# New Application / Add Moduels-Features to Existing Application Prompts - json file

> Generate FlexBase-ready JSON from new application requirements or module/feature designs following DDD principles.

## When to Use

* You have analyzed business requirements and need **FlexBase JSON output**
* You want to generate JSON **directly from user requirements**
* You need **structured JSON** for FlexBase Studio import

## How to Use

Tell your AI agent what JSON you need. It will load the JSON structure rules and conventions automatically.

**Example prompts you can give your AI agent:**

```
Generate FlexBase JSON for a new healthcare scheduling application
```

```
Create FlexBase JSON for a new Payments module
```

```
Generate domain services JSON with full attributes for my new application
```

```
Convert this application design markdown to FlexBase JSON
```

***

## Task Catalog

### Task 1: Complete Application JSON

**Goal:** Generate JSON for an entire new application\
**User provides:** Business requirements\
**Output:** `[ProjectName]_Flexbase_Import.json`

### Task 2: New Module JSON

**Goal:** Generate JSON for a new module to add to an existing application\
**User provides:** Module requirements\
**Output:** Module JSON with features, validations, events

### Task 3: New Features JSON

**Goal:** Generate JSON for new features in an existing module\
**User provides:** Feature requirements and target module\
**Output:** Features JSON with validations and events

### Task 4: Quick JSON from Requirements

**Goal:** Fast JSON generation from brief requirements\
**User provides:** Brief business description\
**Output:** `[ProjectName]_Flexbase_Import.json`

### Task 5: Domain Services with Full Properties

**Goal:** Generate detailed domain services with attributes, relationships, and indexes\
**User provides:** Entity descriptions or existing analysis\
**Output:** `[ProjectName]_DomainServices.json` with full attribute definitions

### Task 6: UI-Enriched JSON

**Goal:** Generate JSON with screen/UI metadata on features\
**User provides:** Application requirements with UI descriptions\
**Output:** JSON with `metadata.screenFlow` on UI-facing features

### Task 7: Screen Definition JSON

**Goal:** Generate screen definitions with controls referencing features\
**User provides:** Application requirements with UI descriptions\
**Output:** `[ProjectName]_[ModuleName]_Screens.json` — one per module

### Task 8: Incremental Feature Addition JSON

**Goal:** Generate JSON for additional features to merge with existing import\
**User provides:** New feature requirements + existing module context\
**Output:** Per-module feature JSON files

### Task 9: Event-Driven Architecture JSON

**Goal:** Generate JSON with complex event chains and multi-level subscribers\
**User provides:** Event flow description\
**Output:** Features JSON with nested event/subscriber hierarchies

***

## Key Rules (Applied Automatically)

* **3-section JSON structure:** `modules`, `domainServices`, `modulesWithFeatures` (+ `modulesWithScreens` for UI apps)
* **Every operation = one feature** — no operations array inside features
* **Module names PLURAL** PascalCase
* **Only complex validations** in JSON — skip simple attribute validations
* **Files auto-split when large** — per-module JSON files + full combined import

***

## Related

* **Markdown design first:** [New Application → Markdown](/flexbase-mcp-ai-prompts/new-application-add-moduels-features-to-existing-application-prompts-md-file.md)
* **After import:** [Implementation Completion](/flexbase-mcp-ai-prompts/implementation-completion-prompts.md)


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# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.flexbase.in/flexbase-mcp-ai-prompts/new-application-add-moduels-features-to-existing-application-prompts-json-file.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.