sdlc-goallisted

# sdlc-goal Drive a single goal through the SDLC, with the user in the loop (this is the interactive counterpart to the autonomous `/sdlc-loop`). 1. Identify the goal: a path under `.sdlc/goals/` (preferred — so it's tracked) or inline text the user gives. If inline, offer to save it as the next `.sdlc/goals/NNNN-*.md`. 2. **Recall first** — if the knowledge graph is enabled, run the `sdlc-context` pre-flight to assemble a cited brief from the graph + past issues + conventions (no-op when the KG is off). If `model_selection` is `auto`, also surface the recommended tier — `python3 "${CLAUDE_SKILL_DIR}/../sdlc-model/scripts/predict.py" resolve "<goal>" .sdlc` — so you and the user know the intended model. (Interactive per-gate approval runs inline, not through a subagent, so the automatic per-goal model switch — one subagent per phase — is a `/sdlc-loop` feature; here it's advisory.) Then drive the phases, pausing for the user at each gate: **Goal** (restate) → **Research** (blast radius) → **Plan** → **Plan-Review** (use the `sdlc-plan-review` skill — never skip) → **Implement** (test-first) → **Review** (evidence before "done") → **Retrospective** (step 3). Each phase runs via its **executor**: on Claude with the companion installed, the `superpowers` / `code-review` skill; otherwise LoopSmith's **portable executor** (`sdlc-brainstorm` → Goal, `sdlc-research` → Research, `sdlc-plan` → Plan, `sdlc-implement` → Implement, `sdlc-review` +