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# AI skills
```skill.ai.symphony``` defines a processing graph that is comprised of ```edges``` and ```nodes```.
## Schema
| Field | Type | Description |
|--------|--------|--------|
| ```Bindings```| ```[]BindingSpec``` | A list of [bindings](binding.md) that represent actions allowed on the AI skill. |
| ```DisplayName``` | ```string``` | A user friendly name. |
| ```Edges``` | ```[]EdgeSpec``` | Graph edges. |
| ```Nodes``` | ```[]NodeSpec``` | Graph nodes. |
| ```Parameters``` | ```map[string]string``` | Parameters. A parameter can be used anywhere in the skill definition. For more information, see the [parameters](#parameters) sections below. |
| ```Properties``` | ```map[string]string``` | A property bag, |
## Parameters
You can define any number of parameters in the ```parameters``` section. All parameters are ```string``` typed. And you specify a default for the parameter when declaring it.
```yaml
parameters:
delay_buffer: "0.1"
model_platform: "invalid"
model_flavor: "edge"
```
Then, you can refer to the parameter in your AI skill graph definition, for example:
```yaml
nodes:
- id: "4"
type: export
name: video_snippet_export
configurations:
filename_prefix: test
recording_duration: "$param(model_flavor)"
insights_overlay: "$param(model_platform)"
delay_buffer: "$param(delay_buffer)"
```
## Overwrite parameters
A ```instance.solution.symphony``` object can overwrite AI skill parameter values in its own ```parameters``` section.
```yaml
parameters:
cv-skill.delay_buffer: "0.2"
cv-skill.model_platform: "TensorFlow"
cv-skill.model_flavor: "TensorFlowMobile"
```
>**Note:** when a solution instance uses multiple references to a same AI skill, it can use alias to distinguish different AI skill instances.
