alpha-squad/SKILL.md
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.
npx skillsauth add deevsdeevs/agent-system alpha-squadInstall this skill globally with one command. Works with Claude Code, Cursor, and Windsurf.
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Use this skill when the user wants market hypotheses generated from complementary lenses.
fundamentalist -> agents/fundamentalist.mdvulture -> agents/vulture.mdnetwork-architect -> agents/network-architect.mdbook-physicist -> agents/book-physicist.mdcausal-detective -> agents/causal-detective.mdREADME.md and enforce mechanism-first reasoning.agent_type and task context.wait to gather results, then synthesize a single hypothesis slate.causal-detective before presenting final output.development
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.
development
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.
testing
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.
development
Use when building Go applications requiring concurrent programming, microservices architecture, or high-performance systems. Invoke for goroutines, channels, Go generics, gRPC integration.