DAAF Contribution Community
Official@daaf-contribution-community
Provides standardized access and analytical frameworks for U.S. educational, demographic, and institutional datasets to support rigorous policy and equity research.
Agent Skills by DAAF Contribution Community
Showing 25 vetted skills indexed across 1 GitHub repositories.
DAAF-Contribution-Communityeducation-data-source-crdc
Document CRDC data elements, methodology, and legal context for educational equity analysis.
DAAF-Contribution-Communityeducation-data-query
Downloads educational datasets from configured mirror sources and filters them locally with Polars.
DAAF-Contribution-Communityeducation-data-source-nhgis
Access US Census Bureau data via NHGIS for education research.
DAAF-Contribution-Communityeducation-data-context
Explain data provenance, missing value codes, and variable definitions for Urban Institute Education Data Portal datasets.
DAAF-Contribution-Communityeducation-data-source-nccs
Access NCCS Form 990 data for private nonprofit higher education institutions.
DAAF-Contribution-Communityeducation-data-source-saipe
Retrieve U.S. Census Bureau SAIPE poverty estimates for school districts, counties, and states.
DAAF-Contribution-Communityelection-data-source-countypres
Fetch county-level U.S. presidential election returns from 2000-2024 via Harvard Dataverse.
DAAF-Contribution-Communityeducation-data-source-campus-safety
Retrieve and analyze U.S. Department of Education Campus Safety and Security data.
DAAF-Contribution-Communityeducation-data-source-fsa
Access Federal Student Aid datasets on grants, loans, and 90/10 revenue.
DAAF-Contribution-Communityplotly
Generate interactive Plotly charts from data with export options.
DAAF-Contribution-Communityeducation-data-source-scorecard
Analyze post-college earnings, debt, and loan repayment rates from College Scorecard data.
DAAF-Contribution-Communitydata-scientist
Enforce rigorous Python data analysis with validation, documentation, and verification.
DAAF-Contribution-Communityeducation-data-source-nacubo
Analyzes NACUBO endowment data for market values, returns, allocations, and spending rates.
DAAF-Contribution-Communityeducation-data-source-meps
Access Model Estimates of Poverty in Schools data for standardized school-level poverty analysis.
DAAF-Contribution-Communitymarimo
Create reactive Python notebooks with automatic cell re-execution.
DAAF-Contribution-Communityeducation-data-source-edfacts
Retrieve EDFacts state assessment, graduation rate, and accountability data.
DAAF-Contribution-Communityeducation-data-source-eada
Analyze gender equity in college athletics using EADA dataset with polars.
DAAF-Contribution-Communityeducation-data-source-ipeds
Interpret IPEDS postsecondary education data with cohort definitions and accounting standards.
DAAF-Contribution-Communityeducation-data-source-pseo
Analyze Postsecondary Employment Outcomes data for graduate earnings and industry employment.
DAAF-Contribution-Communitypolars
Manipulate tabular data with the Polars DataFrame library in Python.
DAAF-Contribution-Communityplotnine
Create data visualizations with the plotnine Python library.
DAAF-Contribution-Communityeducation-data-explorer
Explore Urban Institute Education Data Portal endpoints and variables for schools and colleges.
DAAF-Contribution-Communityskill-authoring
Guides users through creating Claude Skills with SKILL.md format and YAML frontmatter.
DAAF-Contribution-Communityagent-authoring
Create DAAF agent definition files following canonical templates and integration checklists.
Frequently Asked Questions About DAAF Contribution Community
FAQPage SchemaWhat specific research tasks are enabled by these data sources?▼
These resources enable quantitative analysis of educational equity, institutional financial health, and post-graduation employment outcomes. Users can retrieve, filter, and interpret complex datasets from the U.S. Department of Education, Census Bureau, and Urban Institute to perform standardized longitudinal research on school districts and higher education institutions.
Who is the target persona for these data integration modules?▼
The primary users are educational researchers, policy analysts, and data scientists focused on public sector data. These modules are designed for professionals requiring reproducible, documented access to federal education datasets and those needing to perform rigorous statistical validation on institutional performance metrics.
What are the technical prerequisites for running these data queries?▼
Users require a local environment capable of executing data processing tasks, specifically utilizing the Polars library for tabular manipulation. The modules rely on structured access to public endpoints and mirror sources, requiring standard connectivity to retrieve datasets before applying local filtering and analysis logic.