Neural trading strategies — self-learning LSTM/Transformer/N-BEATS models with Rust/NAPI backtesting
Plugin ruflo-neural-trader from marketplace ruflo in ruvnet/ruflo. Commands read from the repo's manifest — today.
trader-backtestRun a historical backtest using npx neural-trader with Rust/NAPI engine (8-19x faster) and walk-forward validation; Ed25519-sign the result for paper→live tamper evidence (ADR-126 Phase 4)
trader-cloud-backtestRun a heavy neural-trader job (long walk-forward, big Monte-Carlo, parameter sweep, model training) on the Anthropic Managed Agent cloud runtime instead of locally
trader-explainRegulator-grade feature attribution for any LSTM/Transformer signal — single-entry PageRank ranks the top-K features that drove the prediction (ADR-126 Phase 6, ADR-123 single-entry PR)
trader-portfolio-cgMean-variance portfolio optimization via Conjugate Gradient — 40-60× faster than the legacy Neumann path (ADR-126 Phase 3, ADR-123 Wedge 8)
trader-portfolioOptimize portfolio allocation using npx neural-trader mean-variance engine with risk constraints and rebalancing plan
trader-regimeDetect current market regime using npx neural-trader — bull/bear/ranging/volatile classification with recommended strategy. Use when the user asks about market conditions, wants to pick a strategy for current conditions, or before running a backtest/signal that should be regime-aware.
trader-riskAssess portfolio risk using npx neural-trader — VaR, CVaR, Sharpe, position sizing, circuit breaker status
trader-signalGenerate trading signals using npx neural-trader anomaly detection engine with Z-score scoring and neural prediction
trader-trainTrain neural models (LSTM, Transformer, N-BEATS) on market data using npx neural-trader with confidence intervals
/ruflo-neural-trader:traderNeural trading via npx neural-trader — strategies, backtesting, signals, risk, portfolio optimization
backtest-engineerBacktesting specialist using npx neural-trader Rust/NAPI engine — walk-forward validation, Monte Carlo simulation, parameter optimization. Orthogonal research lane (ADR-126 Phase 5) — produces signed promotion candidates, NOT a hot-path participant in live execution
market-analystMarket regime detection and technical analysis using npx neural-trader — RSI, MACD, Bollinger Bands, volume profile, regime classification. Pipeline entry point — sends RegimeVerdict to trading-strategist (ADR-126 Phase 5)
risk-analystPortfolio risk assessment and position sizing using npx neural-trader — VaR/CVaR, Kelly criterion, circuit breakers, correlation monitoring. Pipeline BLOCKING GATE — receives SignalProposal from trading-strategist, returns RiskDecision (ADR-126 Phase 5)
trading-strategistDesigns and optimizes neural trading strategies using npx neural-trader — LSTM/Transformer models, Rust/NAPI backtesting, Z-score anomaly detection. Pipeline middle stage — receives RegimeVerdict from market-analyst, sends SignalProposal[] to risk-analyst, gated on RiskDecision approval (ADR-126 Pha
Agentic QE (external: maintained in proffesor-for-testing/agentic-qe, pinned to v3.15.17): a quality-engineering fleet with 11 QE agents, 9 skills, 9 commands, the agentic-qe MCP server pinned to the plugin version, and the aqe-mod guard that refuses destructive operations on AQE learning data
9 skills · 9 commands · 11 agents · 1 MCP server
Token usage tracking, model cost attribution per agent, budget alerts, and optimization recommendations
24 skills · 1 command · 1 agent · hooks
Tenant-isolated AI teams that plan work, coordinate tasks, recall approved context, and return evidence-backed results
6 skills · 6 commands · 4 agents · 1 MCP server
Agent runtimes — local WASM-sandboxed agents (rvagent) + Anthropic Claude Managed Agents (cloud); one interface, local-vs-cloud backends
5 skills · 2 commands · 9 agents
MetaHarness integration — surfaces score/genome/mint/mcp-scan/threat-model via skills; pairs with @metaharness/router (ADR-148/149) for cost-optimal model routing; honors ADR-150 optional-augmentation constraint
13 skills · 1 command · 1 agent · hooks
Visual workflow automation with templates, orchestration, and lifecycle management
5 skills · 8 commands · 3 agents
The official CCXT MCP server plus the ccxt-mcp usage skill — market data, balances and opt-in trading across 100+ crypto exchanges and prediction markets, with keys kept local.
1 MCP server
Quantitative analysis, algorithmic trading strategies, financial modeling, portfolio risk management, and backtesting
2 skills · 2 agents
Price bonds, analyze yield curves, evaluate FX carry trades, value options, and build macro dashboards using LSEG financial data and analytics.
8 skills · 8 commands · 1 MCP server
Price bonds, analyze yield curves, evaluate FX carry trades, value options, and build macro dashboards using LSEG financial data and analytics.
8 skills · 8 commands · 1 MCP server
End-to-end feature-flag discipline: classify, ship, ramp, retire. Detects stale flags as debt, generates phased rollout plans (ring/linear/log/cohort), and audits every flag for a documented kill switch. 3 stdlib Python tools, 4 references on flag taxonomy + provider trade-offs (LaunchDarkly/GrowthBook/Statsig/Unleash/Flipt/DIY) + rollout strategies + lifecycle. /flag-cleanup slash command. Cross-tool compatible.
1 skill
Skills for event and conference sponsorship work on live data: sponsorship context, find sponsors for an event, price packages, draft a prospectus, draft sponsor outreach, vet a trade show, budget a booth, track where competitors exhibit, build an events calendar. Adds 9 skills and the hosted ConferenceDB MCP server (https://conferencedatabase.com/api/mcp); no sign-in, no API key. Company-level data only: no people, emails or phone numbers. Drafting only: no skill sends anything.
9 skills · 1 MCP server
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