Instructions for the AI agent in this project

The agent reads this file at the start of every session. Edit it freely. When the agent makes the same mistake twice, add a line here.

About me

I am a social scientist (EDIT: field, e.g. sociology, political science, economics).
I have used AI as a chatbot, mostly for text. I have not written code before.
Explain what you do in plain language. The first time you use a technical term, give a one-line definition.
Use Python for code, unless I ask for R or Stata.

For any task with more than a few steps, first show me a short plan and wait for my OK.
Do the smallest thing that answers my request. Ask before adding extras.
Work in small steps. Stop at natural break points and tell me what you did and what is left.
If my request is unclear, ask one question rather than guessing.
When you finish, say what you did not do or could not check.

Never delete files. If something should go, move it to _old/ and tell me.
Never change anything in data/raw/. Raw data stays as it arrived.
Never overwrite a Word, Excel or PDF file I gave you. Save your changes as a new file with _v2 (or the next number) at the end of the name.
Install Python packages only inside this project’s environment (.venv). Ask before installing anything for the whole computer.
Do not upload my files or data to any website or online service.

Never make up numbers, references, quotes or sources. If you cannot verify something, say so.
When you report a number, say where it comes from (which file, which script, which web page).
Check your own results: count rows before and after each step, and compare a few values by hand with the source.
Log analytical choices in DECISIONS.md (see the decision-log skill).

data/raw/ original data, never edited
data/clean/ cleaned data, produced by code
code/ scripts, numbered in the order they run: 01_get_data.py, 02_clean.py, …
output/ figures (PNG) and tables
docs/ notes, memos and drafts. Write new text in Markdown (.md); convert to Word only when I ask.
Every result must be reproducible: running the scripts in order rebuilds all outputs.

Plain, direct prose. Short sentences. No hype words (delve, crucial, landscape, comprehensive, shed light on).
Say what the data shows, then the caveats. Talk about associations, not effects, unless the design allows a causal reading.

To read a PDF, first extract its text to a .txt file, then work from the text (see the read-pdf skill).