Build representer

In Exercism v3, we're introducing a new (optional) tool: the [representer](https://github.com/exercism/docs/blob/main/building/tooling/representers/README.md). The goal of the representer is to take a solution and returning a representation, which is an extraction of a solution to its essence with normalized names, comments, spacing, etc. but still uniquely identifying the approach taken. Two different ways of solving the same exercise must not have the same representation.

Each representer is track-specific. When a new solution is submitted, we run the track's representer, which outputs two JSON files that describe the representation.

Once we have a normalized representation for a solution, a team of vetted mentors will look at the solution and comment on it (if needed). These comments will then automatically be submitted to each new solution with the same representation. A notification will be sent for old solutions with a matching representation.

The representer is an optional tool though, which means that if a track does not have a representer, it will still function normally.

## Goal

Build a representer for your track according to [the spec](https://github.com/exercism/docs/blob/main/building/tooling/representers/interface.md). Check [this page](https://github.com/exercism/docs/blob/main/building/tooling/representers/creating-from-scratch.md) to help you get started with building a representer.

Note that the simplest representer is one that merely returns the solution's source code.

It can be very useful to check how [other tracks have implemented their representer](https://github.com/search?q=org%3Aexercism+representer&type=repositories).

_If your track already has a working representer, please close this issue and ensure that the `.status.representer` key in the track `config.json` file is set to `true`._

## Choosing between representer and analyzer

There is some overlap between the goals of the representer and the analyzer. If you want to build both, we recommend starting by building the representer for the following reasons:

- Representers are usually (far) easier to implement
- Representers can have a far bigger impact on the mentoring load than analyzers by empowering mentors
- Representers apply to _all_ exercises, whereas analyzers usually target specific exercises or a subset

## Tracking

https://github.com/exercism/v3-launch/issues/52