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 osf-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.
基于 SOC 职业分类
正在显示 SKILL.md
| name | osf-api-guide |
| description | Access Open Science Framework for preregistrations, preprints, and data |
| metadata | {"openclaw":{"emoji":"🔓","category":"research","subcategory":"methodology","keywords":["osf","open-science","preregistration","preprints","reproducibility","collaboration"],"source":"https://developer.osf.io/"}} |
The Open Science Framework (OSF) is a free, open-source platform developed by the Center for Open Science (COS) that supports the entire research lifecycle. It provides tools for project management, preregistration of studies, data storage, preprint hosting, and research collaboration. OSF is widely used across social sciences, psychology, and increasingly in other disciplines as a hub for transparent and reproducible research.
The OSF API v2 is a JSON:API-compliant RESTful interface that provides programmatic access to the full range of OSF features. Researchers can search for preregistrations, browse preprints hosted on OSF Preprints and its community servers (such as PsyArXiv, SocArXiv, and BioHackrXiv), access project files and metadata, and manage their own research projects.
Public data on OSF is accessible without authentication. Creating or modifying resources requires a personal access token. The API is free for all users.
Public read access requires no authentication. For creating or modifying resources, generate a personal access token at https://osf.io/settings/tokens.
# Public access (no auth needed)
curl "https://api.osf.io/v2/nodes/?filter[title]=reproducibility"
# Authenticated access for write operations
export OSF_TOKEN=$OSF_TOKEN
curl -H "Authorization: Bearer $OSF_TOKEN" \
"https://api.osf.io/v2/users/me/"
Find public OSF projects by title, tags, or other attributes.
GET https://api.osf.io/v2/nodes/?filter[title]={query}
Parameters:
filter[title]: Filter by project title (contains match)filter[tags]: Filter by tagsfilter[category]: Filter by category (project, data, analysis, etc.)page[size]: Results per page (default 10, max 100)page: Page numberExample: Search for replication studies:
curl -s "https://api.osf.io/v2/nodes/?filter[title]=replication&page[size]=5" \
| python3 -m json.tool
Browse preprints across OSF and its community preprint servers.
GET https://api.osf.io/v2/preprints/?filter[provider]={provider}
curl -s "https://api.osf.io/v2/preprints/?filter[provider]=psyarxiv&page[size]=5" \
| python3 -m json.tool
Search for preregistered studies, a cornerstone of open science methodology.
GET https://api.osf.io/v2/registrations/?filter[title]={query}
curl -s "https://api.osf.io/v2/registrations/?filter[title]=cognitive+bias&page[size]=5" \
| python3 -m json.tool
import requests
import time
BASE_URL = "https://api.osf.io/v2"
def search_registrations(query, max_pages=5):
"""Search OSF registrations (preregistered studies)."""
all_results = []
url = f"{BASE_URL}/registrations/"
params = {
"filter[title]": query,
"page[size]": 25,
"page": 1
}
for page_num in range(1, max_pages + 1):
params["page"] = page_num
resp = requests.get(url, params=params)
data = resp.json()
results = data.get("data", [])
if not results:
break
all_results.extend(results)
time.sleep(0.5)
return all_results
registrations = search_registrations("randomized controlled trial")
print(f"Found {len(registrations)} preregistrations")
for reg in registrations[:5]:
attrs = reg.get("attributes", {})
print(f" Title: {attrs.get('title')}")
print(f" Created: {attrs.get('date_created', '')[:10]}")
print()
()
()
List files attached to an OSF project node.
curl -s "https://api.osf.io/v2/nodes/{node_id}/files/osfstorage/" \
| python3 -m json.tool
Preregistration Review: Search for preregistered studies in your field to understand how others formulate hypotheses, specify sample sizes, and plan analyses before data collection. This is essential for meta-science and methodological research.
Preprint Discovery: Use the preprints endpoint to find the latest unrefereed manuscripts across multiple community servers, getting access to cutting-edge findings before formal publication.
Open Data Access: Retrieve datasets attached to OSF projects for replication attempts, secondary analyses, or meta-analyses. OSF projects often include raw data, analysis scripts, and materials.
Collaboration Mapping: Explore contributors and linked projects to understand research collaboration networks in specific domains.
Reproducibility Audits: Programmatically check whether published studies have associated preregistrations, open data, or open materials on OSF.
page and page[size] parameters; default page size is 10data key, relationships are linkedfields[nodes]=title,date_created to request only needed fieldsembed=contributors to include related resources in a single requestlinks.next URL for pagination