Enumerate unknowns in architecture decisions through structured questioning techniques.
npx skills add https://github.com/avelikiy/great_cto --skill discovery-avelikiy
Please help me install this Agent Skill. Skill: discovery Source: https://github.com/avelikiy/great_cto/tree/main/skills/discovery Command: npx skills add https://github.com/avelikiy/great_cto --skill discovery-avelikiy
This Skill helps in uncovering unknowns and hidden constraints early in the architecture process, leading to more informed decisions and reducing risk.
Use the discovery skill to perform a structured questioning session on the "user experience" feature before designing the interface.
High-intent search queries and answers about installing and using this skill.
To uncover hidden constraints before finalizing software architecture, apply structured questioning techniques to enumerate unknowns early in the decision-making process. This reduces risk by identifying undocumented limitations before locking in design choices.
Structured questioning for architecture decision-making is a technique to surface unknowns and hidden constraints systematically. It helps reviewers identify what data is not yet understood before creating models or security plans.
You should perform a constraints discovery session before locking in design, architecture documentation, security plans, or other critical steps. Running it early reveals unknowns and ensures more informed decisions.
To identify unknown data requirements before creating a data model, use structured questioning to analyze the feature set and document what is not yet understood. This surfaces hidden constraints prior to architecture documentation.
Architecture constraints discovery works for security planning and audits by systematically enumerating unknowns before critical decisions are locked in. It requires analysis and documentation skills to reveal hidden risks.
The limitation of using structured questioning for architecture review is that it requires strong analysis and documentation skills to be effective. It only surfaces unknowns and does not resolve the constraints independently.
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