Nber Working Papers ApiSAFE
🔬 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.
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.
e1ba289846fdOBSERVED · 2026-10-08Host compatibility
What the documentation claims. We have not run a compatibility test.
| Host | Status | Notes |
|---|---|---|
| openclaw | mentioned |
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: nber-working-papers-api
description: "Access NBER working papers and economic research datasets"
metadata:
openclaw:
emoji: "📈"
category: "domains"
subcategory: "economics"
keywords: ["NBER", "working papers", "economics research", "macroeconomics", "economic policy", "recession dating"]
source: "https://www.nber.org/"
---
# NBER Working Papers and Data API
## Overview
The National Bureau of Economic Research (NBER) is the leading U.S. economics research organization, publishing 1,200+ working papers annually by top economists. NBER papers are among the most cited in economics. The website provides structured access to working papers, researcher profiles, and macroeconomic datasets. Free metadata access; some full text requires subscription.
## Working Papers Access
### RSS/Atom Feeds
```bash
# Latest working papers feed
curl "https://www.nber.org/papers.rss"
# Papers by program
curl "https://www.nber.org/programs/ef/papers.rss" # Economic Fluctuations
curl "https://www.nber.org/programs/ls/papers.rss" # Labor Studies
curl "https://www.nber.org/programs/io/papers.rss" # Industrial Organization
```
### Working Paper Search
```bash
# Search via NBER website (HTML scraping needed)
curl "https://www.nber.org/api/v1/working_page_listing/contentType/working_paper/?page=1&perPage=20&q=inflation+expectations"
# Get specific paper metadata
curl "https://www.nber.org/api/v1/working_page_listing/contentType/working_paper/?page=1&perPage=1&q=w28104"
```
### NBER Data Portal
```bash
# Macroeconomic history data
# Available at: https://data.nber.org/
# Business cycle dates
curl "https://data.nber.org/data/cycles/business_cycle_dates.json"
# CPS labor data extracts
# https://data.nber.org/cps/
```
## NBER Programs
| Code | Program | Focus |
|------|---------|-------|
| `ef` | Economic Fluctuations and Growth | Macro, business cycles |
| `ls` | Labor Studies | Employment, wages |
| `io` | Industrial Organization | Markets, competition |
| `pe` | Public Economics | Taxation, spending |
| `he` | Health Economics | Healthcare markets |
| `de` | Development Economics | Developing countries |
| `if` | International Finance | Exchange rates, capital flows |
| `it` | International Trade | Trade policy |
| `me` | Monetary Economics | Central banking |
| `cf` | Corporate Finance | Firm finance |
| `ap` | Asset Pricing | Financial markets |
| `ed` | Education | Education economics |
| `ag` | Aging | Demographics |
| `ch` | Children | Child welfare |
| `le` | Law and Economics | Legal institutions |
| `env` | Environment and Energy | Environmental policy |
| `pol` | Political Economy | Political institutions |
## Python Usage
```python
import requests
from xml.etree import ElementTree
def get_latest_papers(program: str = None,
count: int = 20) -> list:
"""Get latest NBER working papers via RSS."""
if program:
url = f"https://www.nber.org/programs/{program}/papers.rss"
else:
url = "https://www.nber.org/papers.rss"
resp = requests.get(url, timeout=30)
resp.raise_for_status()
root = ElementTree.fromstring(resp.content)
papers = []
for item in root.findall(".//item")[:count]:
papers.append({
"title": item.findtext("title", ""),
"link": item.findtext("link", ""),
"description": item.findtext("description", "")[:300],
"pub_date": item.findtext("pubDate", ""),
})
return papers
def search_papers(query: str, page: int = 1,
per_page: int = 20) -> list:
"""Search NBER working papers."""
resp = requests.get(
"https://www.nber.org/api/v1/working_page_listing/"
"contentType/working_paper/",
params={"q": query, "page": page, "perPage": per_page},
timeout=30,
)
resp.raise_for_status()
data = resp.json()
results = []
for item in data.get("results", []):
results.append({
"title": item.get("title"),
"authors": item.get("authors", ""),
"number": item.get("wp_number", ""),
"date": item.get("date", ""),
"url": f"https://www.nber.org/papers/{item.get('wp_number', '')}",
"abstract": item.get("description", "")[:300],
"program": item.get("programs", []),
})
return results
def get_business_cycle_dates() -> list:
"""Get NBER official business cycle dates."""
resp = requests.get(
"https://data.nber.org/data/cycles/business_cycle_dates.json",
timeout=30,
)
resp.raise_for_status()
return resp.json()
# Example: latest macro working papers
papers = get_latest_papers(program="ef", count=5)
for p in papers:
print(f"{p['title']}")
print(f" {p['link']}")
# Example: search for AI economics papers
results = search_papers("artificial intelligence labor market")
for r in results:
print(f"[{r['number']}] {r['title']}")
print(f" Authors: {r['authors']}")
# Example: recession dates
cycles = get_business_cycle_dates()
for c in cycles[-3:]:
print(f"Peak: {c.get('peak')} → Trough: {c.get('trough')}")
```
## Key Datasets
| Dataset | Description |
|---------|-------------|
| Business Cycle Dates | Official US recession start/end dates |
| CPS Extracts | Current Population Survey labor data |
| Macrohistory Database | 150 years of macro indicators |
| Patent Data | Patent citation and classification |
| Trade Data | Bilateral trade statistics |
## References
- [NBER](https://www.nber.org/)
- [NBER Working Papers](https://www.nber.org/papers)
- [NBER Data](https://data.nber.org/)
- [NBER Programs](https://www.nber.org/programs-projects/programs)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.
| Layer | What it checks | Result |
|---|---|---|
| L0 | Provenance & inventory | PASS |
| L1 | Static analysis of the code | NA |
| L2 | Instruction surface (what it tells the agent) | PASS |
| L3 | Class-specific surface | PASS |
| L4 | Behavioural (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.
e1ba289846fdfull audit observations/trust-audit/skill/brycewang-stanford__nber-working-papers-api.json · Report an issue / request a re-scanAudit history
Every audit this skill has had.
| Date | Source | Verdict | Grade | Score | Change |
|---|---|---|---|---|---|
| 2026-10-08 | e1ba289846fd | SAFE | B | 89 | first audit |
Questions
What does the Nber Working Papers Api 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 Nber Working Papers Api 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 Nber Working Papers Api access on my machine?
The audit observed no filesystem, network or shell use at all in its source.
Which assistants does Nber Working Papers Api 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.