes 250M+ works from multiple sources

Constants

• MAX_RESULTS = 10 — Default number of results. Override with — max: 20.
• DEFAULT_SORT = relevance — Sort by relevance. Override with — sort: citations or — sort: date.
• OPENALEX_FETCHER — canonical name openalex_fetch.py, resolved per shared-references/integration-contract.md §2 (Policy D1 — standalone /openalex has no documented inline fallback, so unresolved helper terminates with an explicit error).

Overrides (append to arguments):

• /openalex "topic" — max: 20 — return up to 20 results
• /openalex "topic" — year: 2023- — papers from 2023 onward
• /openalex "topic" — year: 2020-2023 — papers from 2020 to 2023
• /openalex "topic" — type: article — only journal articles
• /openalex "topic" — type: preprint — only preprints
• /openalex "topic" — open-access — only open access papers
• /openalex "topic" — min-citations: 50 — minimum 50 citations
• /openalex "topic" — sort: citations — sort by citation count (descending)
• /openalex "topic" — sort: date — sort by publication date (newest first)

Setup

Prerequisites

1. Python 3.7+ with requests library:

   pip install requests
   

2. Optional: API keys — Create .claude/.env in project root:

   # Copy from template
   cp .claude/.env.example .claude/.env
   
   # Edit and add your keys
   # .claude/.env
   OPENALEX_API_KEY=your-key-here
   OPENALEX_EMAIL=[e-mail]
   

   Claude Code automatically loads .claude/.env as environment variables.

3. Get API keys (optional but recommended):

   • OpenAlex API key: Free tier $1/day (10,000 list calls, 1,000 search calls) from openalex.org
   • Email for polite pool: Faster response times (no registration needed)

Verify Setup

python3 "$OPENALEX_FETCHER" search "machine learning" --max 3

(Resolve $OPENALEX_FETCHER via the canonical chain first — see Step 2 below.)

Workflow

Step 1: Parse Arguments

Parse $ARGUMENTS for:

• query: The research topic (required)
• max: Override MAX_RESULTS
• year: Publication year filter (e.g., 2023-, 2020-2023)
• type: Work type filter (article, preprint, book, book-chapter, dataset, dissertation)
• open-access: Only include open access papers
• min-citations: Minimum citation count threshold
• sort: Sort order (relevance, citations, date)

Step 2: Locate Script

Resolve $OPENALEX_FETCHER via the canonical strict-safe chain (see shared-references/integration-contract.md §2). Policy D1: there is no native inline fallback for OpenAlex (retrieval requires the requests SDK + optional API key — the fetcher script encapsulates pagination, throttling, and per-source parameters), so unresolved helper terminates with explicit remediation.

cd "$(git rev-parse --show-toplevel 2>/dev/null || pwd)" || exit 1
if [ -z "${ARIS_REPO:-}" ] && [ -f .aris/installed-skills.txt ]; then
    ARIS_REPO=$(awk -F'\t' '$1=="repo_root"{print $2; exit}' .aris/installed-skills.txt 2>/dev/null) || true
fi
if [ -z "${ARIS_REPO:-}" ] && [ -f "$HOME/.aris/repo" ]; then
    ARIS_REPO=$(cat "$HOME/.aris/repo" 2>/dev/null) || true
fi
OPENALEX_FETCHER=".aris/tools/openalex_fetch.py"
[ -f "$OPENALEX_FETCHER" ] || OPENALEX_FETCHER="tools/openalex_fetch.py"
[ -f "$OPENALEX_FETCHER" ] || { [ -n "${ARIS_REPO:-}" ] && OPENALEX_FETCHER="$ARIS_REPO/tools/openalex_fetch.py"; }
[ -f "$OPENALEX_FETCHER" ] || {
  echo "ERROR: openalex_fetch.py not resolved at .aris/tools/, tools/, \$ARIS_REPO/tools/, or via ~/.aris/repo." >&2
  echo "       Fix: rerun bash tools/install_aris.sh or smart_update.sh (refreshes ~/.aris/repo), export ARIS_REPO, or copy the helper to tools/." >&2
  echo "       Also ensure 'requests' is installed: pip install requests" >&2
  exit 1
}

Step 3: Execute Search

Basic search:

python3 "$OPENALEX_FETCHER" search "QUERY" --max 10

With filters:

python3 "$OPENALEX_FETCHER" search "QUERY" --max 10 \
  --year 2023- \
  --type article \
  --open-access \
  --min-citations 20 \
  --sort citations

Get specific work by DOI:

python3 "$OPENALEX_FETCHER" work "10.1109/TWC.2024.1234567"

Get specific work by OpenAlex ID:

python3 "$OPENALEX_FETCHER" work "W2741809807"

Step 4: Parse Results

The script returns structured JSON with:

• title: Paper title
• authors: List of author names
• publication_year: Year published
• venue: Journal/conference name
• venue_type: Type of venue (journal, repository, conference, etc.)
• cited_by_count: Number of citations
• is_oa: Boolean for open access status
• oa_status: Open access type (gold, green, bronze, hybrid, closed)
• oa_url: Direct PDF link if available
• doi: DOI identifier
• openalex_id: OpenAlex work ID
• abstract: Full abstract text
• topics: Top 3 research topics
• keywords: Top 5 keywords
• type: Work type (article, preprint, etc.)

Step 5: Present Results

Format results as a structured table:

| # | Title | Venue | Year | Citations | OA | Summary |
|---|-------|-------|------|-----------|----|---------| 
| 1 | ... | IEEE TWC | 2024 | 156 | ✓ | ... |
| 2 | ... | NeurIPS | 2023 | 89 | ✓ | ... |

For each paper, also show:

• DOI: Canonical identifier
• OpenAlex ID: For cross-reference
• Open Access: Status (gold/green/bronze/hybrid/closed) and PDF link
• Topics: Top research topics
• Abstract: First 200 characters or full text

Step 6: Offer Follow-up

After presenting results, suggest:

/semantic-scholar "DOI:..."     — get S2 citation context and related papers
/arxiv "arXiv:XXXX.XXXXX"      — fetch arXiv preprint if available
/research-lit "topic" — sources: openalex, semantic-scholar  — combined multi-source review
/novelty-check "idea"          — verify novelty against literature

Key Rules

• OpenAlex is fully open — no API key required for basic use, but recommended for higher rate limits
• Comprehensive metadata — OpenAlex provides richer metadata than most sources (institutions, funding, topics)
• Citation data is open — unlike Semantic Scholar, all citation data is freely accessible
• Rate limits: Without API key, very limited (~$0.01/day). With free API key: 10,000 list calls/day, 1,000 search calls/day.
• Polite pool: Set OPENALEX_EMAIL environment variable for faster response times
• Cross-reference with other sources: OpenAlex indexes papers from arXiv, PubMed, Crossref, etc. — use DOI/arXiv ID to cross-reference
• If OpenAlex API is unreachable or rate-limited, suggest using /semantic-scholar, /arxiv, or /research-lit "topic" — sources: web as alternatives.

OpenAlex vs Other Sources

Feature	OpenAlex	Semantic Scholar	arXiv
Coverage	250M+ works	200M+ papers	2.4M+ preprints
Citation data	Fully open	Partially open	None
Institutions	✓ Full affiliations	✓ Limited	✗
Funding	✓ NSF, NIH, etc.	✗	✗
Open access	✓ Full OA status	✓ PDF links	✓ All papers
API key	Optional (free)	Optional (free)	Not required
Rate limits	1,000 searches/day (free key)	Unknown	1 req/3s
Abstract	✓ Full text	✓ TLDR	✓ Full text
Best for	Comprehensive metadata, institutions, funding	Citation counts, venue info	Latest preprints

When to use OpenAlex over S2:

• Need institutional affiliation data
• Need funding information
• Want fully open citation graph
• Need comprehensive topic/keyword metadata
• Working with non-CS fields (OpenAlex covers all disciplines)

When to use S2 over OpenAlex:

• Need real-time citation counts (S2 updates faster)
• Need "highly influential citations" metric
• Need paper recommendations
• CS/AI-focused research (S2 has better CS coverage)