learn-stata-command

---

name: learn-stata-command description: Learn and document a Stata command for Python econometric implementation reference. Use when user says "learn stata command XXX" or wants to understand a Stata command's internals for replicating in Python. Workflow: fetch help via Stata-MCP, write demo do-file, run it, and produce a command breakdown doc. context: fork agent: stata-dev disable-model-invocation: true allowed-tools: Read Write Edit Grep Glob WebSearch WebFetch Bash(stata-mcp tool*)

Learn Stata Command

Systematic workflow to study a Stata command and produce reference docs for Python implementation.

Prerequisites

• Stata-MCP tool must be available. If absent, stop and ask the user.
• Project directories: stata-mcp-folder/stata-mcp-tmp/ (help cache), stata-mcp-folder/stata-mcp-dofile/ (do-files), stata-mcp-folder/stata-mcp-log/ (logs), docs/stata/command/ (breakdown docs).

Workflow

Given a command name (e.g., xtreg, reghdfe, summarize), execute these steps in order.

Step 1: Fetch Help

Fetch help via Stata-MCP:

stata-mcp tool help <command>

This writes help__<command>.txt to stata-mcp-folder/stata-mcp-tmp/. Read it to understand:

• Syntax and sub-commands (e.g., xtreg ... , fe / be / re / mle / pa)
• Options and their meanings
• Key formulas / methods described

Step 2: Fetch Ado Source Code

Many Stata commands (especially user-contributed ones like reghdfe) have viewable .ado source files. Use the script to fetch:

uv run scripts/fetch_ado.py <command>

The script uses findfile + cp to copy the ado file to .verify/ado_plus/<command>.ado.

If the script errors (command may be built-in), it means the command is compiled C code — skip this step. If successful, Read .verify/ado_plus/<command>.ado to understand:

• Internal algorithm flow (e.g., MAP iteration, FE absorption details)
• Option processing logic
• Intermediate variable computation

This information is critical for Python replication — help docs are rarely detailed enough.

Step 3: Write Demo Do-File(s)

Based on the help output, write one or more do-files to stata-mcp-folder/stata-mcp-dofile/. Each do-file tests one sub-command or major option variant.

Do-file conventions:

• Use sysuse auto, clear as the dataset unless the command requires panel data (then use a panel setup like webuse nlswork, clear + xtset).
• Filename pattern: <command>_<variant>_demo.do (e.g., xtreg_fe_demo.do, xtreg_re_demo.do).
• Keep each do-file minimal: load data, set up if needed, run the command.

Step 4: Run Do-Files

Execute each do-file via Stata-MCP:

stata-mcp tool do stata-mcp-folder/stata-mcp-dofile/<filename>.do

Read the log output to verify the command ran correctly and note the output format.

Step 5: Write Command Breakdown Doc

Create docs/stata/command/<command>.md with the following sections:

# <command> -- <brief description>

## Syntax
<!-- from help output -->

## Sub-commands / Variants
<!-- list each variant with its purpose -->

## Key Options
<!-- most important options -->

## Algorithm / Estimation Method
<!-- the math under the hood, from help or Stata manual -->

## Output Elements (Complete Output Checklist)

<!-- List every single numeric item in Stata's output, one per line, no omissions -->
<!-- Reference the actual log output from Step 4 to fill this in -->

### Header section
- Number of obs
- Group variable / Panel variable
- Number of groups
- ... (anything Stata prints in the header)

### Regression table
- Every coef, SE, t/z, p-value, CI (including `_cons`)

### Goodness of fit
- R² (within/between/overall), Adj R², root MSE

### Variance decomposition (panel models)
- sigma_u, sigma_e, rho
- corr(u_i, Xb) (if present)

### Test statistics
- F/chi2, Prob > F/chi2
- F test u_i=0 (FE), Hausman (RE vs FE), Breusch-Pagan LM (RE)
- Any other tests Stata prints

### Other
- log-likelihood (if present)
- Any numeric value in Stata's output

## Implementation Notes
<!-- hints for Python replication -->

Critical: The Output Elements section must be extracted from actual log output in Step 4 — not from memory. Whatever Stata prints, list it. Missing any item will cause missed detections during verification.

Example

See references/example_reghdfe.md for a complete breakdown of reghdfe. Use it as the template for future command breakdown docs.

Important Notes

• Do NOT ask the user for Stata code — use Stata-MCP exclusively.
• If a command has many variants (like xtreg), cover each significant variant with its own do-file.
• The breakdown doc should be concise. Target implementation-relevant details, not a copy of the help file.

Anti-Patterns (forbidden)

• No python3 -c "xxx": Write script files then run with uv run.
• No requests.get() for data download: Stata datasets use uv run scripts/download_data.py <dataset> to download to .local/data/. Read with pd.read_stata(".local/data/<dataset>.dta").
• No guessing Stata data paths: Cannot directly access sysuse / webuse file paths — must use the download script.

Stata-MCP Available Tools

stata-mcp is a CLI tool, not an MCP server. Verify with: stata-mcp --version or uvx stata-mcp --version.

stata-mcp tool help <command>    # View command help, cached to stata-mcp-folder/stata-mcp-tmp/
stata-mcp tool do <file.do>      # Execute do-file, logs saved to stata-mcp-folder/stata-mcp-log/
stata-mcp tool data-info <path>  # View dataset metadata (variable names, types, etc.)
stata-mcp tool read-log <path>   # Read Stata log
stata-mcp tool ado-install <pkg> # Install ado package