Structured divergent/convergent thinking to turn vague ideas into concrete proposals. Use when you have a rough concept that needs exploration before committing to a spec.
npx claudepluginhub v1truv1us/ai-eng-system --plugin ai-eng-learningThis skill uses the workspace's default tool permissions.
Turn vague product ideas or technical concepts into concrete, evaluable proposals through structured divergent and convergent thinking. This skill runs before `spec-driven-development` when the problem space is still ambiguous.
Creates isolated Git worktrees for feature branches with prioritized directory selection, gitignore safety checks, auto project setup for Node/Python/Rust/Go, and baseline verification.
Executes implementation plans in current session by dispatching fresh subagents per independent task, with two-stage reviews: spec compliance then code quality.
Dispatches parallel agents to independently tackle 2+ tasks like separate test failures or subsystems without shared state or dependencies.
Turn vague product ideas or technical concepts into concrete, evaluable proposals through structured divergent and convergent thinking. This skill runs before spec-driven-development when the problem space is still ambiguous.
State the problem clearly:
Generate multiple approaches without judgment:
Score each approach against:
Write a concise proposal covering:
| Rationalization | Reality |
|---|---|
| "The first idea is usually fine" | First ideas tend to be the most obvious, not the most effective. |
| "We can refine later" | Later refinement is more expensive than early exploration. |
| "This is too small for structured thinking" | Even small features benefit from a minute of structured evaluation. |