Atlas / Skills / brycewang-stanford / Database Comparison Guide

Database Comparison GuideSAFE

skills/brycewang-stanford/database-comparison-guide

🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文,并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.

Verdict
SAFE
Grade
B
Trust score
89 /100
Version
—
Hosts
1 documented
License
NOASSERTION
Stars
4,535
01

Overview

🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文,并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.

Read from source at commit e1ba289846fdOBSERVED · 2026-10-08
02

Host compatibility

What the documentation claims. We have not run a compatibility test.

HostStatusNotes
openclawmentioned
03

What it tells the agent

The instruction file, verbatim from the audited commit — this is the text the model reads, and the surface the audit's instruction layer examines. Quoted here so you can judge it without cloning anything.

---
name: database-comparison-guide
description: "Compare major academic databases and when to use each for research"
metadata:
  openclaw:
    emoji: "🗄️"
    category: "literature"
    subcategory: "search"
    keywords: ["academic database search", "scholarly database", "search strategy", "field-specific search"]
    source: "wentor-research-plugins"
---

# Database Comparison Guide

A comprehensive reference for choosing and querying the right academic database for your research domain, including coverage details, advanced operators, and cross-database strategies.

## Overview of Major Academic Databases

| Database | Coverage | Disciplines | Access Model | Unique Strength |
|----------|----------|-------------|--------------|-----------------|
| Web of Science | 1900-present, 21,000+ journals | Multidisciplinary | Subscription | Citation indexing, Journal Impact Factor |
| Scopus | 1970-present, 27,000+ journals | Multidisciplinary | Subscription | Largest abstract/citation DB, CiteScore |
| PubMed | 1946-present, 35M+ records | Biomedical, life sciences | Free | MeSH controlled vocabulary, clinical filters |
| IEEE Xplore | 1872-present, 6M+ docs | Engineering, CS | Subscription | Conference proceedings, standards |
| Google Scholar | Broad, undisclosed | All fields | Free | Widest coverage, full-text indexing |
| JSTOR | Historical archives | Humanities, social sciences | Subscription | Historical journal runs, primary sources |
| arXiv | 1991-present, 2.4M+ papers | Physics, CS, Math, Bio | Free | Preprints, no peer-review delay |
| SSRN | 1994-present | Social sciences, law | Free | Working papers, early-stage research |

## Field-Specific Database Selection

### STEM Fields

For physics, computer science, and mathematics, combine arXiv preprints with Web of Science indexed journals:

```
# arXiv API query for recent ML papers
curl "http://export.arxiv.org/api/query?search_query=cat:cs.LG+AND+ti:transformer&start=0&max_results=25&sortBy=submittedDate&sortOrder=descending"
```

For biomedical research, PubMed with MeSH terms provides the most precise retrieval:

```
# PubMed E-utilities search with MeSH
curl "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi?db=pubmed&term=%22machine+learning%22[MeSH]+AND+%22drug+discovery%22[MeSH]&retmax=50&sort=date"
```

### Social Sciences and Humanities

- **Economics/Business**: Scopus + SSRN + RePEc (for working papers)
- **Psychology**: PsycINFO (APA) + PubMed
- **Law**: Westlaw + SSRN + HeinOnline
- **History/Literature**: JSTOR + Project MUSE + MLA International Bibliography

## Advanced Search Operators by Database

### Web of Science

```
TS=("deep learning" AND "drug discovery") AND PY=(2020-2025)
# TS = Topic (title + abstract + keywords)
# PY = Publication Year
# Use NEAR/x for proximity: TS=("climate" NEAR/3 "adaptation")
```

### Scopus

```
TITLE-ABS-KEY("deep learning" AND "drug discovery") AND PUBYEAR > 2019
# Additional operators:
# AUTHLASTNAME(smith) AND AUTHFIRST(j*)
# AFFIL("MIT" OR "Massachusetts Institute of Technology")
# REF("seminal paper title")
```

### PubMed

```
"deep learning"[Title/Abstract] AND "drug discovery"[Title/Abstract]
AND ("2020/01/01"[Date - Publication] : "2025/12/31"[Date - Publication])
# Use filters: Clinical Trial[pt], Review[pt], Free Full Text[Filter]
```

## Cross-Database Search Strategy

A robust literature search should query multiple databases to maximize recall:

1. **Define your research question** using PICO (Population, Intervention, Comparison, Outcome) or PCC (Population, Concept, Context) frameworks.
2. **Identify controlled vocabulary** for each database (MeSH for PubMed, Emtree for Embase, Thesaurus for PsycINFO).
3. **Build search strings** combining controlled vocabulary with free-text synonyms using Boolean operators.
4. **Execute searches** across at least 2-3 databases relevant to your field.
5. **Deduplicate results** using reference managers (Zotero, EndNote) or tools like Covidence.
6. **Document your search** with database, date, exact query string, and result count for reproducibility.

## Practical Tips

- **Scopus vs. Web of Science**: Scopus has broader coverage (especially post-2000 and non-English journals); WoS has deeper historical archives and the Journal Impact Factor.
- **Google Scholar** finds the most results but lacks advanced filtering. Use it for snowball searches and finding grey literature, not as your primary systematic search tool.
- **API access**: PubMed (E-utilities), OpenAlex, and Crossref all offer free APIs for programmatic searching. Scopus and WoS require institutional API keys.
- **Alert services**: Set up saved search alerts on PubMed, Scopus, and Google Scholar to stay current in fast-moving fields.
04

Trust audit

SAFEgrade B · trust 89/100 Nothing in the source contradicts what it says it does. Grade A is reserved for packages that have also passed the behavioural sandbox.

LayerWhat it checksResult
L0Provenance & inventoryPASS
L1Static analysis of the codeNA
L2Instruction surface (what it tells the agent)PASS
L3Class-specific surfacePASS
L4Behavioural (sandbox)SKIPPED

What the source does

Filesystem
none-observed
Network
none-observed
Shell
none-observed
Dependencies
pinned
Secrets in source
none-found

Findings (0)

No findings outside the package's declared scope.

Gates applied: no_behavioural_pass.

Audited 2026-10-08 · audit v0.4.1 · source sha e1ba289846fdfull audit observations/trust-audit/skill/brycewang-stanford__database-comparison-guide.json · Report an issue / request a re-scan
05

Audit history

Every audit this skill has had.

DateSourceVerdictGradeScoreChange
2026-10-08e1ba289846fdSAFEB89first audit
06

Questions

What does the Database Comparison Guide skill do?

🔬 A curated collection of 23,000+ agent skills for empirical research across 8 social science disciplines. | 精选 23,000+ AI Agent 技能库,覆盖8大社会科学学科的实证研究。CoPaper.AI 20分钟完成一篇可复现的规范实证论文,并支持用户上传 Skills。-- Maintained by CoPaper.AI from Stanford REAP.

Is Database Comparison Guide safe to install?

The audit found nothing in the source that contradicts what it says it does, and graded it B (89/100). Grade A is held back for packages that have also passed a sandboxed behavioural run, which is why a clean skill reads B.

What can Database Comparison Guide access on my machine?

The audit observed no filesystem, network or shell use at all in its source.

Which assistants does Database Comparison Guide work with?

Its documentation mentions openclaw. That is what the text claims, not a compatibility test we ran.

How current is this page?

The grade is for one exact copy of the source (e1ba289846fd), read on 2026-10-08. The repository is watched, and a new audit runs when it changes — this is the first audit.

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