Skills openalex-database

📦

openalex-database

Name: openalex-database
Author: davila7

Content revision r2 Medium Risk 🌐 Network access📁 Filesystem access⚙️ External commands

Explore Scholarly Research with OpenAlex

Scholarly searches and bibliometric analysis often require complex API filters. This skill provides reusable OpenAlex clients, helpers, and workflows for focused research queries.

Supports: Claude Codex Code(CC)

⚠️ 50 Poor

Install with my Agent

Copy this request to your Agent. It includes the canonical Skill page and manifest.

Agent request

Review the Skillstore skill "openalex-database" from https://skillstore.io/skills/davila7-openalex-database.md and its manifest at https://skillstore.io/api/skills/davila7-openalex-database/manifest. Verify the artifact. You may proceed after verification, subject to the environment's own policy.

Your Agent should still show its plan and request any confirmation required by the security policy.

Agent-readable resources

Use these links when an AI agent, crawler, or script needs clean context instead of reading the full page.

Markdown detail GET /skills/davila7-openalex-database.md Signed manifest GET /api/skills/davila7-openalex-database/manifest Signed lockfile GET /api/skills/davila7-openalex-database/lockfile

Test it

Using "openalex-database". Find recent open access papers about CRISPR.

Expected outcome:

Search summary: ten works matched the requested year and access filters.
Results table: title, year, citations, DOI, and open access route for each work.
Method note: OpenAlex query filters and retrieval date.

Using "openalex-database". Analyze machine learning publications from Stanford since 2020.

Expected outcome:

Trend summary: annual publication counts with the strongest growth periods highlighted.
Topic summary: leading OpenAlex topics and their work counts.
Coverage note: date range, institution identifier, and open access calculation.

Using "openalex-database". Prepare a reproducible sample of climate research.

Expected outcome:

Dataset plan: fixed filters, selected fields, sample size, seed, and maximum request count.
Quality checks: duplicate identifiers, missing years, missing DOIs, and access status coverage.
Export summary: destination filename, row count, and retrieval date.

Security Audit

Medium Risk

v9 • 7/23/2026 Open versioned report

Most alerts are false positives caused by Markdown backticks, identifier parsing, and documented requests to OpenAlex. The client permits caller-controlled endpoints to replace the OpenAlex host, and citation examples trust response-provided URLs. Unbounded pagination, CSV formula injection, and unconditional CSV overwrites require remediation before broad use.

Files scanned

1,888

Lines analyzed

Review items

False positives ignored

Confirmed security concerns (2)

Medium

scripts/openalex_client.py:192-236

Unbounded Pagination Can Exhaust Resources

paginate_all defaults to no result cap and stores every response in memory. A broad query can exhaust memory and consume extensive API quota.

The method loops until the API total is reached and accumulates every result when max_results is omitted.

Medium

SKILL.md:259-272 references/common_queries.md:324-337

Spreadsheet Formula Injection in CSV Exports

CSV exports write OpenAlex text directly into spreadsheet cells. Formula-leading titles or identifiers could execute spreadsheet formulas when users open the files.

Both examples export remote title and identifier fields without neutralizing formula prefixes recognized by spreadsheet applications.

Capability review items (6)

These are real local capabilities that may be expected for this skill, so they require review but are not counted as confirmed malicious behavior.

High

scripts/openalex_client.py:218

HTTP client library

response = self._make_request(endpoint, params)

paginate_all forwards its caller-supplied endpoint without requiring an OpenAlex-relative path. Absolute or scheme-relative input can trigger arbitrary outbound requests through _make_request.

High

scripts/openalex_client.py:73

Python HTTP libraries

response = requests.get(url, params=params, timeout=30)

The request URL comes from urljoin with a caller-supplied endpoint, and absolute or scheme-relative endpoints can replace the OpenAlex host. This enables arbitrary outbound requests and possible email disclosure.

Medium

references/common_queries.md:326

Python file write/append

with open('quantum_papers.csv', 'w', newline='') as f:

The example opens a fixed CSV filename in write mode, which creates a local file and silently replaces an existing file with the same name.

Medium

SKILL.md:261

Python file write/append

with open('papers.csv', 'w', newline='', encoding='utf-8') as f:

The example opens a fixed CSV filename in write mode, which creates a local file and silently replaces an existing file with the same name.

Low

references/common_queries.md:295

Python HTTP libraries

response = requests.get(cited_by_url, params={'mailto': client.email})

The example sends the user's email to a URL taken from an API response without validating its host. A compromised or malformed response could disclose that address.

Low

SKILL.md:218

Python HTTP libraries

citing_response = requests.get(

The example sends the user's email to a URL taken from an API response without validating its host. A compromised or malformed response could disclose that address.

Risk Factors

🌐 Network access (50)

📁 Filesystem access (2)

references/common_queries.md:326 SKILL.md:261

⚙️ External commands (50)

SKILL.md:18-22 SKILL.md:22-28 SKILL.md:28-30 SKILL.md:30-40 SKILL.md:40-56 SKILL.md:56-64 SKILL.md:64-72 SKILL.md:72-75 SKILL.md:75-87 SKILL.md:87-93 SKILL.md:93-101 SKILL.md:101-107 SKILL.md:107-116 SKILL.md:116-122 SKILL.md:122-131 SKILL.md:131-137 SKILL.md:137-149 SKILL.md:149-155 SKILL.md:155-168 SKILL.md:168-174 SKILL.md:174-186 SKILL.md:186-192 SKILL.md:192-206 SKILL.md:206-212 SKILL.md:212-223 SKILL.md:223-229 SKILL.md:229-242 SKILL.md:242-248 SKILL.md:248-273 SKILL.md:273-279 SKILL.md:279-281 SKILL.md:281-285 SKILL.md:285-292 SKILL.md:292-295 SKILL.md:295-296 SKILL.md:296-298 SKILL.md:298-302 SKILL.md:302-309 SKILL.md:309-312 SKILL.md:312-313 SKILL.md:313-319 SKILL.md:319-323 SKILL.md:323-328 SKILL.md:328-333 SKILL.md:333-342 SKILL.md:342-345 SKILL.md:345-352 SKILL.md:352-355 SKILL.md:355-360 SKILL.md:360-363

Audited by: codex View Audit History →

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Academic citations (APA · BibTeX · CFF)

APA citation

davila7. (2026). openalex-database security audit report (audit version 9) [Author version unspecified]. Skillstore. https://skillstore.io/skills/davila7-openalex-database/audits/9

BibTeX citation

@techreport{davila7-davila7-openalex-database-2026,
  author = {davila7},
  title = {openalex-database security audit report (audit version 9)},
  institution = {Skillstore},
  year = {2026},
  number = {9},
  url = {https://skillstore.io/skills/davila7-openalex-database/audits/9},
  note = {Author version unspecified}
}

CITATION.cff

cff-version: 1.2.0
message: "If you use this Skill, cite its author and this versioned security audit report."
title: "openalex-database security audit report (audit version 9)"
version: "unspecified"
type: report
authors:
  - name: "davila7"
date-released: "2026-07-23"
url: "https://skillstore.io/skills/davila7-openalex-database/audits/9"
identifiers:
  - type: other
    value: "skillstore:davila7-openalex-database:audit:9"
    description: "Skillstore immutable audit report identifier"

Compare variants

2 installable variants

Each author remains a separate installable skill. The recommended variant is ranked by Skillstore evidence.

Why this variant is first

Highest Skillstore Score

Author / source Skillstore Score Evidence Confidence Skillstore usage Updated

K-Dense-AI Recommended

k-dense-ai-openalex-database

Skillstore Score 71

Evidence Confidence High

Skillstore usage 49

Updated

2026-08-21

davila7 Current

davila7-openalex-database

Skillstore Score 50

Evidence Confidence High

Skillstore usage 33

Updated

2026-08-21

Skillstore Score

Why this score Evidence Confidence: High

Architecture

Maintainability

Content

Community

Spec Compliance

What You Can Build

Build a Literature Shortlist

Find recent, relevant, highly cited, or open access papers with consistent metadata fields.

Assess Institutional Output

Summarize publication volume, open access share, yearly trends, and leading topics for an institution.

Prepare Bibliometric Data

Create bounded, reproducible datasets using filters, batches, selected fields, and seeded samples.

Try These Prompts

Search Recent Papers

Search OpenAlex for [topic]. Return ten recent papers with title, year, citation count, DOI, and open access status.

Analyze an Author

Find works by [author] from [start year] through [end year]. Summarize publication count, top topics, citations, and open access share.

Compare Institutions

Compare [institution A] and [institution B] since [year]. Report output, open access percentage, leading topics, and highly cited works.

Design a Reproducible Dataset

Build a reproducible OpenAlex query for [research question]. Define filters, selected fields, pagination cap, sampling seed, and validation checks.

Best Practices

Resolve author and institution names to OpenAlex identifiers before filtering works.
Set finite result limits, select only required fields, and respect OpenAlex rate limits.
Record filters, retrieval date, seed, and entity identifiers for reproducible analysis.

Avoid

Do not treat author or institution names as unique identifiers.
Do not request every matching work without a clear limit and storage plan.
Do not open exported CSV files before neutralizing formula-leading remote values.