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 nsf-award-api-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.
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| name | nsf-award-api-guide |
| description | Search NSF awards and grants with free public API, no auth required |
| metadata | {"openclaw":{"emoji":"🏛️","category":"research","subcategory":"funding","keywords":["nsf","grants","funding","awards","national-science-foundation"],"source":"https://www.research.gov/common/webapi/awardapisearch-v1.htm"}} |
The National Science Foundation (NSF) Award Search API provides free, unauthenticated access to a comprehensive database of NSF-funded awards spanning decades of federally funded research in the United States. This API is invaluable for researchers seeking to understand funding trends, identify potential collaborators, or find precedent awards in their field.
The API covers all NSF directorates including Computer and Information Science and Engineering (CISE), Biological Sciences (BIO), Engineering (ENG), Geosciences (GEO), Mathematical and Physical Sciences (MPS), Social, Behavioral and Economic Sciences (SBE), and Education and Human Resources (EHR). Each award record includes principal investigator information, award amounts, abstracts, and institutional details.
No API key or authentication is needed. The service returns JSON or XML and supports a wide range of query parameters for precise filtering.
No authentication is required. The NSF Award Search API is completely open and free to use.
# No API key needed -- just make the request
curl "https://api.nsf.gov/services/v1/awards.json?keyword=quantum+computing"
GET https://api.nsf.gov/services/v1/awards.json?{params}
Key Parameters:
keyword: Full-text search across award title and abstractpiFirstName, piLastName: Filter by principal investigator nameawardeeCity, awardeeStateCode: Filter by institution locationstartDateStart, startDateEnd: Date range (format: MM/DD/YYYY)fundProgramName: NSF program nameawardeeName: Institution nameoffset: Pagination offset (default 1)printFields: Comma-separated list of fields to returnExample: Search for machine learning awards at MIT:
curl -s "https://api.nsf.gov/services/v1/awards.json?\
keyword=machine+learning&\
awardeeName=Massachusetts+Institute+of+Technology&\
printFields=id,title,piFirstName,piLastName,startDate,awardeeName,fundsObligatedAmt,abstractText&\
offset=1" | python3 -m json.tool
Retrieve details for a specific award by its NSF award number.
curl -s "https://api.nsf.gov/services/v1/awards/2345678.json?\
printFields=id,title,piFirstName,piLastName,startDate,expDate,awardeeName,fundsObligatedAmt,abstractText" \
| python3 -m json.tool
import requests
import time
base_url = "https://api.nsf.gov/services/v1/awards.json"
def search_nsf_awards(keyword, year_start, year_end, max_results=100):
"""Search NSF awards and return structured results."""
results = []
offset = 1
while len(results) < max_results:
params = {
"keyword": keyword,
"startDateStart": f"01/01/{year_start}",
"startDateEnd": f"12/31/{year_end}",
"printFields": "id,title,piFirstName,piLastName,startDate,awardeeName,fundsObligatedAmt",
"offset": offset
}
resp = requests.get(base_url, params=params)
data = resp.json()
awards = data.get("response", {}).get("award", [])
if not awards:
break
results.extend(awards)
offset += 25
time.sleep(0.5)
return results[:max_results]
awards = search_nsf_awards("large language models", 2022, 2025)
total_funding = sum(int(a.get("fundsObligatedAmt", 0)) for a in awards)
print(f"Found {len(awards)} awards, total funding: ${total_funding:,}")
for a awards[:]:
()
Grant Prospecting: Search for awards in your field to understand typical funding amounts, common program solicitations, and successful framing of research projects. Analyze abstracts of funded proposals for vocabulary and scope.
Collaborator Discovery: Search by keyword and explore the PI network to identify active researchers and institutions. Cross-reference with publication databases to find potential collaborators.
Funding Landscape Analysis: Track funding volumes over time for specific keywords or programs to identify emerging priorities and declining areas. Useful for strategic planning and grant writing.
Institutional Benchmarking: Compare award counts and funding totals across institutions for a given field or directorate.
offset to paginate)printFields to reduce response size and improve performance