# Context windows

Each `.yaml` file here defines a **context window** — a well-defined scope the AI
reads *before* answering, so it stays on topic instead of drifting. The active
context is prepended to every question (spoken and on-screen) before it goes to
the model.

Example: with `python_flask_backend.yaml` active, asking *"what is STOMP"* gets
the Python/Flask-relevant answer first (the WebSocket sub-protocol you'd use from
a Flask backend), then a short note on other meanings — rather than a generic or
off-topic answer.

## Format

```yaml
name: Python / Flask — Senior Backend Engineer   # display name
scope: Senior backend engineering interview …    # one-line summary (optional)
active: true        # mark exactly one file active
strict: false       # false → answer in-context first, then variations
                    # true  → stay strictly in-scope, no variations
definition: |       # required: the scope + how to interpret questions
  Free-form text describing the context…
```

## Choosing the active context

1. If `config.yaml` sets `ai.active_context: <filename-without-extension>`, that
   file wins (e.g. `ai.active_context: python_flask_backend`).
2. Otherwise, the first file with `active: true` is used.
3. If none match, the assistant answers without a context (default behavior).

Files are reloaded when they change on disk, so editing a context takes effect
without restarting the app. To switch contexts, set `active: true` on one file
(and `false` on the others), or set `ai.active_context` in `config.yaml`.