# Teacher-context variants

Each **variant** is one way to build the teacher's refined trajectory `r` — a
self-contained folder that overrides only what differs from the live default. The
shared machinery (HTTP transport, MC rollouts, divergence metrics, the batched
training loop) lives in the core and is **never copied**, so adding a variant never
adds an `if variant == ...` branch.

## Layout

```
agents/variants/
  base.py            TeacherVariant — the interface + shared defaults + t* helpers
  __init__.py        registry: load(name) / available()
  <variant>/
    utils.py         a TeacherVariant subclass (+ VARIANT = TheSubclass)
    prompts.yaml     strategy + maker_system_prompt (+ optional teacher_user wrapper)
    README.md        what it is, the bet, the pre-registered prediction
```

## The interface (what a variant may override)

| method | default | overridden by |
|---|---|---|
| `resolve_prefix(problem, solution, rollout, maker)` | maker rewrite, fall back to reference | P4 (answer-only, maker-free), P6 (captures diagnosis quote) |
| `accepts(prefix, reference)` | `is_acceptable_prefix` (len ≥ 80 ∧ boxed-match) | P2 / P4 (answer-only bypass: boxed-match only) |
| `build_ctx(tok, client, problem, prefix, cfg)` | user turn + `<think>` analysis + close + transition | P5 (reactive wrapper), P4 (no thinking) |
| `t_star(prefix, rollout, tok)` | `difflib` first non-matching block | P3 (`lcp`), P6 (quote-match) |
| `thinking` | `True` | P4 (`False`) |

Everything else — `score_topk`, `mc_branch`, `select_divergent`, M1–M3, the
trainer loss — is shared and calls these methods.

## Two seams this relies on (both in `agents/maker.py::build_prefix`, backward-compatible)

- `prompts=` — a variant supplies its own `{strategy, maker_system_prompt,
  maker_user_template}` instead of a file swap.
- `accept=` — a variant supplies its own gate (e.g. answer-only bypass).

## Usage

```python
from agents.variants import load, available
v = load("p1_surgical")                 # available() -> ['p1_surgical', 'p2_...', ...]
prefix = v.resolve_prefix(problem, solution, rollout, maker_client)
ctx    = v.build_ctx(tok, client, problem, prefix, cfg)
tstar  = v.t_star(prefix, rollout, tok)
```

## Scope

Variants are the prompt-space ranking substrate (probe / Stage-1). The loss-side
mask and per-sample gate (the reactive-constructor spec) are deferred; when they
land, `build_ctx`'s declarations feed the trainer but generation stays shared.

## Adding one

Copy the closest folder, edit `prompts.yaml` + the few overridden methods in
`utils.py`, write the `README.md`. No core edits.