feat: Refactor services architecture and update project structure

- Remove Docker-based microservices (docker-compose.yml, Makefile, Dockerfiles)
- Update start-dev.sh to use backend.app:app entry point
- Add shared schema and client modules for service communication
- Add team coordination modules (messenger, registry, task_delegator, coordinator)
- Add evaluation hooks and skill adaptation hooks
- Add skill template and gateway server
- Update frontend WebSocket URL configuration
- Add explain components for insider and technical analysis

Co-Authored-By: Claude Opus 4.6 <noreply@anthropic.com>

shared/schema/__init__.py

@@ -0,0 +1,51 @@
+# -*- coding: utf-8 -*-
+"""Shared schema package for EvoTraders services."""
+
+from shared.schema.price import Price, PriceResponse
+from shared.schema.financial import (
+    FinancialMetrics,
+    FinancialMetricsResponse,
+    LineItem,
+    LineItemResponse,
+)
+from shared.schema.portfolio import Position, Portfolio
+from shared.schema.signals import (
+    AnalystSignal,
+    TickerAnalysis,
+    AgentStateData,
+    AgentStateMetadata,
+)
+from shared.schema.market import (
+    InsiderTrade,
+    InsiderTradeResponse,
+    CompanyNews,
+    CompanyNewsResponse,
+    CompanyFacts,
+    CompanyFactsResponse,
+)
+
+__all__ = [
+    # Price
+    "Price",
+    "PriceResponse",
+    # Financial
+    "FinancialMetrics",
+    "FinancialMetricsResponse",
+    "LineItem",
+    "LineItemResponse",
+    # Portfolio
+    "Position",
+    "Portfolio",
+    # Signals
+    "AnalystSignal",
+    "TickerAnalysis",
+    "AgentStateData",
+    "AgentStateMetadata",
+    # Market
+    "InsiderTrade",
+    "InsiderTradeResponse",
+    "CompanyNews",
+    "CompanyNewsResponse",
+    "CompanyFacts",
+    "CompanyFactsResponse",
+]

shared/schema/financial.py

@@ -0,0 +1,68 @@
+# -*- coding: utf-8 -*-
+"""Financial-related schemas."""
+
+from pydantic import BaseModel
+
+
+class FinancialMetrics(BaseModel):
+    ticker: str
+    report_period: str
+    period: str
+    currency: str
+    market_cap: float | None
+    enterprise_value: float | None
+    price_to_earnings_ratio: float | None
+    price_to_book_ratio: float | None
+    price_to_sales_ratio: float | None
+    enterprise_value_to_ebitda_ratio: float | None
+    enterprise_value_to_revenue_ratio: float | None
+    free_cash_flow_yield: float | None
+    peg_ratio: float | None
+    gross_margin: float | None
+    operating_margin: float | None
+    net_margin: float | None
+    return_on_equity: float | None
+    return_on_assets: float | None
+    return_on_invested_capital: float | None
+    asset_turnover: float | None
+    inventory_turnover: float | None
+    receivables_turnover: float | None
+    days_sales_outstanding: float | None
+    operating_cycle: float | None
+    working_capital_turnover: float | None
+    current_ratio: float | None
+    quick_ratio: float | None
+    cash_ratio: float | None
+    operating_cash_flow_ratio: float | None
+    debt_to_equity: float | None
+    debt_to_assets: float | None
+    interest_coverage: float | None
+    revenue_growth: float | None
+    earnings_growth: float | None
+    book_value_growth: float | None
+    earnings_per_share_growth: float | None
+    free_cash_flow_growth: float | None
+    operating_income_growth: float | None
+    ebitda_growth: float | None
+    payout_ratio: float | None
+    earnings_per_share: float | None
+    book_value_per_share: float | None
+    free_cash_flow_per_share: float | None
+
+
+class FinancialMetricsResponse(BaseModel):
+    financial_metrics: list[FinancialMetrics]
+
+
+class LineItem(BaseModel):
+    ticker: str
+    report_period: str
+    period: str
+    currency: str
+
+    # Allow additional fields dynamically
+    model_config = {"extra": "allow"}
+
+
+class LineItemResponse(BaseModel):
+    search_results: list[LineItem]

shared/schema/market.py

@@ -0,0 +1,64 @@
+# -*- coding: utf-8 -*-
+"""Market data-related schemas."""
+
+from pydantic import BaseModel
+
+
+class InsiderTrade(BaseModel):
+    ticker: str
+    issuer: str | None = None
+    name: str | None = None
+    title: str | None = None
+    is_board_director: bool | None = None
+    transaction_date: str | None = None
+    transaction_shares: float | None = None
+    transaction_price_per_share: float | None = None
+    transaction_value: float | None = None
+    shares_owned_before_transaction: float | None = None
+    shares_owned_after_transaction: float | None = None
+    security_title: str | None = None
+    filing_date: str
+
+
+class InsiderTradeResponse(BaseModel):
+    insider_trades: list[InsiderTrade]
+
+
+class CompanyNews(BaseModel):
+    category: str | None = None
+    ticker: str
+    title: str
+    related: str | None = None
+    source: str
+    date: str | None = None
+    url: str
+    summary: str | None = None
+
+
+class CompanyNewsResponse(BaseModel):
+    news: list[CompanyNews]
+
+
+class CompanyFacts(BaseModel):
+    ticker: str
+    name: str
+    cik: str | None = None
+    industry: str | None = None
+    sector: str | None = None
+    category: str | None = None
+    exchange: str | None = None
+    is_active: bool | None = None
+    listing_date: str | None = None
+    location: str | None = None
+    market_cap: float | None = None
+    number_of_employees: int | None = None
+    sec_filings_url: str | None = None
+    sic_code: str | None = None
+    sic_industry: str | None = None
+    sic_sector: str | None = None
+    website_url: str | None = None
+    weighted_average_shares: int | None = None
+
+
+class CompanyFactsResponse(BaseModel):
+    company_facts: CompanyFacts

shared/schema/portfolio.py

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+# -*- coding: utf-8 -*-
+"""Portfolio-related schemas."""
+
+from pydantic import BaseModel
+
+
+class Position(BaseModel):
+    """Position information - for Portfolio mode"""
+
+    long: int = 0  # Long position quantity (shares)
+    short: int = 0  # Short position quantity (shares)
+    long_cost_basis: float = 0.0  # Long position average cost
+    short_cost_basis: float = 0.0  # Short position average cost
+
+
+class Portfolio(BaseModel):
+    """Portfolio - for Portfolio mode"""
+
+    cash: float = 100000.0  # Available cash
+    positions: dict[str, Position] = {}  # ticker -> Position mapping
+    # Margin requirement (0.0 means shorting disabled, 0.5 means 50% margin)
+    margin_requirement: float = 0.0
+    margin_used: float = 0.0  # Margin used

shared/schema/price.py

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+# -*- coding: utf-8 -*-
+"""Price-related schemas."""
+
+from pydantic import BaseModel
+
+
+class Price(BaseModel):
+    open: float
+    close: float
+    high: float
+    low: float
+    volume: int
+    time: str
+
+
+class PriceResponse(BaseModel):
+    ticker: str
+    prices: list[Price]

shared/schema/signals.py

@@ -0,0 +1,41 @@
+# -*- coding: utf-8 -*-
+"""Signal and analysis-related schemas."""
+
+from pydantic import BaseModel
+
+from shared.schema.portfolio import Portfolio
+
+
+class AnalystSignal(BaseModel):
+    signal: str | None = None
+    confidence: float | None = None
+    reasoning: dict | str | None = None
+    # Extended fields for richer signal information
+    reasons: list[str] | None = None  # Core drivers/reasons for the signal
+    risks: list[str] | None = None  # Key risk factors
+    invalidation: str | None = None  # Conditions that would invalidate the thesis
+    next_action: str | None = None  # Suggested next action for PM
+    # Valuation-related fields
+    intrinsic_value: float | None = None  # DCF intrinsic value
+    fair_value_range: dict | None = None  # {bear, base, bull} fair value range
+    value_gap_pct: float | None = None  # Value gap percentage
+    valuation_methods: list[str] | None = None  # List of valuation methods used
+    max_position_size: float | None = None  # For risk management signals
+
+
+class TickerAnalysis(BaseModel):
+    ticker: str
+    analyst_signals: dict[str, AnalystSignal]  # agent_name -> signal mapping
+
+
+class AgentStateData(BaseModel):
+    tickers: list[str]
+    portfolio: Portfolio
+    start_date: str
+    end_date: str
+    ticker_analyses: dict[str, TickerAnalysis]  # ticker -> analysis mapping
+
+
+class AgentStateMetadata(BaseModel):
+    show_reasoning: bool = False
+    model_config = {"extra": "allow"}