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默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。
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决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。
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默认使用会先检查来源的 Prompt;你也可以切换为直接命令,或下载本地副本。
决定是否安装前,请先阅读 SKILL.md,以及 SkillsMP 当前展示的配套文件。
用 Codex 或 Claude 帮你安装 复制这段 Prompt,粘贴到 Codex、Claude 或其他助手里,让它检查 Skill 页面并帮你完成安装。
直接命令不会经过审查 Prompt;运行前请先检查来源。
npx skills add https://github.com/brycewang-stanford/Auto-Empirical-Research-Skills --skill boolean-search-guide命令会保持在同一行。复制前请横向滚动并检查完整内容。
想先保存到本地?可下载 SkillsMP 当前能够提供的文件。
Route empirical-research requests through the Auto-Empirical Research Skills catalog when this whole repository is installed as one skill in Codex, CodeBuddy, Claude Code, or another IDE. Use to choose and load the right vendored AERS skill for causal inference, econometrics, replication, data acquisition, manuscript writing, peer review and referee responses, citation checking, de-AIGC editing, or full empirical-paper workflows without reading the entire repository at once.
中英双语学术降 AIGC / bilingual academic de-AIGC skill. Removes AI-generated writing signatures from empirical papers in economics, management, and the social sciences — in both English and Chinese. Covers Turnitin AI, GPTZero, Originality.ai on the English side and 知网 AMLC, 万方, 维普 on the Chinese side. Uses a six-step loop (intake → audit → claim-evidence check → differentiated rewrite → five-dimension self-score → cold-reader recheck) with two pattern libraries (22 English + 17 Chinese patterns), section-by-section strategies for empirical papers, and hard protections that keep every number, coefficient, and citation intact.
Use when a research task needs reproducible Kaggle discovery, metadata inspection, bounded public-data downloads, competition or kernel discovery, model discovery, or an explicitly approved Kaggle write/delete operation through the official CLI.
基于 SOC 职业分类
正在显示 SKILL.md
| name | boolean-search-guide |
| description | Master Boolean operators and advanced search syntax for academic databases |
| metadata | {"openclaw":{"emoji":"🔎","category":"literature","subcategory":"search","keywords":["boolean search","search operators","database search","PubMed","Web of Science","search strategy"],"source":"wentor-research-plugins"}} |
A skill for constructing precise, reproducible search queries using Boolean operators across major academic databases. Covers AND, OR, NOT logic, proximity operators, truncation, field codes, and strategies for building systematic search strings.
AND — Narrows results. Both terms must appear.
"machine learning" AND "drug discovery"
OR — Broadens results. Either term may appear.
"deep learning" OR "neural network"
NOT — Excludes results. Removes records containing the term.
cancer NOT "lung cancer"
() — Groups terms to control evaluation order.
(COVID-19 OR SARS-CoV-2) AND (vaccine OR vaccination)
Databases evaluate Boolean expressions in this order unless parentheses override:
Always use parentheses to make your intent explicit:
# Ambiguous (results depend on database precedence):
sleep disorders OR insomnia AND cognitive performance
# Clear (intended meaning explicit):
(sleep disorders OR insomnia) AND cognitive performance
* — Truncation (unlimited characters)
therap* matches therapy, therapies, therapeutic, therapeutics
? — Single-character wildcard
wom?n matches woman, women
$ — Optional character (some databases)
behavio$r matches behavior, behaviour
| Database | Operator | Example | Meaning |
|---|---|---|---|
| PubMed | Not supported | -- | Use phrase search instead |
| Web of Science | NEAR/n | climate NEAR/3 adaptation | Within 3 words |
| Scopus | W/n | gene W/5 therapy | Within 5 words, ordered |
| Scopus | PRE/n | drug PRE/3 resistance | First term precedes second |
| ProQuest | N/n, P/n | poverty N/5 education | Within 5 words |
| EBSCO | Nn | mental N3 health | Within 3 words |
PubMed:
"machine learning"[Title]
"Smith J"[Author]
"Nature"[Journal]
"2020/01/01"[Date - Publication] : "2024/12/31"[Date - Publication]
Web of Science:
TI=("deep learning")
AU=(Smith, John)
SO=(Nature)
PY=(2020-2024)
Scopus:
TITLE("deep learning")
AUTH(Smith)
SRCTITLE(Nature)
PUBYEAR > 2019
def build_pico_search(population: str, intervention: str,
comparison: str, outcome: str) -> str:
"""
Construct a Boolean search string from PICO components.
Args:
population: Target population terms (OR-separated)
intervention: Intervention terms (OR-separated)
comparison: Comparator terms (OR-separated, may be empty)
outcome: Outcome terms (OR-separated)
Returns:
Complete Boolean search string
"""
blocks = []
blocks.append(f"({population})")
blocks.append(f"({intervention})")
if comparison:
blocks.append(f"({comparison})")
blocks.append(f"({outcome})")
return " AND ".join(blocks)
# Example: Effect of mindfulness on anxiety in college students
query = build_pico_search(
population='"college students" OR "university students" OR undergraduates',
intervention='mindfulness OR "mindfulness-based stress reduction" OR MBSR',
comparison='"wait list" OR "waitlist" OR "usual care" OR "control group"',
outcome='anxiety OR "generalized anxiety" OR GAD OR "anxiety symptoms"'
)
print(query)
1. Identify key concepts from your research question
2. List synonyms, related terms, and variant spellings for each concept
3. Combine synonyms within each concept using OR
4. Connect concept blocks using AND
5. Test the search in your target database
6. Review the first 50 results for relevance
7. If recall is too low: add more synonyms, use truncation
8. If precision is too low: add more AND blocks, use field limits
9. Document the final search string with date and result count
Language: English, Chinese, Spanish, etc.
Date range: Publication year or date added
Document type: Journal article, review, conference paper
Study design: RCT, cohort, case-control (PubMed clinical queries)
Species: Human, animal (PubMed)
Open access: Free full text available
PubMed provides validated search filters (hedges) for specific study types. Append these to your search:
# Therapy/Intervention (sensitive):
AND (randomized controlled trial[pt] OR controlled clinical trial[pt]
OR randomized[tiab] OR randomly[tiab] OR trial[tiab])
# Diagnosis (specific):
AND (sensitivity and specificity[MeSH] OR predictive value of tests[MeSH]
OR accuracy[tiab])
# Systematic Reviews:
AND (systematic review[pt] OR meta-analysis[pt] OR systematic[sb])
For systematic reviews and reproducible research, always record:
Store search strategies in a version-controlled file alongside your project so they can be independently verified and updated.