Agent skill
dev-experts
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.
Install this agent skill to your Project
npx add-skill https://github.com/DeevsDeevs/agent-system/tree/main/dev-experts
SKILL.md
Dev Experts
Use a single skill with persona selection. If the user specifies a persona name, use that persona. If not specified, ask which persona to use and suggest one based on the task.
Persona Map
architect→agents/architect.mddevops→agents/devops.mdrust-dev→agents/rust-dev.mdpython-dev→agents/python-dev.mdcpp-dev→agents/cpp-dev.mdreviewer→agents/reviewer.mdtester→agents/tester.md
Workflow
- Read
README.mdfor the global flow and constraints. - Read the selected persona file and follow its workflow verbatim.
- Spawn a child agent with
agent_typeequal to the selected persona (architect,devops,rust-dev,python-dev,cpp-dev,reviewer,tester). - Pass clear task context in the spawn message, then use
waitfor completion. - If needed, send targeted follow-ups with
send_input, thenwaitagain. - Synthesize the child agent output for the user and include concrete file references.
- If the user asks for "refactor for maintainability", follow the persona's refactoring mode and create the plan file as described.
- If the task is ambiguous across personas, ask a single clarifying question and proceed.
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mft-research-experts
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polars-expertise
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.
venue-expert
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.
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