Skip to main content

Catalog Overview

ChimeraMiND is not a single trading bot with a UI wrapped around it. The platform is built from eight distinct capability layers — introspection tooling, execution routes, bot definitions, strategy logic, machine learning, exchange connectivity, real-time analytics, and core execution subsystems. This page is the index; each linked page below documents the capabilities in that layer with the actual module/file it maps to, so every number here is traceable back to source rather than a rolled-up marketing total.

Capability count by layer

LayerCountDetail
MCP introspection tools60 tools / 10 domainsRead-only observability surface (portfolio, analytics, AI state, market data)
REST API routes67 route filesTrading, portfolio, risk, config, calibration, infra
Trading bot types21 (16 active, 5 in stub/partial/minimal status)DCA, grid, momentum, breakout, cascade, arbitrage variants, and more — see Trading Bots
Core strategy modules15Orchestrated as one ensemble, not run in isolation — production authority varies per module, see ML Models
ML models5 model familiesDirection (GBM, inference active/execution shadow-gated), regime (HMM, gate/context), cascade risk (active as risk blocker), microstructure (DeepLOB, shadow/0-weight), meta-optimizer (RL, meta-only) — see ML Models for the per-model status
Exchange gateways7 modules (6 external + 1 paper)Binance, OKX, Bybit, Bitget, Coinbase, Kraken, Paper — see Exchange Gateways
Real-time analytics streams14VPIN, CVD, OI velocity, regime, breadth, and more — see Analytics Streams
Core execution subsystems24+Risk, calibration, portfolio, feeders, liquidation detection, on-chain tracking

Why the count is presented this way

Each number above is a count of things that actually exist in the codebase — files, registered tools, or configured integrations — not a marketing estimate. The MCP tool count and domain breakdown come directly from chimera_mcp/server.py. The route file count comes from api/routes/. The strategy and model counts come from strategy/ and the model-serving layer. This catalog is meant to survive a technical reviewer opening the repository and checking.

What "antifragile" means here

The platform's core differentiator is not any single model or bot — it is that 15 strategy modules are coordinated through a consensus/voting layer (strategy_mux, decision_engine) into one adaptive decision process, with a reinforcement-learning meta-optimizer adjusting parameters against forward-paper performance telemetry (see Metrics Methodology for what "performance" means today). See Architecture Overview for how this fits into the runtime.