agent-system

Run multi-lens hypothesis generation across accounting, flows, networks, microstructure, and causal checks. Use when you need market hypotheses with mechanism, counterparty, and decay. Triggers: alpha squad, fundamentalist, vulture, network-architect, book-physicist, causal-detective, hypothesis generation, mechanism first.

Run systematic bug hunting with spec reconstruction, adversarial validation, and confidence scoring. Use when you want to hunt bugs (not fix them), validate correctness, or run logic-first/code-first investigations. Triggers: bug hunt, spec reconstruction, logic-first, code-first, orchestrator, logic-hunter, cpp-hunter, python-hunter.

Apply opinionated developer personas for architecture decisions, production debugging, language-specific code review, comprehensive reviewer passes, and test strategy. Use when you need an architect plan, devops investigation, Rust/Python/C++ review, grumpy reviewer audit, or tester-driven test plan. Triggers: architect, devops, rust-dev, python-dev, cpp-dev, reviewer, tester, pre-merge review, refactor for maintainability.

Run research orchestration for data quality, factor geometry, hypothesis validation, and incident forensics. Use when you need SHIP/KILL/ITERATE decisions with strict validation. Triggers: mft-strategist, data-sentinel, factor-geometer, skeptic, forensic-auditor, research pipeline, hypothesis validation, post-mortem.

This skill should be used when the user asks about "market microstructure", "exchange mechanics", "order book", "auction", "NBBO", "Reg NMS", "trading venue", "halt", "LULD", "tick size", "maker-taker", "price-time priority", "SIP", "direct feed", "TRF", "wholesaler", "PFOF", "best execution", "trade-through", "ISO", "opening cross", "closing cross", "NOII", "ITCH", "OUCH", or mentions specific exchanges (Nasdaq, NYSE, CME, Binance, SHFE, DCE, CZCE, CFFEX, INE, etc.). For Chinese futures: "CTP", "综合交易平台", "夜盘", "night session", "看穿式监管", "position limits", "持仓限额", queue position in Chinese markets, or Chinese product codes (rb, cu, sc, if, ic, i, j, ta, ma, etc.). Provides hierarchical venue expertise for research and debugging trading systems.

Apply timeless programming wisdom from "97 Things Every Programmer Should Know" when writing, reviewing, or refactoring code. Use for design decisions, code quality checks, professional development guidance, testing strategies, and workflow optimization.

After working on the code, ensure the branch contains only the minimal, idiomatic changes by removing AI-generated slop introduced on this branch.

Search arXiv preprint repository for research papers in physics, mathematics, computer science, quantitative biology, finance, and statistics. Use when finding academic papers, preprints, ML research, scientific publications. Triggers: arxiv, preprint, research paper, academic paper, scientific literature.

Create, list, and load multi-session chain links that capture work context for later continuation. Use when you want to save current progress, resume a project from a prior session, or inspect chain history. Triggers: chain link, chain load, chain list, save context, resume work, continue later, session handoff.

Configure the Claude Code cost/status line plugin that shows session, monthly, total cost, and context usage. Use when a user wants cost tracking, status line setup, or context usage display. Triggers: cost status, status line, show cost, context usage, Claude cost tracking.

Get current date and time in various formats. Use whenever you need the current date, time, timestamps, or formatted datetime values for any purpose (logging, file naming, scheduling, comparisons, etc.)

Use when building Go applications requiring concurrent programming, microservices architecture, or high-performance systems. Invoke for goroutines, channels, Go generics, gRPC integration.

This skill should be used when the user asks about Polars DataFrame library (Apache Arrow) for Python or Rust. Triggers: "polars expressions", "lazy vs eager", "scan_parquet streaming", "convert pandas to polars", "pyspark to polars", "kdb to polars", "group_by_dynamic", "rolling_mean", "polars window functions", "asof join", "polars GPU", "polars parquet", "LazyFrame". Time series: OHLCV resampling, rolling windows, financial data patterns. Performance: native expressions over map_elements, early projection, categorical types, streaming.