Decide Fit First

• Core job: 量化研究（因子与 Alpha 框架） 面向研究流程与方法论，不替代实盘交易执行与合规审查；涉及具体标的或策略时须提示回测与实盘的差异及监管要求。 设计或评估 因子 / 特征：价值、动量、质量、低波动、另类数据等 数据层：复权、停牌、财报发布日、幸存者偏差…
• Best fit: Use it when the task has reusable inputs, steps, and validation criteria rather than a one-off answer.
• Avoid forcing it: If the source lacks commands, platform support, or external-service evidence, keep those fields unknown instead of guessing.

Design Intent

• Structure: The skill is organized around “何时启用”, “研究流程”, “输出要求”, “质量检查清单”, showing how the author expects the agent to judge fit, collect context, and produce verifiable output.
• Trigger evidence: Prioritize the author’s wording around when to use it, what context to collect, and what output shape to produce.
• Evidence boundary: Author text states facts, repository files prove commands and paths, and Fluxly only adds fit, limits, and usage judgment.

How To Use It

• Inputs: Provide target material, scope, expected result, forbidden changes, and validation method.
• Invocation: Name quantitative-research directly; if the source includes slash commands, start with the command and then add task context.
• Validation: Start small and check whether the result follows “何时启用 / 研究流程 / 输出要求” before expanding.

Boundaries And Review

• Dependencies: It usually needs no extra API key, so start with a small validation task.
• Permissions: Declared permissions include read / write; ask the agent to state file, command, and rollback boundaries before acting.
• Quality bar: A useful result names the deliverable, evidence, and next action. Generic prose means the task needs tighter context.