/education-data-source-scorecard
College Scorecard — post-enrollment outcomes linking aid records to IRS/Treasury earnings. Earnings, loan repayment, debt via six Portal sub-datasets. Use when tax-record-based earnings needed. Tracks only Title IV aid recipients, not all students.
$ npx -y skills add brycewang-stanford/Auto-Empirical-Research-Skills --skill education-data-source-scorecard --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
- Fires itselfAuto-invocation. Claude auto-loads it when your prompt matches the work.Auto-invocation is when the right skill fires by itself at the right moment, driven by a FLOW.md router and a hook, instead of you invoking it by name. It is the difference between a skill being installed and a skill actually getting used.Read the full definition →
- You can call itInvoke it directly when you want it.
- Slash command
/education-data-source-scorecard
Context preview
The summary Claude sees to decide when to auto-load this skill.
College Scorecard — post-enrollment outcomes linking aid records to IRS/Treasury earnings. Earnings, loan repayment, debt via six Portal sub-datasets. Use when tax-record-based earnings needed. Tracks only Title IV aid recipients, not all students.
SKILL.md
education-data-source-scorecard.SKILL.mdname: education-data-source-scorecard
description: >-
College Scorecard — post-enrollment outcomes linking aid records to IRS/Treasury earnings. Earnings, loan repayment, debt via six Portal sub-datasets. Use when tax-record-based earnings needed. Tracks only Title IV aid recipients, not all students.
metadata:
audience: any-agent
domain: data-source
skill-authored: "2026-02-09"
skill-last-updated: "2026-02-09"
Scorecard Data Source Reference
College Scorecard — the primary institutional-level source for post-enrollment labor market outcomes, linking NSLDS financial aid records to IRS/Treasury earnings data. Use when comparing institutions on post-graduation earnings, loan repayment, or student debt, or when actual tax-record-based earnings are required rather than survey estimates. Covers six sub-datasets accessed via Portal mirrors. Critical limitation: tracks only Title IV federal aid recipients, not all students.
Federal data on post-college outcomes including earnings, debt, and repayment for students who received Title IV financial aid. Links education records to IRS tax data for actual earnings, making it the primary source for post-college labor market outcomes.
> **CRITICAL: Value Encoding and Missing Data** > > The Education Data Portal uses **integer encodings** for all categorical variables > and **lowercase, restructured variable names** that differ from the original > Scorecard column names. Suppression encoding differs by dataset: > > - **Earnings/counts**: `-3` integer code is the primary suppression indicator > - **Yes/No flags** (institutional characteristics): `null` for missing, `0`/`1` for valid > - **Rates** (repayment, default): `null` for missing > - The original Scorecard string `"PrivacySuppressed"` does NOT appear in Portal data > > | Context | `pred_degree_awarded_ipeds` | HBCU / tribal flags | `religious_affiliation` | > |---------|----------------------------|---------------------|-------------------------| > | **Portal (integer)** | `0`-`4` | `0` / `1` | Integer codes 22-200 | > | Original Scorecard | String labels | String labels | String labels | > > See `./references/variable-definitions.md` for complete encoding tables.
What is College Scorecard?
- **Publisher**: U.S. Department of Education
- **Primary value**: Post-college labor market outcomes (earnings) and debt/repayment metrics
- **Data sources**: NSLDS (loans/aid), IRS/Treasury (earnings), IPEDS (institutional characteristics)
- **Coverage**: **Title IV federal aid recipients only** — not all students
- **Unique feature**: Links education to IRS tax records for actual earnings data
- **Access**: Education Data Portal mirrors (parquet/CSV); see `datasets-reference.md` for paths, `mirrors.yaml` for mirror config, `fetch-patterns.md` for fetch code
- **Primary identifier**: `unitid` (IPEDS institution ID)
Reference File Structure
| File | Purpose | When to Read | |------|---------|--------------| | `earnings-data.md` | Post-college earnings methodology, cohorts, time horizons | Analyzing earnings outcomes | | `debt-repayment.md` | Student debt, repayment rates, default rates | Analyzing debt or loan outcomes | | `completion-rates.md` | Completion metrics vs IPEDS | Comparing graduation rates | | `population-coverage.md` | Title IV limitation details, who is included/excluded | Understanding data representativeness | | `variable-definitions.md` | Key variables, naming conventions, special values | Building queries or interpreting results | | `data-quality.md` | Suppression rules, selection bias, known limitations | Assessing data reliability | | `field-of-study.md` | Program-level earnings and debt data | Analyzing outcomes by major/CIP code |
Decision Trees
What outcome am I researching?
Outcome type?
├─ Post-college earnings
│ ├─ Institution-level → ./references/earnings-data.md
│ └─ By field of study → ./references/field-of-study.md
├─ Student debt levels
│ ├─ Cumulative borrowing → ./references/debt-repayment.md
│ └─ Debt by field → ./references/field-of-study.md
├─ Loan repayment/default
│ └─ Repayment rates → ./references/debt-repayment.md
├─ Completion rates
│ └─ Scorecard completion → ./references/completion-rates.md
└─ Understanding limitations
├─ Who is included → ./references/population-coverage.md
└─ Data quality issues → ./references/data-quality.mdHow do I interpret this data?
Interpretation question?
├─ Why are earnings suppressed?
│ └─ Privacy thresholds → ./references/data-quality.md
├─ What does "6-year earnings" mean?
│ └─ Cohort timing → ./references/earnings-data.md
├─ Why don't Scorecard rates match IPEDS?
│ └─ Different cohorts → ./references/completion-rates.md
├─ What loans are included in debt?
│ └─ Federal only → ./references/debt-repayment.md
└─ How representative is this data?
└─ Title IV coverage → ./references/population-coverage.mdBuilding a query?
Query construction?
├─ Variable names and codes → ./references/variable-definitions.md
├─ Suppression flags to handle → ./references/data-quality.md
├─ Understanding cohort years → ./references/earnings-data.md
└─ Field-level queries → ./references/field-of-study.md
Quick Reference: Scorecard Variables
Portal Data Structure (CRITICAL)
The Portal uses **LONG format** with time horizon as a column, NOT the WIDE format from original Scorecard bulk download files. **Portal column names are all lowercase** and differ significantly from original Scorecard names.
| Original Scorecard (WIDE) | Portal Column (LONG) | How to Get | |---------------------------|----------------------|------------| | `MD_EARN_WNE_P6` | `earnings_med` | Filter: `years_after_entry == 6` | | `MD_EARN_WNE_P10` | `earnings_med` | Filter: `years_after_entry == 10` | | `COUNT_WNE_P6` | `count_working` | Filter: `years_after_entry == 6` | | `MN_EARN_WNE_P6` | `earnings_mean` | Filter: `years_after_entry == 6` | | `CONTROL`, `INSTNM` | NOT
Read more
name: education-data-source-scorecard description: >- College Scorecard — post-enrollment outcomes linking aid records to IRS/Treasury earnings. Earnings, loan repayment, debt via six Portal sub-datasets. Use when tax-record-based earnings needed. Tracks only Title IV aid recipients, not all students. metadata: audience: any-agent domain: data-source skill-authored: "2026-02-09" skill-last-updated: "2026-02-09"
Scorecard Data Source Reference
College Scorecard — the primary institutional-level source for post-enrollment labor market outcomes, linking NSLDS financial aid records to IRS/Treasury earnings data. Use when comparing institutions on post-graduation earnings, loan repayment, or student debt, or when actual tax-record-based earnings are required rather than survey estimates. Covers six sub-datasets accessed via Portal mirrors. Critical limitation: tracks only Title IV federal aid recipients, not all students.
Federal data on post-college outcomes including earnings, debt, and repayment for students who received Title IV financial aid. Links education records to IRS tax data for actual earnings, making it the primary source for post-college labor market outcomes.
> **CRITICAL: Value Encoding and Missing Data** > > The Education Data Portal uses **integer encodings** for all categorical variables > and **lowercase, restructured variable names** that differ from the original > Scorecard column names. Suppression encoding differs by dataset: > > - **Earnings/counts**: `-3` integer code is the primary suppression indicator > - **Yes/No flags** (institutional characteristics): `null` for missing, `0`/`1` for valid > - **Rates** (repayment, default): `null` for missing > - The original Scorecard string `"PrivacySuppressed"` does NOT appear in Portal data > > | Context | `pred_degree_awarded_ipeds` | HBCU / tribal flags | `religious_affiliation` | > |---------|----------------------------|---------------------|-------------------------| > | **Portal (integer)** | `0`-`4` | `0` / `1` | Integer codes 22-200 | > | Original Scorecard | String labels | String labels | String labels | > > See `./references/variable-definitions.md` for complete encoding tables.
What is College Scorecard?
- **Publisher**: U.S. Department of Education
- **Primary value**: Post-college labor market outcomes (earnings) and debt/repayment metrics
- **Data sources**: NSLDS (loans/aid), IRS/Treasury (earnings), IPEDS (institutional characteristics)
- **Coverage**: **Title IV federal aid recipients only** — not all students
- **Unique feature**: Links education to IRS tax records for actual earnings data
- **Access**: Education Data Portal mirrors (parquet/CSV); see `datasets-reference.md` for paths, `mirrors.yaml` for mirror config, `fetch-patterns.md` for fetch code
- **Primary identifier**: `unitid` (IPEDS institution ID)
Reference File Structure
| File | Purpose | When to Read | |------|---------|--------------| | `earnings-data.md` | Post-college earnings methodology, cohorts, time horizons | Analyzing earnings outcomes | | `debt-repayment.md` | Student debt, repayment rates, default rates | Analyzing debt or loan outcomes | | `completion-rates.md` | Completion metrics vs IPEDS | Comparing graduation rates | | `population-coverage.md` | Title IV limitation details, who is included/excluded | Understanding data representativeness | | `variable-definitions.md` | Key variables, naming conventions, special values | Building queries or interpreting results | | `data-quality.md` | Suppression rules, selection bias, known limitations | Assessing data reliability | | `field-of-study.md` | Program-level earnings and debt data | Analyzing outcomes by major/CIP code |
Decision Trees
What outcome am I researching?
Outcome type?
├─ Post-college earnings
│ ├─ Institution-level → ./references/earnings-data.md
│ └─ By field of study → ./references/field-of-study.md
├─ Student debt levels
│ ├─ Cumulative borrowing → ./references/debt-repayment.md
│ └─ Debt by field → ./references/field-of-study.md
├─ Loan repayment/default
│ └─ Repayment rates → ./references/debt-repayment.md
├─ Completion rates
│ └─ Scorecard completion → ./references/completion-rates.md
└─ Understanding limitations
├─ Who is included → ./references/population-coverage.md
└─ Data quality issues → ./references/data-quality.mdHow do I interpret this data?
Interpretation question?
├─ Why are earnings suppressed?
│ └─ Privacy thresholds → ./references/data-quality.md
├─ What does "6-year earnings" mean?
│ └─ Cohort timing → ./references/earnings-data.md
├─ Why don't Scorecard rates match IPEDS?
│ └─ Different cohorts → ./references/completion-rates.md
├─ What loans are included in debt?
│ └─ Federal only → ./references/debt-repayment.md
└─ How representative is this data?
└─ Title IV coverage → ./references/population-coverage.mdBuilding a query?
Query construction? ├─ Variable names and codes → ./references/variable-definitions.md ├─ Suppression flags to handle → ./references/data-quality.md ├─ Understanding cohort years → ./references/earnings-data.md └─ Field-level queries → ./references/field-of-study.md
Quick Reference: Scorecard Variables
Portal Data Structure (CRITICAL)
The Portal uses **LONG format** with time horizon as a column, NOT the WIDE format from original Scorecard bulk download files. **Portal column names are all lowercase** and differ significantly from original Scorecard names.
| Original Scorecard (WIDE) | Portal Column (LONG) | How to Get | |---------------------------|----------------------|------------| | `MD_EARN_WNE_P6` | `earnings_med` | Filter: `years_after_entry == 6` | | `MD_EARN_WNE_P10` | `earnings_med` | Filter: `years_after_entry == 10` | | `COUNT_WNE_P6` | `count_working` | Filter: `years_after_entry == 6` | | `MN_EARN_WNE_P6` | `earnings_mean` | Filter: `years_after_entry == 6` | | `CONTROL`, `INSTNM` | NOT
📌 文档结构(2026-07-22 起): 本文件是中文默认入口 —— banner + badges + 信任面 + 9 阶段流水线速览 + 76 行合集总表。 每个合集的完整描述、按用途分组、精确数字、验证方法在 docs/CONTENT_ZH.md(扩展正文,总表行内的 → 直接跳转到对应锚点)。 English version: README-en.md · 中文扩展正文:docs/CONTENT_ZH.md · README-zh-CN.md 已弃用(重定向占位) 🌐 语言: English |
Other skills on auto-empirical-research-skills.
- /pipeline
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) —
Open skill - /pipeline
Classical end-to-end empirical analysis workflow in the modern tidyverse + econometrics R ecosystem — dplyr + tidyr + haven + fixest + sandwich + lmtest + clubSandwich + AER + ivreg + did + bacondecomp + HonestDiD + eventstudyr + rdrobust + rddensity + Synth + gsynth + synthdid
Open skill - /pipeline
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc +
Open skill - /00-Full-empirical-analysis-skill_StatsPAI
Use when the user asks to run a full empirical / causal analysis in Python — by default in the style of an applied economics paper (AER / QJE / JPE / ReStud / AEJ) with DID / RD / IV / SCM / DML / matching, written-out estimating equation + identifying assumption, Table 1 /
Open skill - /00.1-Full-empirical-analysis-skill_Python
Classical end-to-end empirical analysis workflow in the traditional Python econometric stack — pandas + numpy + scipy + statsmodels + linearmodels + pyfixest + rdrobust + econml + causalml + matplotlib/seaborn. **Defaults to economics empirical-paper style** (AER / QJE / AEJ) —
Open skill - /00.2-Full-empirical-analysis-skill_Stata
Classical end-to-end empirical analysis workflow in the traditional Stata ecosystem — native Stata + reghdfe + ivreg2 + csdid + did_imputation + eventstudyinteract + sdid + rdrobust + rddensity + synth + synth_runner + psmatch2 + teffects + ebalance + coefplot + esttab + asdoc +
Open skill

