🧭 Context Initialization

You are acting as an AI Systems Architect & Data Visualization Expert assisting in Phase 5 of the Jemy OS Project (pointer: OS-HISTORICAL-PREDICTIVE-005).

Your task is to analyze the existing Evolution Logs Collector module and prepare all necessary contextual knowledge for constructing the next visualization module called:

EvolutionHistoryChart
(to be integrated into CollectiveAdaptiveDashboard)
🧩 Source Knowledge

The current collector file (confirmed by passing unit tests) is
import { generateMetaForecast, MetaForecastResult } from './meta-forecast';
import { getTimelineHistory } from './timeline';

const STORAGE_KEY = 'os:evo:logs:v1';

export interface EvolutionLog {
  id: string;
  timestamp: string; // ISO
  trend: MetaForecastResult['trend'];
  confidence: number; // 0..1
  changeRate: number; // %
  notes?: string;
}

export function getEvolutionLogs(): EvolutionLog[] { ... }
export function logSnapshot(partial?: Partial<EvolutionLog>): EvolutionLog { ... }
export function startAutoSnapshot(opts?: AutoSnapshotOptions): void { ... }
export function stopAutoSnapshot(): void { ... }

🎯 Objective

Generate a comprehensive analysis + plan to build a historical visualization layer
showing the temporal evolution of system trends across time.

The chart should reflect:

trend → categorical dimension (possible values: Integrate, Reform, Reset)

confidence → numeric weight (0 → 1)

changeRate → % change indicator (line or bar overlay)

timestamp → chronological X-axis

🧠 Required Deliverables

Gemini must output structured, implementation-ready intelligence, including:

Data Mapping Plan

Define the transformation from EvolutionLog[] → chart-ready dataset.

Include TypeScript interface for the mapped data.

Propose normalization or aggregation if logs > 1000.

Trend Color System

Suggest color palette (light + dark mode) for each trend.

Base confidence visual cue (opacity / alpha) on confidence value.

Include example JSON color map.

Visualization Layout

Choose best chart structure (LineChart + Scatter overlay + Tooltip + Legend).

Specify Recharts components composition and axes configuration.

Detail how to combine confidence (0–1) as color or dot size.

Predictive Insights Model

Suggest how to infer possible next trend based on changeRate and confidence mean slope.

Output pseudocode for the next-step prediction (e.g., moving average + threshold).

Component Blueprint (React + TypeScript)

Skeleton code for <EvolutionHistoryChart /> component with props:
data: EvolutionLog[] and optional showPrediction?: boolean.

Include responsive layout + tooltip + legend + confidence gradient.

Integration Notes

How to import from history.collector and render within CollectiveAdaptiveDashboard.

Caching or memoization tips for large datasets.

Guidelines for incremental update when new logSnapshot() arrives.

⚙️ Environment Assumptions

Frontend: React 18 + Vite + TypeScript

Chart Library: Recharts (2.x)

Styling: TailwindCSS + HUD Theme Variables (--hud-primary, --hud-success, --hud-warning)

Runtime Data: LocalStorage from os:evo:logs:v1

Framework Goal: High-performance analytics dashboard with real-time trend tracking

🧪 Bonus Request

If possible, Gemini should provide:

Example mock dataset (5–6 logs) for local testing.

Suggested chart legend design (icons + labels + color gradient).

Any statistical insights that could make the chart “intelligent,”
e.g., detect stability plateaus or confidence surges

🧩 Expected Output Format

Gemini’s output should be a multi-section technical brief:

Overview Summary

Data Mapping Design (interfaces + logic)

Chart Structure (React Skeleton)

Predictive Heuristic (pseudocode)

Integration Plan

Final Goal:
Use Gemini’s output as the foundation document for the implementation phase inside Jemy’s OS system.
Gemini’s analysis will feed directly into ChatGPT (GPT-5) to code the actual EvolutionHistoryChart component with precision.

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