chore: add dedicated claude skill for RNE (#800)

## Description

This PR adds a _Claude Skill_ for RN Executorch that can help with
building, prototyping and debugging RNE apps.

### Introduces a breaking change?

- [ ] Yes
- [x] No

### Type of change

- [ ] Bug fix (change which fixes an issue)
- [ ] New feature (change which adds functionality)
- [ ] Documentation update (improves or adds clarity to existing
documentation)
- [x] Other (chores, tests, code style improvements etc.)

### Tested on

- [ ] iOS
- [ ] Android

### Testing instructions

The same version of this skill was uploaded to [this
repository](https://github.com/software-mansion-labs/react-native-skills)
so it's possible to use this skill globally now.

To do this run:
```
npx skills add software-mansion-labs/react-native-skills 
```

(after merging this PR it will be possible to add this skill to the
project with `npx skills add software-mansion/react-native-executorch`)
 
### Screenshots

<!-- Add screenshots here, if applicable -->

### Related issues

<!-- Link related issues here using #issue-number -->

### Checklist

- [ ] I have performed a self-review of my code
- [ ] I have commented my code, particularly in hard-to-understand areas
- [ ] I have updated the documentation accordingly
- [ ] My changes generate no new warnings

### Additional notes

<!-- Include any additional information, assumptions, or context that
reviewers might need to understand this PR. -->

---------

Co-authored-by: Mateusz Słuszniak <mateusz.sluszniak@swmansion.com>

Author: mateuszlampert

.cspell-wordlist.txt

@@ -6,6 +6,8 @@ torch
 huggingface
 bbox
 bboxes
+chatbots
+llms
 deeplab
 unsqueeze
 qlora

docs/docs/03-hooks/02-computer-vision/useImageSegmentation.md

@@ -55,13 +55,13 @@ To run the model, you can use the [`forward`](../../06-api-reference/interfaces/
 
 - The image can be a remote URL, a local file URI, or a base64-encoded image.
 - The [`classesOfInterest`](../../06-api-reference/interfaces/ImageSegmentationType.md#classesofinterest) list contains classes for which to output the full results. By default the list is empty, and only the most probable classes are returned (essentially an arg max for each pixel). Look at [`DeeplabLabel`](../../06-api-reference/enumerations/DeeplabLabel.md) enum for possible classes.
-- The [`resizeToInput`](../../06-api-reference/interfaces/ImageSegmentationType.md#resizeToInput) flag specifies whether the output will be rescaled back to the size of the input image. The default is `true`. The model runs inference on a scaled (probably smaller) version of your image (224x224 for `DEEPLAB_V3_RESNET50`). If you choose to resize, the output will be `number[]` of size `width * height` of your original image.
+- The [`resizeToInput`](../../06-api-reference/interfaces/ImageSegmentationType.md#resizetoinput) flag specifies whether the output will be rescaled back to the size of the input image. The default is `true`. The model runs inference on a scaled (probably smaller) version of your image (224x224 for `DEEPLAB_V3_RESNET50`). If you choose to resize, the output will be `number[]` of size `width * height` of your original image.
 
 :::warning
-Setting `resize` to true will make `forward` slower.
+Setting `resizeToInput` to `false` will make `forward` faster.
 :::
 
-[`forward`](../../06-api-reference/interfaces/ImageSegmentationType.md#forward) returns a promise which can resolve either to an error or a dictionary containing number arrays with size depending on [`resize`](../../06-api-reference/interfaces/ImageSegmentationType.md#resize):
+[`forward`](../../06-api-reference/interfaces/ImageSegmentationType.md#forward) returns a promise which can resolve either to an error or a dictionary containing number arrays with size depending on [`resizeToInput`](../../06-api-reference/interfaces/ImageSegmentationType.md#resizetoinput):
 
 - For the key [`DeeplabLabel.ARGMAX`](../../06-api-reference/enumerations/DeeplabLabel.md#argmax) the array contains for each pixel an integer corresponding to the class with the highest probability.
 - For every other key from [`DeeplabLabel`](../../06-api-reference/enumerations/DeeplabLabel.md), if the label was included in [`classesOfInterest`](../../06-api-reference/interfaces/ImageSegmentationType.md#classesofinterest) the dictionary will contain an array of floats corresponding to the probability of this class for every pixel.

docs/docs/04-typescript-api/02-computer-vision/ImageSegmentationModule.md

@@ -52,13 +52,13 @@ To run the model, you can use the [`forward`](../../06-api-reference/classes/Ima
 
 - The image can be a remote URL, a local file URI, or a base64-encoded image.
 - The [`classesOfInterest`](../../06-api-reference/classes/ImageSegmentationModule.md#classesofinterest) list contains classes for which to output the full results. By default the list is empty, and only the most probable classes are returned (essentially an arg max for each pixel). Look at [`DeeplabLabel`](../../06-api-reference/enumerations/DeeplabLabel.md) enum for possible classes.
-- The [`resizeToInput`](../../06-api-reference/classes/ImageSegmentationModule.md#resizeToInput) flag specifies whether the output will be rescaled back to the size of the input image. The default is `true`. The model runs inference on a scaled (probably smaller) version of your image (224x224 for the `DEEPLAB_V3_RESNET50`). If you choose to resize, the output will be `number[]` of size `width * height` of your original image.
+- The [`resizeToInput`](../../06-api-reference/classes/ImageSegmentationModule.md#resizetoinput) flag specifies whether the output will be rescaled back to the size of the input image. The default is `true`. The model runs inference on a scaled (probably smaller) version of your image (224x224 for the `DEEPLAB_V3_RESNET50`). If you choose to resize, the output will be `number[]` of size `width * height` of your original image.
 
 :::warning
 Setting `resize` to true will make `forward` slower.
 :::
 
-[`forward`](../../06-api-reference/classes/ImageSegmentationModule.md#forward) returns a promise which can resolve either to an error or a dictionary containing number arrays with size depending on [`resize`](../../06-api-reference/classes/ImageSegmentationModule.md#resize):
+[`forward`](../../06-api-reference/classes/ImageSegmentationModule.md#forward) returns a promise which can resolve either to an error or a dictionary containing number arrays with size depending on [`resizeToInput`](../../06-api-reference/classes/ImageSegmentationModule.md#resizetoinput):
 
 - For the key [`DeeplabLabel.ARGMAX`](../../06-api-reference/enumerations/DeeplabLabel.md#argmax) the array contains for each pixel an integer corresponding to the class with the highest probability.
 - For every other key from [`DeeplabLabel`](../../06-api-reference/enumerations/DeeplabLabel.md), if the label was included in [`classesOfInterest`](../../06-api-reference/classes/ImageSegmentationModule.md#classesofinterest) the dictionary will contain an array of floats corresponding to the probability of this class for every pixel.

docs/docs/06-api-reference/functions/useImageSegmentation.md

@@ -2,7 +2,7 @@
 
 > **useImageSegmentation**(`ImageSegmentationProps`): [`ImageSegmentationType`](../interfaces/ImageSegmentationType.md)
 
-Defined in: [packages/react-native-executorch/src/hooks/computer_vision/useImageSegmentation.ts:15](https://github.com/software-mansion/react-native-executorch/blob/9e79b9bf2a34159a71071fbfdaed3ddd9393702f/packages/react-native-executorch/src/hooks/computer_vision/useImageSegmentation.ts#L15)
+Defined in: [packages/react-native-executorch/src/hooks/computer_vision/useImageSegmentation.ts:15](https://github.com/software-mansion/react-native-executorch/blob/6b532e47fba9c94d5beee0e422f95326d37e8c80/packages/react-native-executorch/src/hooks/computer_vision/useImageSegmentation.ts#L15)
 
 React hook for managing an Image Segmentation model instance.