aios-core
Version:
Synkra AIOS: AI-Orchestrated System for Full Stack Development - Core Framework
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Markdown
## Execution Modes
**Choose your execution mode:**
### 1. YOLO Mode - Fast, Autonomous (0-1 prompts)
- Autonomous decision making with logging
- Minimal user interaction
- **Best for:** Simple, deterministic tasks
### 2. Interactive Mode - Balanced, Educational (5-10 prompts) **[DEFAULT]**
- Explicit decision checkpoints
- Educational explanations
- **Best for:** Learning, complex decisions
### 3. Pre-Flight Planning - Comprehensive Upfront Planning
- Task analysis phase (identify all ambiguities)
- Zero ambiguity execution
- **Best for:** Ambiguous requirements, critical work
**Parameter:** `mode` (optional, default: `interactive`)
## Task Definition (AIOS Task Format V1.0)
```yaml
task: generateAiFrontendPrompt()
responsável: Uma (Empathizer)
responsavel_type: Agente
atomic_layer: Template
**Entrada:**
- campo: name
tipo: string
origem: User Input
obrigatório: true
validação: Must be non-empty, lowercase, kebab-case
- campo: options
tipo: object
origem: User Input
obrigatório: false
validação: Valid JSON object with allowed keys
- campo: force
tipo: boolean
origem: User Input
obrigatório: false
validação: Default: false
**Saída:**
- campo: created_file
tipo: string
destino: File system
persistido: true
- campo: validation_report
tipo: object
destino: Memory
persistido: false
- campo: success
tipo: boolean
destino: Return value
persistido: false
```
## Pre-Conditions
**Purpose:** Validate prerequisites BEFORE task execution (blocking)
**Checklist:**
```yaml
pre-conditions:
- [ ] Target does not already exist; required inputs provided; permissions granted
tipo: pre-condition
blocker: true
validação: |
Check target does not already exist; required inputs provided; permissions granted
error_message: "Pre-condition failed: Target does not already exist; required inputs provided; permissions granted"
```
## Post-Conditions
**Purpose:** Validate execution success AFTER task completes
**Checklist:**
```yaml
post-conditions:
- [ ] Resource created successfully; validation passed; no errors logged
tipo: post-condition
blocker: true
validação: |
Verify resource created successfully; validation passed; no errors logged
error_message: "Post-condition failed: Resource created successfully; validation passed; no errors logged"
```
## Acceptance Criteria
**Purpose:** Definitive pass/fail criteria for task completion
**Checklist:**
```yaml
acceptance-criteria:
- [ ] Resource exists and is valid; no duplicate resources created
tipo: acceptance-criterion
blocker: true
validação: |
Assert resource exists and is valid; no duplicate resources created
error_message: "Acceptance criterion not met: Resource exists and is valid; no duplicate resources created"
```
## Tools
**External/shared resources used by this task:**
- **Tool:** component-generator
- **Purpose:** Generate new components from templates
- **Source:** .aios-core/scripts/component-generator.js
- **Tool:** file-system
- **Purpose:** File creation and validation
- **Source:** Node.js fs module
## Scripts
**Agent-specific code for this task:**
- **Script:** create-component.js
- **Purpose:** Component creation workflow
- **Language:** JavaScript
- **Location:** .aios-core/scripts/create-component.js
## Error Handling
**Strategy:** retry
**Common Errors:**
1. **Error:** Resource Already Exists
- **Cause:** Target file/resource already exists in system
- **Resolution:** Use force flag or choose different name
- **Recovery:** Prompt user for alternative name or force overwrite
2. **Error:** Invalid Input
- **Cause:** Input name contains invalid characters or format
- **Resolution:** Validate input against naming rules (kebab-case, lowercase, no special chars)
- **Recovery:** Sanitize input or reject with clear error message
3. **Error:** Permission Denied
- **Cause:** Insufficient permissions to create resource
- **Resolution:** Check file system permissions, run with elevated privileges if needed
- **Recovery:** Log error, notify user, suggest permission fix
## Performance
**Expected Metrics:**
```yaml
duration_expected: 3-8 min (estimated)
cost_estimated: $0.002-0.005
token_usage: ~1,500-5,000 tokens
```
**Optimization Notes:**
- Cache template compilation; minimize data transformations; lazy load resources
## Metadata
```yaml
story: N/A
version: 1.0.0
dependencies:
- N/A
tags:
- automation
- workflow
updated_at: 2025-11-17
```
# No checklists needed - this task generates prompts, validation is built into prompt generation methodology
tools:
- github-cli
- context7
# Create AI Frontend Prompt Task
## Purpose
To generate a masterful, comprehensive, and optimized prompt that can be used with any AI-driven frontend development tool (e.g., Vercel v0, Lovable.ai, or similar) to scaffold or generate significant portions of a frontend application.
## Inputs
- Completed UI/UX Specification (`front-end-spec.md`)
- Completed Frontend Architecture Document (`front-end-architecture`) or a full stack combined architecture such as `architecture.md`
- Main System Architecture Document (`architecture` - for API contracts and tech stack to give further context)
## Key Activities & Instructions
### 1. Core Prompting Principles
Before generating the prompt, you must understand these core principles for interacting with a generative AI for code.
- **Be Explicit and Detailed**: The AI cannot read your mind. Provide as much detail and context as possible. Vague requests lead to generic or incorrect outputs.
- **Iterate, Don't Expect Perfection**: Generating an entire complex application in one go is rare. The most effective method is to prompt for one component or one section at a time, then build upon the results.
- **Provide Context First**: Always start by providing the AI with the necessary context, such as the tech stack, existing code snippets, and overall project goals.
- **Mobile-First Approach**: Frame all UI generation requests with a mobile-first design mindset. Describe the mobile layout first, then provide separate instructions for how it should adapt for tablet and desktop.
### 2. The Structured Prompting Framework
To ensure the highest quality output, you MUST structure every prompt using the following four-part framework.
1. **High-Level Goal**: Start with a clear, concise summary of the overall objective. This orients the AI on the primary task.
- _Example: "Create a responsive user registration form with client-side validation and API integration."_
2. **Detailed, Step-by-Step Instructions**: Provide a granular, numbered list of actions the AI should take. Break down complex tasks into smaller, sequential steps. This is the most critical part of the prompt.
- _Example: "1. Create a new file named `RegistrationForm.js`. 2. Use React hooks for state management. 3. Add styled input fields for 'Name', 'Email', and 'Password'. 4. For the email field, ensure it is a valid email format. 5. On submission, call the API endpoint defined below."_
3. **Code Examples, Data Structures & Constraints**: Include any relevant snippets of existing code, data structures, or API contracts. This gives the AI concrete examples to work with. Crucially, you must also state what _not_ to do.
- _Example: "Use this API endpoint: `POST /api/register`. The expected JSON payload is `{ "name": "string", "email": "string", "password": "string" }`. Do NOT include a 'confirm password' field. Use Tailwind CSS for all styling."_
4. **Define a Strict Scope**: Explicitly define the boundaries of the task. Tell the AI which files it can modify and, more importantly, which files to leave untouched to prevent unintended changes across the codebase.
- _Example: "You should only create the `RegistrationForm.js` component and add it to the `pages/register.js` file. Do NOT alter the `Navbar.js` component or any other existing page or component."_
### 3. Assembling the Master Prompt
You will now synthesize the inputs and the above principles into a final, comprehensive prompt.
1. **Gather Foundational Context**:
- Start the prompt with a preamble describing the overall project purpose, the full tech stack (e.g., Next.js, TypeScript, Tailwind CSS), and the primary UI component library being used.
2. **Describe the Visuals**:
- If the user has design files (Figma, etc.), instruct them to provide links or screenshots.
- If not, describe the visual style: color palette, typography, spacing, and overall aesthetic (e.g., "minimalist", "corporate", "playful").
3. **Build the Prompt using the Structured Framework**:
- Follow the four-part framework from Section 2 to build out the core request, whether it's for a single component or a full page.
4. **Present and Refine**:
- Output the complete, generated prompt in a clear, copy-pasteable format (e.g., a large code block).
- Explain the structure of the prompt and why certain information was included, referencing the principles above.
- <important_note>Conclude by reminding the user that all AI-generated code will require careful human review, testing, and refinement to be considered production-ready.</important_note>