Generate explainable China Sports Lottery football predictions with event-time snapshots, T-24h/T-6h/T-90m/closing model horizons, separate directional and value states, strict reference/target market isolation, sourced pre-match intelligence, hierarchical Dixon-Coles probabilities, multi-window model validation…
Backtesting and simulation: vectorized backtesting, paper trading simulation, strategy A/B testing, automated strategy building, natural language to strategy, and trading plan generation. USE FOR: backtest, backtesting, paper trading, simulation, strategy builder, A/B test strategies, natural language strategy…
This skill should be used when the user wants to "deploy with human approval", "verify a deployment approval", "resolve the effective agents-cli deploy plan", or needs a forced-blocking gate before agents-cli deploy. Covers resolving CLI flags + agents-cli-manifest.yaml into a plan, presenting that plan at…
Pay-per-call agent tools over Bitcoin Lightning / USDC (x402), exposed as a remote MCP server. Use BEFORE any irreversible or consequential action (a trade, a destructive command, shipping code, spending funds) to get a capital-scale-aware governance review; for facts-only crypto market intelligence (macro risk…
The agent-to-agent trust handshake. Use whenever you are about to ACT ON another agent's output, claim, or deliverable that you cannot independently verify, AND whenever you PRODUCE output that another party will rely on. Demand a proof on what you receive; attach a proof to what you ship. A proof is a portable…
A prompt-writing guide for creating minimal editorial or zine-style poster images about any subject. It turns a theme, sentence, mood, or brief into a focused image prompt.
A research rulebook for using only information that would have been available at each moment in a historical investment test. A backtest is a simulation of how an investment strategy would have performed in the past.
A method for finding real icons, images, logos, avatars, and empty-state artwork for a website or app. It favors fetched or properly sourced assets over invented SVG shapes, emoji, or unsuitable stock images.
Run a parallel bull/bear adversarial research pipeline on a specific ticker. Use when the user asks for "adversarial research", "bull bear analysis", "deep research on [ticker]", a bull-bear debate on X, or wants a rigorous debate-style investment thesis. (Bare "should I buy X?" belongs to pre-trade-check.) Then…
Monthly rebalance + DCA prompt for the long-term core ETF sleeve only (broad-market index ETFs) - NOT single-stock adds (use cash-deployment) and NOT max-Sharpe reweighting (use optimize-allocation). Use when the user asks "should I rebalance?", "where should I deploy my paycheck?", "DCA recommendation", "is my…
Run a one-shot morning portfolio digest that ties together health, alerts, macro regime, crowding risk, concentration, and earnings calendar into a single decision-ready brief. Use when the user asks for "morning briefing", "daily digest", "what's happening today?", "what changed overnight?", or "give me the morning…
Design, evaluate, and optimize production-grade AI Agent systems using FastAPI, LangChain, LangGraph, LLM orchestration, multi-agent architectures, tool calling, memory, retrieval, and workflow graphs. Use when architecting or reviewing scalable, high-performance AI Agent systems for real-world deployment.
Enter explore mode - a thinking partner for exploring ideas, investigating problems, and clarifying requirements. Use when the user wants to think through something before or during a change.
Design high-performance, scalable, and fault-tolerant backend systems using Python (FastAPI, async/concurrency), real-time architectures, APIs, databases, queues, and caches. Use when designing system architecture, backend services, scalability strategies, or evaluating trade-offs for production-grade systems.
This skill creates disciplined investment retrospectives for public-market equities by starting from abnormal price windows and testing candidate drivers before generating a narrative.
Turn a natural-language daily A-share stock or ETF idea into a typed diePi StrategySpec, obtain missing Tushare data through an already-installed official Skill, validate marketdatav1 inputs, run an auditable backtest, and interpret only verified results.
Stateless OHLC primitives service — candlestick bars in, technical indicators + Smart-Money-Concepts objects out. Single POST / takes a bars array + an indicators selection map and returns computed primitives; GET /metadata is the output-path catalog; GET /health. 67 primitives across trend (SMA/EMA + 15 more MAs…
Use before a backtest result informs an investment discussion, especially for split-buy strategies, to verify point-in-time data, next-bar execution, costs, benchmark parity, train-test separation, hand checks, and explicit failure warnings.
Use when comparing KRX-listed broad-market ETFs or preparing an ETFAnalysisSnapshot for a split-buy strategy, including cost, tracking quality, liquidity, premium or discount, and underlying-index valuation without turning those facts into an order recommendation.
Use for ETF or stock research, screening, thesis review, and evidence collection when every material number must preserve its source, as-of date, available-at time, missing-data state, and contrary evidence before it can inform a decision.
Interpret backtest output from the historicalpriceanalyzer tool — four built-in strategies (SMA crossover, RSI reversal, breakout, mean reversion) over Indian stocks, with Sharpe, max drawdown, win rate, and avg trade. Use when the user asks about "backtest", "how would strategy X have performed", "test this on…
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