> ## Documentation Index
> Fetch the complete documentation index at: https://docs.plura.ai/llms.txt
> Use this file to discover all available pages before exploring further.

# Taxonomy Manager

> Create and manage shot taxonomies for the Media Processing Node

# Taxonomy Manager

Define required photo checklists for media workflows

## What Is a Taxonomy?

A **taxonomy** is a predefined checklist of required shots for a specific use case. It tells the Media Processing Node's Coverage Scoring section what photos to expect and how to recognize them.

Each taxonomy includes:

* **Required Shots**: Must be captured before proceeding
* **Conditional Shots**: Required only when a specific condition is met
* **AI Descriptions**: How Claude identifies each shot type
* **Extraction Links**: Which shots should trigger OCR data extraction

<Info>
  Taxonomies are managed separately from workflows, allowing you to reuse the same shot requirements across multiple workflows and clients.
</Info>

***

## Accessing the Taxonomy Manager

Navigate to **Settings → Taxonomy Manager** to view, create, and edit taxonomies.

The **List View** displays all available taxonomies with:

* Taxonomy name and icon
* Industry category
* Shot count (required vs. conditional)
* Type badge (Plura Template or Custom)

Use the filters to narrow by industry or type, or search by name.

***

## Creating a Taxonomy

<Steps>
  <Step title="Click Create Taxonomy">
    Or clone an existing template to start with a base configuration.
  </Step>

  <Step title="Set Basic Info">
    * **Name**: Descriptive name (e.g., "Auto Damage - Standard")
    * **Industry**: Category for filtering (Auto, Homeowners, Healthcare, Logistics)
    * **Icon**: Visual identifier for the list view
    * **Description**: Optional context for your team
  </Step>

  <Step title="Add Shot Requirements">
    Define each photo you need. See Shot Configuration below.
  </Step>

  <Step title="Configure Conditions">
    For conditional shots, specify when they're required.
  </Step>

  <Step title="Link Extraction Fields">
    Connect shots to extraction fields for OCR (e.g., VIN plate → VIN extraction).
  </Step>

  <Step title="Save">
    Your taxonomy is now available in the Media Processing Node dropdown.
  </Step>
</Steps>

***

## Shot Configuration

Each shot in a taxonomy has the following fields:

| Field              | Purpose                              | Example                                                              |
| ------------------ | ------------------------------------ | -------------------------------------------------------------------- |
| **Shot ID**        | Variable name for code/triggers      | `front_full`                                                         |
| **Display Name**   | Human-readable label shown to users  | "Front of Vehicle"                                                   |
| **AI Description** | How Claude recognizes this shot type | "Full front view showing hood, grille, headlights, and front bumper" |
| **Distance**       | Expected framing                     | Wide / Mid / Close-up                                                |
| **Requirement**    | When this shot is needed             | Required / Conditional / Optional                                    |
| **Condition**      | Logic for conditional shots          | `airbags_deployed == true`                                           |
| **Extract Field**  | Link to extraction field             | VIN, License Plate, etc.                                             |

### Writing Good AI Descriptions

The AI Description is critical — it's what Claude uses to determine if a photo matches a shot type.

**Good descriptions include:**

* What should be visible in the frame
* Relative positioning and framing
* Key identifying features

**Example — Front of Vehicle:**

```
Full front view showing hood, grille, headlights, and front bumper. 
Vehicle should fill most of the frame. 
Shot from directly in front, not at an angle.
```

**Example — VIN Plate:**

```
Close-up of the VIN plate on the dashboard (visible through windshield) 
or on the door jamb sticker. All 17 characters must be clearly readable.
```

<Tip>
  Be specific about what makes this shot different from similar shots. For corners, specify which corner and the expected angle (e.g., "45-degree angle showing both front and driver side").
</Tip>

***

## Conditional Shots

Conditional shots are only required when a specific condition is true. This keeps the shot list manageable while ensuring you capture situational documentation.

### Condition Syntax

Conditions use the same variable syntax as Decision Triggers:

```
{variable} == {value}
{variable} != {value}
{variable} > {value}
```

### Common Conditions

| Shot               | Condition                  | When Required         |
| ------------------ | -------------------------- | --------------------- |
| Interior / Airbags | `airbags_deployed == true` | When airbags deployed |
| Glass Close-up     | `glass_damaged == true`    | When glass is damaged |
| Undercarriage      | `flood_damage == true`     | For flood claims      |
| Roof Damage        | `hail_reported == true`    | For hail claims       |

### Setting Condition Variables

Condition variables can be set by:

1. **Data Extraction** in an earlier node
2. **API Call** that returns claim details
3. **User Input** captured in the conversation
4. **Workflow Variables** passed from the trigger

***

## Plura Template Library

Plura ships with pre-built taxonomies for common use cases. These can be used as-is or cloned and customized.

### Auto Insurance

| Taxonomy                 | Shots               | Description                        |
| ------------------------ | ------------------- | ---------------------------------- |
| Auto Damage - Standard   | 12 (9 req, 3 cond)  | Standard FNOL documentation        |
| Auto Damage - Total Loss | 15 (12 req, 3 cond) | Extended for total loss evaluation |
| VIN Verification - Quick | 4 (4 req)           | Quick VIN + plate capture          |

### Homeowners Insurance

| Taxonomy                | Shots               | Description                   |
| ----------------------- | ------------------- | ----------------------------- |
| Water Damage - Standard | 14 (10 req, 4 cond) | Water intrusion documentation |
| Fire Damage - Standard  | 16 (12 req, 4 cond) | Fire and smoke damage         |
| Roof Damage - Standard  | 10 (8 req, 2 cond)  | Roof condition assessment     |

### Healthcare

| Taxonomy         | Shots     | Description                      |
| ---------------- | --------- | -------------------------------- |
| Insurance Card   | 2 (2 req) | Front and back of insurance card |
| Driver's License | 2 (2 req) | Front and back of ID             |

### Logistics

| Taxonomy             | Shots             | Description        |
| -------------------- | ----------------- | ------------------ |
| Package Intake       | 6 (4 req, 2 cond) | Shipment receiving |
| Damage Documentation | 8 (6 req, 2 cond) | Damage claims      |

***

## Example: Auto Damage - Standard

Here's the complete breakdown of the Auto Damage - Standard taxonomy:

### Required Shots (9)

| Shot ID          | Display Name       | AI Description                                            | Distance |
| ---------------- | ------------------ | --------------------------------------------------------- | -------- |
| `front_full`     | Front of Vehicle   | Full front view showing hood, grille, headlights, bumper  | Wide     |
| `rear_full`      | Rear of Vehicle    | Full rear view showing trunk/tailgate, taillights, bumper | Wide     |
| `left_side`      | Left Side          | Full driver side from front wheel to rear wheel           | Wide     |
| `right_side`     | Right Side         | Full passenger side from front wheel to rear wheel        | Wide     |
| `corner_fl`      | Front-Left Corner  | 45° angle showing front and driver side                   | Wide     |
| `corner_fr`      | Front-Right Corner | 45° angle showing front and passenger side                | Wide     |
| `corner_rl`      | Rear-Left Corner   | 45° angle showing rear and driver side                    | Wide     |
| `corner_rr`      | Rear-Right Corner  | 45° angle showing rear and passenger side                 | Wide     |
| `damage_closeup` | Damage Close-up    | Close-up of primary damage area, minimum 2 photos         | Close-up |

### Required with Extraction (3)

| Shot ID         | Display Name  | Extract Field | Validation        |
| --------------- | ------------- | ------------- | ----------------- |
| `vin_plate`     | VIN Plate     | VIN Number    | VIN Checksum      |
| `license_plate` | License Plate | Plate Number  | US Plate Format   |
| `odometer`      | Odometer      | Mileage       | Number (0-500000) |

### Conditional Shots (3)

| Shot ID            | Display Name       | Condition                  |
| ------------------ | ------------------ | -------------------------- |
| `interior_airbags` | Interior / Airbags | `airbags_deployed == true` |
| `glass_damage`     | Glass Close-up     | `glass_damaged == true`    |
| `undercarriage`    | Undercarriage      | `flood_damage == true`     |

***

## Taxonomy Versioning

When you update a taxonomy, existing in-flight conversations continue using the version they started with. New conversations use the updated taxonomy.

<Warning>
  Significant taxonomy changes should be tested before deployment. Consider cloning the taxonomy and testing the new version in a staging workflow before updating the production taxonomy.
</Warning>

***

## JSON Import/Export

For power users, taxonomies can be exported and imported as JSON.

### Export

Click **Export JSON** on any taxonomy detail view to download the configuration.

### Import

Use **Create Taxonomy → Import JSON** to create a new taxonomy from a JSON file.

### JSON Structure

```json theme={null}
{
  "name": "Auto Damage - Standard",
  "industry": "auto_insurance",
  "icon": "🚗",
  "shots": [
    {
      "id": "front_full",
      "display_name": "Front of Vehicle",
      "ai_description": "Full front view showing hood, grille...",
      "distance": "wide",
      "requirement": "required",
      "extract_field": null
    },
    {
      "id": "vin_plate",
      "display_name": "VIN Plate",
      "ai_description": "Close-up of VIN plate...",
      "distance": "closeup",
      "requirement": "required",
      "extract_field": "vin"
    },
    {
      "id": "interior_airbags",
      "display_name": "Interior / Airbags",
      "ai_description": "Interior shot showing deployed airbags...",
      "distance": "wide",
      "requirement": "conditional",
      "condition": "airbags_deployed == true",
      "extract_field": null
    }
  ]
}
```

***

## Best Practices

<CardGroup cols={2}>
  <Card title="Start with Templates" icon="copy">
    Clone a Plura template and customize rather than building from scratch.
  </Card>

  <Card title="Be Specific in Descriptions" icon="message">
    Detailed AI descriptions reduce misclassification and improve coverage accuracy.
  </Card>

  <Card title="Use Conditional Shots" icon="code-branch">
    Don't overload required shots — use conditions to keep the flow manageable.
  </Card>

  <Card title="Link Extraction Fields" icon="link">
    Connect shots to extraction when you need OCR data from that specific photo.
  </Card>
</CardGroup>

***

## Next Steps

* [Media Processing Node](/the-platform/workflows/nodes/media-processing-node) — Use taxonomies in workflows
* [Dynamic Data Extraction](/the-platform/workflows/nodes/media-processing-node#section-4-dynamic-data-extraction) — Configure extraction fields
* [Decision Triggers](/the-platform/workflows/decision-triggers) — Route based on coverage