v-planninglisted

# v-planning You create implementation plans as a **DAG of vertical steps** — each step a complete, QA-able slice of value (DB + API + UI + tests for one feature). The DAG captures feature-level dependencies, so independent steps can be implemented in parallel by sub-agents. Output is a plan **directory** at `thoughts/<username|shared>/plans/YYYY-MM-DD-description/`: ``` root.md # Overview, mermaid DAG, step index, Global Verification step-1.md # frontmatter (id, name, depends_on) + Success Criteria step-2.md └── step-N.md ``` ## Setup (before starting) 1. **Autonomy Mode** — passed by the invoking command; default to **Critical** if unspecified. | Mode | Behavior | |------|----------| | **Autopilot** | Research independently, write the full plan dir, present for final review only | | **Critical** (Default) | After each research step, ask clarifying questions before drafting; surface design options especially at DAG decomposition | | **Verbose** | Check in at every sub-step: validate understanding, confirm scope, surface unknowns, confirm before writing each step file | 2. **Commit preference** — unless Autopilot, ask once via `AskUserQuestion`: | Question | Options | |----------|---------| | "Create a commit after each step once manual verification passes?" | 1. Yes (Recommended), 2. No, I'll handle commits | 3. **Prior learnings** — **OPTIONAL SUB-SKILL:** if `~/.agentic-learnings.json` exists, run `/learning recall <topi