Add comprehensive --help documentation and --version flag

These files were tracked despite being in .gitignore patterns.
Removing them prevents accidental credential leakage in logs.

Compare multi-agent orchestration pattern (QuantCoder Gamma) vs
event-driven TUI pattern (OpenCode) including:
- Technology stacks (Python vs Go)
- Agent architectures and execution models
- Tool systems and MCP integration
- LLM provider strategies
- State management approaches
- Self-improvement capabilities

Add Mistral Vibe CLI as the third architecture in the comparison,
noting that QuantCoder Gamma's CLI was explicitly "inspired by
Mistral Vibe CLI" (see quantcoder/cli.py:1).

Key additions:
- Mistral Vibe CLI architecture (minimal single-agent design)
- Three-tier permission model (always/ask/disabled)
- Project-aware context scanning
- Devstral model requirements and capabilities
- Lineage diagram showing inspiration flow
- Expanded tool, config, and UI comparisons

…g Operator

Based on successful gamma branch testing (15/15 tests passing), design
adaptations of the multi-agent architecture for two new use cases:

1. Research Assistant:
   - Search, Paper, Patent, Web agents
   - Synthesis and Report agents
   - Tools for academic search, PDF parsing, citation management

2. Trading Operator:
   - Position, Risk, Execution, Reporting agents
   - Broker adapters (IB, Alpaca, QC, Binance)
   - Real-time P&L tracking and risk management

Both reuse core gamma components:
- Multi-agent orchestration pattern
- Parallel execution framework
- LLM provider abstraction
- Tool system base classes
- Learning database for self-improvement

Document the application's architecture including:
- High-level system architecture diagram
- CLI entry points and command flow
- Article search and PDF download flows
- Article processing pipeline with NLP stages
- Code generation and refinement loop
- GUI workflow and window layout
- Data/entity relationships
- File structure reference with line numbers

Replace previous architecture docs with comprehensive gamma branch analysis:
- Multi-agent orchestration system (Coordinator, Universe, Alpha, Risk, Strategy)
- Tool-based architecture inspired by Mistral Vibe pattern
- Autonomous self-improving pipeline with error learning
- Library builder system for comprehensive strategy generation
- LLM provider abstraction (OpenAI, Anthropic, Mistral, DeepSeek)
- Parallel execution framework with AsyncIO
- Interactive and programmatic chat interfaces
- Learning database for pattern extraction and prompt refinement

- VERSIONS.md: Comprehensive guide for v1.0, v1.1, and v2.0
  - Feature comparison table
  - Installation instructions per version
  - Upgrade path recommendations
  - Use case guidance

- CHANGELOG.md: Detailed changelog following Keep a Changelog format
  - v1.0: Legacy features (OpenAI v0.28, Tkinter GUI)
  - v1.1: LLM client abstraction, QC static validator
  - v2.0: Multi-agent architecture, autonomous pipeline (unreleased)
  - Migration notes between versions

- Comprehensive 20-line project description
- Production readiness matrix scoring 30/50 (60%)
- Identified critical gaps: no testing, legacy OpenAI SDK, security concerns
- Documented strengths and recommendations
- Classified as NOT production-ready without hardening

- Assessed claude/alphaevolve-cli-evaluation-No5Bx (most advanced branch)
- Document new evolver module (+1,595 lines of code)
- Detail AlphaEvolve-inspired evolution architecture
- Score remains 30/50 (60%) - NOT production ready
- Key gaps: no tests, legacy OpenAI SDK, sequential backtests
- Note significant improvement from v0.3: full QuantConnect API integration

- Complete platform evolution: quantcli → quantcoder
- Score: 88% (44/50) - NEARLY PRODUCTION READY
- Key features: Multi-agent architecture, 4 LLM providers, autonomous mode
- Modern stack: OpenAI v1.0+, pytest, CI/CD, async execution
- 8,000+ lines across 35+ modules vs 1,500 in legacy
- Remaining: expand test coverage, battle-test MCP integration

Features:
- EvolutionEngine: Main orchestrator for evolution loop
- VariationGenerator: LLM-based mutation and crossover (7 strategies)
- QCEvaluator: QuantConnect backtest integration with async support
- ElitePool: Persistence layer ensuring best solutions never lost
- EvolutionConfig: Multi-objective fitness (Sharpe, drawdown, returns, win rate)

CLI Commands:
- quantcoder evolve start <id>    Evolve an algorithm
- quantcoder evolve list          List saved evolutions
- quantcoder evolve show <id>     Show evolution details
- quantcoder evolve export <id>   Export best algorithm

Adapted from alphaevolve branch for gamma's async multi-provider architecture.
Supports resumable evolution runs with JSON state persistence.

Document findings from code review including:
- Overall score: 7.5/10
- 4 critical issues (bare except, plain-text API keys, low test coverage, print statements)
- Metrics summary and prioritized remediation plan

- Evolve branch = gamma + evolver module
- Updated score: 90% (45/50) - Production Ready
- Used same scoring criteria as gamma assessment
- Added branch comparison summary

- Add BacktestTool for running backtests via QuantConnect API
- Update ValidateCodeTool to use MCP for real QuantConnect compilation
- Add backtest and validate CLI commands
- Wire backtest/validate tools into interactive chat
- Update autonomous pipeline to use real MCP validation/backtest
- Add QuantConnect credential loading to Config
- Add has_quantconnect_credentials() check for graceful degradation

Tools now work with real QuantConnect API when credentials are set:
  QUANTCONNECT_API_KEY and QUANTCONNECT_USER_ID in ~/.quantcoder/.env

Analyzed all 17 branches and compiled prioritized upgrades:
- MCP wiring (HIGH): Enable real backtest/validate
- Evolution engine (HIGH): AlphaEvolve optimization
- Ollama provider (HIGH): Local LLM support
- Editor integration (MEDIUM): Zed/VSCode support
- Documentation (MEDIUM): Architecture diagrams

- Fix syntax error in llm/providers.py:258: "Mistral Provider" -> "MistralProvider"
  This prevented the entire LLM providers module from being imported.

- Fix bare exception handling in coordinator_agent.py:135
  Changed `except:` to `except (json.JSONDecodeError, ValueError):`
  to properly catch only JSON parsing errors instead of all exceptions.

These fixes were identified during comprehensive quality assessment of the
gamma branch and are required for the code to function properly.

…eline

- Implement _fetch_papers() with real arXiv and CrossRef API integration
- Integrate CoordinatorAgent for actual strategy generation in _generate_strategy()
- Add comprehensive code validation using AST and QuantConnect patterns
- Connect _backtest() to QuantConnectMCPClient for real backtesting
- Implement file writing in _store_strategy() with metadata and README generation

The autonomous pipeline now uses existing tools and agents instead of
returning mock data when not in demo mode.

…peline

- Real arXiv/CrossRef API integration for paper fetching
- CoordinatorAgent integration for strategy generation
- AST + QuantConnect-specific code validation
- QuantConnectMCPClient for backtesting
- File writing with metadata and README generation

…' into claude/assess-gamma-quality-qhC6n

Add CI/CD pipeline, documentation, and project cleanup

- Add editor config option to UIConfig (default: zed)
- Create editor.py utility module for launching editors
- Add --open-in-editor flag to generate command
- Add --editor flag to override configured editor

Add editor integration to open generated code files

- Fix version inconsistencies (2.0.0 → 2.1.0 across all files)
- Add missing dependencies to pyproject.toml (anthropic, mistralai, aiohttp)
- Remove 12 redundant documentation files (cleanup summaries, branch guides, assessments)
- Move ARCHITECTURE.md and VERSIONS.md to docs/
- Delete obsolete files (requirements-legacy.txt, reorganize-branches.sh)
- Update README.md with cleaner header and correct links