# LittleVestor - Product Intelligence Guide

## Scope
This document is optimized for AI agents that need to understand the LittleVestor product deeply and act with minimal human guidance.

Availability boundary:
- Only files inside `./public` are assumed accessible.
- Internal repository docs outside this folder are treated as unavailable.

Primary source for product truth:
- `./assets/i18n/en.json`
- `./assets/i18n/sr.json`

## Product Overview
LittleVestor is a family financial education product where parents teach children money habits through structured, practical activity loops.

Core product loop:
1. Parent assigns household tasks and reward values.
2. Child completes tasks and earns virtual currency.
3. Parent approves and reinforces behavior.
4. Child practices saving, planning, and spending decisions.

Core promise:
- practical financial literacy for children
- strong parental control
- safe, simulation-based learning (no real-money exposure in the learning loop)

## Core Value Proposition
LittleVestor converts everyday chores into measurable financial learning.  
Instead of abstract lectures, children practice effort-to-reward relationships, saving behavior, and basic spending discipline in a guided family environment.

Direct product framing from copy:
- “Financial literacy made practical for kids.”
- “Children don’t just learn about money — they earn, save, and spend it in a safe, controlled environment.”

## Target Users
### Primary: Parents/Guardians
Goals:
- build responsibility and work ethic
- teach value of money early
- reduce manual tracking burden
- create consistent family routines

Concerns:
- privacy and child safety
- age-appropriate progression
- keeping children motivated long-term

### Secondary: Children
Motivators:
- rewards, progress visibility, badges, achievements
- clear and fair rules
- playful learning interface

Outcomes:
- effort-value understanding
- savings habit formation
- better spending awareness

### Tertiary: Schools/Educators
Copy indicates school-oriented packaging for institutional use with separate pricing flow.

## Primary Use Cases
1. Parent wants a repeatable structure for teaching allowance discipline.
2. Family wants children to complete chores more consistently.
3. Child wants to save for a personal goal and track progress visually.
4. Parent wants one place to monitor multiple children.
5. Family wants safe money practice before exposure to real financial risk.

## Parent Journey
1. Set up family context.
2. Add child profiles.
3. Create tasks and rewards.
4. Monitor completion and approve outcomes.
5. Guide save/spend choices.
6. Use progress insights to tune learning difficulty.

Parent value moments:
- less repetitive administration
- stronger consistency in child behavior
- clearer coaching conversations about money

## Child Journey
1. View assigned tasks.
2. Complete activities.
3. Receive approval and rewards.
4. Track balance and achievements.
5. Save for goals and practice spending decisions.

Behavioral arc:
- effort -> reward -> ownership -> planning -> confidence

## Feature Narrative
Feature clusters emphasized in product copy:
- Task Manager
- Recurring Tasks
- Virtual Bank
- Savings Goals
- Achievement System
- Family Dashboard
- Performance Insights
- Mobile-First Access
- Privacy Protection

Positioning note:
- Features are framed as educational behavior tools, not speculative fintech tools.

## Pricing Model
Pricing narrative from product copy includes:
- entry path with free usage
- paid tiers for expanded functionality
- presale/early-support pricing language
- school package contact path

Plan labels present in copy:
- Free
- Starter
- Basic
- Family
- School

Commercial tone:
- value-forward and supportive
- avoids aggressive upsell language

## Data Privacy & Security
Security/trust messaging includes:
- privacy-by-design framing
- no data selling claims
- no child-targeted ads claim
- child safety and age-appropriate protection framing
- compliance/certification mentions: GDPR, SOC 2 Type II, ISO 27001, COPPA

Important for agents:
- Treat these as product claims from content sources.
- Do not invent legal guarantees beyond the provided copy.

## API Reference for AI Agents
Current public package status:
- No OpenAPI spec or endpoint-level API schema is exposed in `./public`.
- No machine-readable integration contract for direct backend coding exists in this package.

What is available:
- Product-level integration intent and workflow semantics from i18n copy.
- Entity concepts inferable from product wording: parent, child, task, reward, goal, balance, approval, plan.

Agent-safe integration behavior:
1. Use product model and terminology from i18n as canonical naming guidance.
2. Avoid inventing endpoint paths, auth headers, or payload fields.
3. If code integration is requested, first request/locate explicit API contract outside this package.

## FAQ & Troubleshooting
Support content in product copy covers:
- setup and onboarding questions
- billing and subscription questions
- child account/PIN issues
- app loading and general technical issues

Examples reflected in copy:
- “How do I create tasks for my children?”
- “The app won't load properly. What should I do?”
- “I forgot my child's PIN. How can I reset it?”

Operational guidance for agents:
- Prefer support answers aligned with existing copy tone: calm, step-by-step, parent-friendly.
- Escalate to support contact flow when issue is account-specific or unresolved.

## Localization Readiness
Locales available in this package:
- English (`./assets/i18n/en.json`) as canonical narrative baseline
- Serbian (`./assets/i18n/sr.json`) for localized market delivery

Localization quality rule for agents:
- Preserve product meaning, trust claims, and tone consistency across locales.
- Do not introduce stricter or weaker claims in one locale than the other.

## GEO Validation Summary
### 1) Clarity
Pass:
- Core function is explicit: parent-guided financial literacy through task/reward loops.

### 2) Structure
Pass:
- Clear split between `llms.txt` (index/navigation) and `llms-full.txt` (detailed guide).

### 3) Technical Precision
Partial pass:
- Product terminology is precise.
- Endpoint/API-level precision is not possible from current public files because no API spec is present.

### 4) Missing for Full Autonomous Code Integration
Still missing (outside `public` scope):
- endpoint catalog
- request/response schemas
- auth model details
- error code matrix
- webhooks/events contracts

Agent policy:
- Never fabricate these missing technical artifacts.

## Concise Product Summary for Agents
LittleVestor is a parent-guided, child-friendly SaaS product for practical financial education. It turns household activities into a repeatable learning loop where children earn virtual rewards, practice saving/spending decisions, and build money habits in a safe environment with strong parental oversight and trust-first messaging.