This skill should be used at Phase 3 of deep-work to execute slice-based TDD (RED → GREEN → REFACTOR) for each approved plan slice. Dispatches in solo (inline) or team (implement-slice-worker subagent delegation by cluster_id) mode, runs computational sensors (lint/typecheck/coverage), performs 2-stage slice review (delegate reviewer + evaluator_model), and emits M3-envelope-wrapped receipts/SLICE-*.json via hooks/scripts/wrap-receipt-envelope.js. Triggered by 'implement phase', '구현 시작', '/deep-work continue', /deep-implement slash, cross-platform Skill({ skill: "deep-work:deep-implement", args: "..." }), or orchestrator dispatch after plan approval.
This skill should be used at Phase 2 of deep-work, after research.md approval, to design a detailed implementation plan with TDD slices. Decomposes work into SLICE-NNN units with `depends_on` DAG, acceptance contracts (`failing_test`, `acceptance_threshold`), and optional `cluster_id` hint for parallel-safe grouping. Emits plan.md with the inline slice DAG (Implement Phase's deep-implement skill parses it for worker fan-out — no external slices.md/slice-graph.json is emitted). Triggered by 'create implementation plan', '계획 수립', /deep-plan slash, cross-platform Skill({ skill: "deep-work:deep-plan", args: "..." }), or orchestrator dispatch after research approval.
Author the executable spec contract for deep-work research sessions. Invoked through /deep-spec, $deep-work:deep-spec, or orchestrator dispatch.
This skill should be used when the user invokes /deep-work "task", uses cross-platform Skill({ skill: "deep-work:deep-work-orchestrator", args: "task" }), asks to start a new deep-work session, or requests evidence-driven workflow auto-flow across Brainstorm → Research → Plan → Implement → Test phases. Handles session initialization (profile v3 load, capability detection, session-recommender sub-agent, AskUserQuestion 4-key ask, flag parsing) and dispatches the 5-phase pipeline with Exit Gates between each phase.
Use when the user finishes a deep-work session — merging, opening a PR, keeping the branch as-is, or discarding. Triggers on `/deep-finish`, "finish session", "wrap up session", "세션 마무리", "세션 종료", "PR 만들어줘", or orchestrator auto-call after Phase 5 (Integrate) completes. Emits an M3-envelope-wrapped `session-receipt.json` (and optionally a cross-plugin `handoff.json`). Supports `--skip-integrate` (Phase 5 bypass), `--handoff-to=<plugin>` / `--no-handoff` (post-finish handoff control).
Use when the user manually requests a deep-work phase document review. Parses --phase, --structural, and --adversarial compatibility arguments, then enters the canonical adaptive review protocol.
Use when the user wants to generate or view the comprehensive deep-work session report — session lifecycle, slice summary, evidence trail, TDD compliance, sensor pass-rate, model usage, evaluation outcomes. Triggers on `/deep-report`, `/deep-status --report`, "session report", "deep-work report", "세션 리포트", "세션 보고서", "리포트 생성". Writes to `$WORK_DIR/report.md` and prints inline summary. Sub-page of the deep-status hub.
This skill should be used during deep-work Phase 1 to research an existing codebase (architecture/patterns/risks) via research-codebase-worker, or to investigate a zero-base project's tech stack/conventions/data-model via research-zerobase-worker (using WebSearch + Context7 for up-to-date library docs). Consumes evolve-insights and harnessability M3 envelopes as context. Triggered by 'start research phase', 'analyze codebase', /deep-research slash, cross-platform Skill({ skill: "deep-work:deep-research", args: "..." }), or orchestrator dispatch after brainstorm approval. Solo/Team mode automatic based on project size.