Improve modularity/extensibility, adopt plugin good practices, polish

README.md

@@ -1,8 +1,8 @@
 Code Practice (Neovim)
 ======================
 
-A local, Neovim-native practice plugin for browsing exercises, solving them in
-buffer, and running tests from the editor.
+A Neovim plugin for browsing coding exercises, solving them, and running tests
+— all without leaving the editor.
 
 Features
 --------
@@ -30,7 +30,8 @@ Using [lazy.nvim](https://github.com/folke/lazy.nvim):
 }
 ```
 
-Then populate the exercise database. The simplest way is to import a JSON file:
+Then populate the exercise database. The simplest way is to import a JSON file
+(see [`test/example_exercises.json`](test/example_exercises.json) for the expected schema):
 
 ```vim
 :CPImport /path/to/exercises.json
@@ -103,9 +104,7 @@ Browser Keymaps
 | `m`       | Toggle filter: medium difficulty|
 | `h`       | Toggle filter: hard difficulty  |
 | `a`       | Clear all filters               |
-| `p`       | Toggle filter: Python           |
-| `r`       | Toggle filter: Rust             |
-| `t`       | Toggle filter: Theory           |
+| per-engine key | Toggle filter by engine (defaults: `p` Python, `r` Rust, `t` Theory) |
 | `gg`      | Go to top of list               |
 | `G`       | Go to bottom of list            |
 | `q`       | Close browser                   |
@@ -139,14 +138,14 @@ Tools
 ### Exercise Generator
 
 Generate exercises from a syllabus using Hugging Face models. The generator is
-fully language-agnostic: the LLM produces a self-contained test harness alongside
-each exercise, so adding a new language is just a run command — no Python glue code needed.
+engine-agnostic: the LLM produces a self-contained test harness alongside
+each exercise, so adding a new engine is just a run command — no Python glue code needed.
 
 Requires [uv](https://docs.astral.sh/uv/) and a HF token (set via `HF_TOKEN` env var, or `huggingface-cli login`).
 
 Configuration lives in two TOML files under `tools/`:
-- **`languages.toml`** — defines supported languages (run commands, prompt rules,
-  required fields). Add a new language here; no Python changes needed.
+- **`engines.toml`** — defines supported engines (run commands, prompt rules,
+  required fields). Add a new engine here; no Python changes needed.
 - **`syllabus.toml`** — defines what to generate (topics, counts, difficulties).
 
 ```bash
@@ -159,11 +158,11 @@ uv run tools/generate_exercises.py tools/syllabus.toml --model Qwen/Qwen3-Coder-
 # Dry run (print JSON, don't insert)
 uv run tools/generate_exercises.py tools/syllabus.toml --dry-run
 
-# Use a custom languages config
-uv run tools/generate_exercises.py tools/syllabus.toml --languages my_languages.toml
+# Use a custom engines config
+uv run tools/generate_exercises.py tools/syllabus.toml --engines my_engines.toml
 ```
 
-Or from Neovim: `:CPGenerate` (prompts for topic, count, difficulty, and language).
+Or from Neovim: `:CPGenerate` (prompts for topic, count, difficulty, and engine).
 
 Data
 ----
@@ -179,7 +178,7 @@ Roadmap
 - [ ] Context-aware LLM hint based on current buffer code
 - [ ] Live timer with opt-out config
 - [ ] Git theory questions
-- [ ] Haskell runner
+- [ ] Haskell engine
 
 Development
 -----------

dev/init.lua

@@ -33,20 +33,16 @@ require("code-practice").setup({
     height = 0.8,
     border = "rounded",
   },
-  languages = {
+  engines = {
     python = {
       enabled = true,
       cmd = "python3",
-      ext = "py",
     },
     rust = {
       enabled = false,
-      cmd = "rustc",
-      ext = "rs",
     },
     theory = {
       enabled = true,
-      ext = "md",
     },
   },
   keymaps = {