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Turn OpenClaw into a No-Key Paper Scout for OpenAlex Research

A practical OpenClaw skill candidate for paper search, DOI lookup, citation-chain triage, and lightweight literature reviews using the free OpenAlex API. Not yet runner-tested; review artifacts should be queued before any install decision.

May 16, 2026
Original
Awesome OpenClaw Skills listOpen original externally
Status & Access
Current access and latest update details.
Access
Free
Updated
Jun 1, 2026, 09:54 AM

LinkLoot AI review

Use dummy data first

Score: 59/100
Flow and dependencies checked

Reviewed loot: Turn OpenClaw into a No-Key Paper Scout for OpenAlex Research

My take: this website/guide loot is usable, but not a blind buy or blind-use recommendation.

User decisionVerify first

My take: this website/guide loot is usable, but not a blind buy or blind-use recommendation.

The visible value is plausible and easier to judge through source/screenshot evidence.Judges how careful a user should be before signing up, downloading, or using it.
Reasons to use it
  • Keeps promise: The visible value is plausible and easier to judge through source/screenshot evidence.
  • Sources, external URL, and visible link/site signals were reviewed.
  • Install surface, scripts, dependencies, and suspicious patterns were checked statically.
  • Optional page snapshot. For code repositories this is context, not security proof.
Reasons to be careful
  • Practical guide replay: No supported end-to-end replay was completed for this guide.
  • The payload selects workflow_automation, but the title, tags, and sources show an OpenClaw skill with SKILL.md and a Python script. For visitors, code/skill safety matters more than websi...
  • Safe to try: Judges how careful a user should be before signing up, downloading, or using it.
  • This repo/code loot has no CVE/advisory lookup result in this run.
Keeps promise83/100
Safe to try58/100
Easy to try63/100
Trust signals67/100
Worth following66/100
LLQI auditVerdict: RISKY
security & trust38/100
functionality & value48/100
quality & structure43/100
sources checked
code signals checked
snapshot optional
Dependency check missing

Automated AI review. Decision aid, not a safety guarantee. · 2026-06-01 04:59:52 UTC

What it does

Academic Research is an OpenClaw community skill that wraps OpenAlex lookups into agent-friendly research tasks: topic search, author search, DOI lookup, citation-chain exploration, open-access URL discovery, and a lightweight literature-review workflow. The source evidence says it uses OpenAlex without an API key and includes Python scripts for search and review generation.

Who should use it

Use this as a candidate for researchers, students, content teams, and agent builders who need fast paper triage before a deeper manual review. It is especially useful when the job is discovery and metadata synthesis rather than guaranteed full-text extraction or peer-reviewed conclusions.

Setup surface

The visible setup surface is small: a SKILL.md plus Python scripts that call public scholarly APIs. Source files reviewed from ClawHub show network calls to OpenAlex and Unpaywall, a /tmp cache for literature-review results, and optional markdown/JSON output. Pricing is classified as free because the ClawHub/source text states OpenAlex usage needs no API key and the page lists an MIT-0 license; no paid gate was visible in the fetched evidence.

Runner test plan

Before anyone installs or uses it, Runner AI Review should produce artifacts for: static scan of SKILL.md and all bundled scripts; dependency/install review, including Python package imports and whether requests is assumed or bundled; prompt-injection and tool-poisoning review of the skill text and generated outputs; sandbox execution against harmless OpenAlex queries with network egress restricted to expected domains; screenshot or video capture of representative command output; and a residual-risk note covering API data quality, cached files in /tmp, outbound scholarly API calls, and citation-synthesis hallucination risk.

Risk notes

This has not been tested, verified safe, or marked production-ready by LinkLoot Runner artifacts yet. The main visible risks are outbound network access, third-party scholarly data reliability, local cache writes under /tmp, and the temptation to treat generated literature reviews as authoritative. The skill should be reviewed as untrusted code and run only in a sandbox until Runner evidence exists.

Source links

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