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 ror-organization-api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 | ror-organization-api |
| description | Identify and link research organizations via the ROR registry API |
| metadata | {"openclaw":{"emoji":"🏢","category":"literature","subcategory":"metadata","keywords":["ROR","research organizations","institution registry","affiliation","organization identifiers","ISNI"],"source":"https://ror.org/"}} |
ROR is the community-led registry of open persistent identifiers for research organizations worldwide — 110,000+ entries covering universities, research institutes, government agencies, hospitals, and companies. The API enables affiliation disambiguation, institutional search, and metadata retrieval. Essential for bibliometrics, funder compliance, and research analytics. Free, no authentication required.
https://api.ror.org/v2
# Text search
curl "https://api.ror.org/v2/organizations?query=MIT"
# Affiliation matching (fuzzy match for messy affiliation strings)
curl "https://api.ror.org/v2/organizations?affiliation=Dept+of+CS,+Massachusetts+Inst+of+Technology"
# Filter by country
curl "https://api.ror.org/v2/organizations?query=university&filter=locations.geonames_details.country_code:US"
# Filter by organization type
curl "https://api.ror.org/v2/organizations?query=research&filter=types:facility"
# Retrieve full record
curl "https://api.ror.org/v2/organizations/https://ror.org/042nb2s44"
# Also works with just the ID portion
curl "https://api.ror.org/v2/organizations/042nb2s44"
| Parameter | Description | Example |
|---|---|---|
query | Text search | query=Harvard |
affiliation | Fuzzy affiliation match | affiliation=MIT Cambridge MA |
filter | Faceted filtering | filter=types:education |
page | Page number (1-based) | page=2 |
| Type | Description |
|---|---|
education | Universities, colleges |
facility | Research facilities, labs |
healthcare | Hospitals, medical centers |
company | Companies with research activities |
government | Government agencies |
nonprofit | Non-profit research organizations |
funder | Funding agencies |
archive | Archives, libraries |
{
"number_of_results": 3,
"items": [
{
"id": "https://ror.org/042nb2s44",
"names": [
{"value": "Massachusetts Institute of Technology", "types": ["ror_display"]},
{"value": "MIT", "types": ["acronym"]}
],
"types": ["education"],
"locations": [
{
"geonames_details": {
"country_code": "US"
import requests
BASE_URL = "https://api.ror.org/v2/organizations"
def search_organizations(query: str,
country: str = None,
org_type: str = None) -> list:
"""Search ROR for research organizations."""
params = {"query": query}
filters = []
if country:
filters.append(
f"locations.geonames_details.country_code:{country}")
if org_type:
filters.append(f"types:{org_type}")
if filters:
params["filter"] = ",".join(filters)
resp = requests.get(BASE_URL, params=params)
resp.raise_for_status()
data = resp.json()
results = []
for org in data.get("items", []):
display_name = next(
(n["value"] for n in org.get("names", [])
if "ror_display" in n.get("types", [])),
org.get("names", [{}])[0].get("value", ""),
)
acronyms = [n["value"] for n in org.get("names", [])
if "acronym" in n.get("types", [])]
loc = org.get(, [{}])[].get(, {})
results.append({
: org.get(),
: display_name,
: acronyms,
: org.get(, []),
: loc.get(),
: loc.get(),
: org.get(),
})
results
() -> :
resp = requests.get(
BASE_URL,
params={: affiliation_string},
)
resp.raise_for_status()
items = resp.json().get(, [])
items items[].get():
items[].get(, {})
items[] items {}
() -> :
resp = requests.get()
resp.raise_for_status()
resp.json()
orgs = search_organizations(, country=,
org_type=)
o orgs:
(
)
result = match_affiliation(
)
(
)