update-planning
The `update-planning` command synchronizes implementation progress with planning documentation by gathering current status, reviewing existing task breakdowns, and reconciling completed work against planned milestones. Use this command when development has advanced since the last planning update, blockers have emerged, or scope has shifted, ensuring planning docs remain accurate guides for ongoing and future work.
mkdir -p ~/.claude/commands && curl -fsSL https://raw.githubusercontent.com/codeaholicguy/ai-devkit/HEAD/commands/update-planning.md -o ~/.claude/commands/update-planning.mdupdate-planning.md
Help me reconcile current implementation progress with the planning documentation.
1. **Gather Context** — If not already provided, ask for: feature/branch name and brief status, tasks completed since last update, new tasks discovered, blockers/risks, and planning doc path (default: latest matching `docs/ai/planning/YYYY-MM-DD-feature-{name}.md`; fallback `docs/ai/planning/feature-{name}.md`).
2. **Use Memory for Context** — Search memory for prior decisions that affect priorities/scope: `npx ai-devkit@latest memory search --query "<feature planning updates>"`.
3. **Review & Reconcile** — Summarize existing milestones, task breakdowns, and dependencies from the planning doc. For each planned task: mark status (done / in progress / blocked / not started), note scope changes, record blockers, identify skipped or added tasks.
4. **Produce Updated Task List** — Generate an updated checklist grouped by: Done, In Progress, Blocked, Newly Discovered Work — with short notes per task.
5. **Store Reusable Knowledge** — If new planning conventions or risk-handling rules emerge, store them with `npx ai-devkit@latest memory store ...`.
6. **Next Steps & Summary** — Suggest the next 2-3 actionable tasks and prepare a summary paragraph for the planning doc.
7. **Next Command Guidance** — Return to `/execute-plan` for remaining work. When all implementation tasks are complete, run `/check-implementation`.AI DevKit · Compare implementation with design and requirements docs to ensure alignment.
AI DevKit · Pre-push code review against design docs.
AI DevKit · Execute a feature plan task by task.
AI DevKit · Scaffold feature documentation from requirements through planning.
AI DevKit · Store reusable guidance in the knowledge memory service.
AI DevKit · Review feature design for completeness.
AI DevKit · Review feature requirements for completeness.
AI DevKit · Add tests for a new feature.