Data Documentation Assistant
SkillDatabases & datadata-doc is a skill that has your AI write clear documentation for the datasets it works with in empirical research. Once added, your AI records each dataset's variables, sources, and merge keys in structured templates, so the work can be replicated by others later.
Available today. Use it from your connected AI after setup.
No other account needed.
Add the skill, then ask your AI to document a dataset you are working with. It will follow the structured template to capture the variables, sources, and merge keys.
Then ask your AI: use the Data Documentation Assistant skill
What your AI can do with it
- Document datasets and their variables in structured templates
- Record where each dataset came from
- List the merge keys that connect datasets to each other
- Produce documentation that supports replication of the analysis
What this skill tells your AI
The instructions your AI receives, as published by brycewang-stanford/auto-empirical-research-skills in skills/30-zirui-song-claude-skills/data-doc/SKILL.md and read by ahel’s review.
Help document datasets systematically for replication packages, co-author handoffs, and future reference.
Dataset Documentation Template
When documenting a dataset, capture:
1. Dataset Overview
- Name: (e.g.,
firm_year_panel.parquet) - Location: (relative path from project root)
- Created by: (script that generates it)
- Last updated:
- Unit of observation: (firm-year, loan-quarter, etc.)
- N observations:
- Time coverage:
2. Source Data
| Source | Access | Raw File | Notes |
|---|---|---|---|
| WRDS Compustat | Subscription | raw/compustat_funda.csv | Annual fundamentals |
| Revelio Labs | Licensed | raw/revelio_positions.parquet | Via BU server |
| Hand-collected | Manual | raw/manual_coding.xlsx | See coding protocol |
3. Key Variables
| Variable | Type | Description | Source | Notes |
|---|---|---|---|---|
gvkey | str | Compustat firm identifier | Compustat | Primary key |
fyear | int | Fiscal year | Compustat | |
at | float | Total assets ($ millions) | Compustat | Winsorized 1/99 |
treated | int | =1 if treated firm | Constructed | See section 4 |
4. Variable Construction
For constructed/derived variables, document:
Variable: treated
Definition: =1 if firm received first PE investment in year t
Construction:
1. Merge PitchBook deals to Compustat on EIN
2. Keep first deal per firm
3. Flag year of first investment
Script: 2a_construct_treatment.py, lines 45-78
5. Sample Filters
Document all filters applied:
| Filter | Observations Dropped | Remaining |
|---|---|---|
| Raw data | - | 150,000 |
| Drop financials (SIC 6000-6999) | 25,000 | 125,000 |
| Require non-missing assets | 5,000 | 120,000 |
| Require 2+ years in panel | 10,000 | 110,000 |
6. Merge Keys
| Dataset A | Dataset B | Key(s) | Match Rate | Notes |
|---|---|---|---|---|
| Compustat | CRSP | gvkey | 95% | Via CCM link table |
| Compustat | PitchBook | EIN | 72% | Manual cleaning needed |
| Revelio | Compustat | company_name | 68% | Fuzzy match, see script |
Quick Commands
- "document this dataset" - Generate full template for a dataset
- "variable list" - Create variable table only
- "merge documentation" - Focus on merge keys and match rates
- "sample flow" - Generate sample filter table
- "codebook" - Formal codebook format for replication package
Codebook Format (for Replication Packages)
================================================================================
CODEBOOK: firm_year_panel.dta
Generated: 2026-01-15
================================================================================
IDENTIFICATION
gvkey Compustat permanent firm identifier
fyear Fiscal year
OUTCOME VARIABLES
roa Return on assets = ni/at (winsorized 1/99)
investment Capex/lagged assets = capx/L.at
TREATMENT VARIABLES
post =1 for years after treatment
treated =1 for firms ever treated
treat_post Interaction: treated × post (DiD coefficient)
CONTROLS
size Log total assets = ln(at)
leverage Book leverage = (dltt+dlc)/at
mtb Market-to-book = (prcc_f×csho)/ceq
FIXED EFFECTS
ff48 Fama-French 48 industry classification
state State of incorporation
================================================================================
Data Provenance Checklist
Before finalizing a dataset, verify:
- All source files documented with access instructions
- Variable definitions are unambiguous
- Sample filters documented with observation counts
- Merge match rates reported
- Winsorization/trimming documented
- Missing value treatment documented
- Script that creates dataset is identified
- Date of creation recorded
Signals
- GitHub stars
- 4k
- Forks
- 476
- Last commit
- Sep 2026
Advanced
- Catalog kind
- skill
- Gateway key
data-doc- Source
- github.com/brycewang-stanford/auto-empirical-research-skills