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cody
2026-06-03 22:05:27 -08:00
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AGENTS.md
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@@ -10,6 +10,9 @@ The main teaching example is an ICU septic shock study:
- Teach by showing small code chunks that the user can type in manually. - Teach by showing small code chunks that the user can type in manually.
- Explain each meaningful line of code before moving on. - Explain each meaningful line of code before moving on.
- Add generous learner-focused comments, especially around R functions, function arguments, return values, and unfamiliar package functions.
- Include many small examples and REPL-style checkpoints with code, expected output, and interpretation.
- Keep report-style Quarto notebooks focused on rendered tables and interpretation unless the user asks for REPL-style checkpoints there.
- Teach the base R mechanics when a concept is new, then prefer readable tidyverse-style code for routine analysis. - Teach the base R mechanics when a concept is new, then prefer readable tidyverse-style code for routine analysis.
- Make the smallest correct change when editing project files. - Make the smallest correct change when editing project files.
- Keep scripts and notebooks numbered so the learning sequence is obvious. - Keep scripts and notebooks numbered so the learning sequence is obvious.
@@ -21,8 +24,11 @@ The main teaching example is an ICU septic shock study:
- Use the native pipe `|>`, not `%>%` - Use the native pipe `|>`, not `%>%`
- snake_case for all names - snake_case for all names
- Prefer explicit, teaching-oriented comments over terse production-style code while this remains a learning project.
- For reusable functions, include comments describing purpose, arguments, return value, and at least one example call.
- Prefer `vapply` over `sapply`; explicit return types - Prefer `vapply` over `sapply`; explicit return types
- Use `cli::cli_*` for messages, not `message()`/`cat()` - Use `cli::cli_*` for messages, not `message()`/`cat()`
- Prefer cleaner imports with grouped startup message suppression, for example `suppressPackageStartupMessages({ library(readr); library(dplyr) })`.
- Prefer `dplyr` verbs for data manipulation when external dependencies are allowed. - Prefer `dplyr` verbs for data manipulation when external dependencies are allowed.
- Prefer `skimr` for quick data summaries. - Prefer `skimr` for quick data summaries.
- Prefer `gt` and `gtsummary` for clear analytic tables in notebooks and reports. - Prefer `gt` and `gtsummary` for clear analytic tables in notebooks and reports.
@@ -40,6 +46,7 @@ The main teaching example is an ICU septic shock study:
- renv for dependency management; lockfile is source of truth - renv for dependency management; lockfile is source of truth
- targets for pipeline orchestration - targets for pipeline orchestration
- tidyverse, especially `dplyr`, for routine data manipulation - tidyverse, especially `dplyr`, for routine data manipulation
- ggplot2 for exploratory plots and visual diagnostics
- data.table for performance-oriented data manipulation when needed - data.table for performance-oriented data manipulation when needed
- skimr for quick data summaries - skimr for quick data summaries
- gt for presentation tables - gt for presentation tables
@@ -53,6 +60,15 @@ The main teaching example is an ICU septic shock study:
- Keep base R explanations available when they help the user understand what the package code is doing. - Keep base R explanations available when they help the user understand what the package code is doing.
- Do not add packages outside the approved stack without asking first. - Do not add packages outside the approved stack without asking first.
## Workflow Roles
- Put reusable logic in `R/` functions.
- Put reusable smoke checks or command-line workflows in `scripts/`.
- Put polished displays, interpretation, exploratory visualization, and rendered result tables in Quarto notebooks.
- Avoid CSV intermediates when functions can be called directly and reproducibly.
- Use `run_all.sh` as the lightweight end-to-end runner until the project is ready for `targets`.
- Keep rendered notebook reports in `outputs/reports/`.
## Learning Roadmap ## Learning Roadmap
- [x] Choose ICU teaching scenario: early vasopressor strategy in septic shock. - [x] Choose ICU teaching scenario: early vasopressor strategy in septic shock.
@@ -104,14 +120,16 @@ Baseline confounders in the first simulated dataset:
- Lactate. - Lactate.
- Mean arterial pressure. - Mean arterial pressure.
Initial causal contrast: Initial estimand:
- Risk difference in 28-day mortality. - Risk difference in 28-day mortality.
- Risk ratio for 28-day mortality. - Risk ratio for 28-day mortality.
## File Sequence ## File Sequence
- `scripts/01_simulate_icu_data_base_r.R`: generate synthetic ICU cohort data from the reusable simulation primitive. - `run_all.sh`: run the key scripts and render all current notebooks.
- `scripts/02_naive_analysis_base_r.R`: compute an initial naive comparison with readable tidyverse-style code. - `scripts/01_simulate_icu_data.R`: simulate an ICU cohort in memory and print a quick `skimr` summary.
- `R/simulate_icu_cohort.R`: first reusable simulation primitive. - `R/simulate_icu_cohort.R`: first reusable simulation primitive.
- `notebooks/01_target_trial_basics.qmd`: conceptual walkthrough of the target trial protocol with `skimr`, `gt`, and `gtsummary` examples. - `R/estimate_naive_vasopressor_mortality_effect.R`: shared naive mortality-effect primitive used by notebook workflows.
- `notebooks/01_target_trial_basics.qmd`: report-style walkthrough of the target trial protocol and initial results.
- `notebooks/02_explore_simulated_data.qmd`: exploratory visual diagnostics for the simulated cohort.