Ship Playbook

Ship Playbook

Inputs

• $request: The feature prompt — what to plan, build, review, and ship. May carry overrides like harness=codex or golive=yes to seed intake. For a fix round, pass the prior findings as the prompt. To RESUME from an existing, already-reviewed DAG plan, point at it (e.g. resume .ulpi/plans/<name>.md or --plan .ulpi/plans/<name>.json): the run skips planning + plan-review and starts at build.

Goal

Turn one prompt into shipped-quality work the same way every time, by running the delivery playbook as a single runnable Workflow: a grounded DAG plan, an optional founder plan review, an implementation built task-by-task across the DAG layers (each task written and reviewed by the executor the user chose), an optional plan-vs-implementation review, and an optional go-live audit — then it RETURNS the verified findings as feedback. It runs ONE pass and does not loop on its own; if findings remain, the user decides whether to run a fix round.

The 14 steps map to the Workflow phases: step 3 → Plan · steps 4–9 → Plan review (optional, bounded loop) · steps 10–11 → Build (per-task review optional) · step 12 → Impl review (optional, plan-vs-implementation) · step 14 → Verify (dedup + adversarial verify → feedback) · step 13 → Audit (only if goLive AND build+impl verified-clean). The skill does the intake (dependency check + prompt

• gate questions) up front. Each review gate runs at the depth the user chose (skip / native / codex / kiro); there is no automatic recursion — the workflow returns its findings and stops.

Phase 1 — Intake

Step 0 — Decide the MODE: new run vs resume (do this FIRST)

The skill runs in one of two modes — detect which before anything else:

• NEW RUN (default — the user gives a feature prompt). Run the full intake below (dependency check + gate questions + scope grounding), create a FRESH status file, and launch with full args.
• RESUME a previous run (the user says "resume", "continue the build", gives a wf_… runId, or points at an existing .ulpi/workflows/<id>.json). Do NOT re-run intake and do NOT overwrite the status file. Instead, from the repo root run node <skill-dir>/helpers/wf-status.mjs --resume [<runId>] — it reads the run's status file and prints the exact Workflow({ scriptPath, args }) to relaunch, already carrying planPath (skip re-planning), checkpointResume:true (skip tasks already done), and the same statusFile. Launch that verbatim. The durable checkpoint makes resume session-independent (no resumeFromRunId); the build rebuilds only what's left. (If --resume warns that launchArgs is missing — a pre-v1.7.0 run — supply the missing validate/hardRules; run --write first if there's no status file yet.) Then skip to Phase 3 reporting when it returns.

The rest of Phase 1 is the NEW-RUN path.

Step 1 — Dependency check & setup (do this FIRST)

Before anything else, tell the user what would make this skill do its BEST work, what's already here, and what's missing — with copy-paste install commands. ship-playbook composes other skills and routes to specialist agents; the more of these are installed, the better the result.

How to detect — THREE states, not two. A skill is only loaded into your available-skills list (and an agent into your subagent_type options) at Claude STARTUP, so "installed on disk" ≠ "usable this session". Classify each item:

• Ready — in your loaded available-skills list / subagent_type options. Usable now. Don't list it.
• Installed, needs restart — NOT in the loaded list, but present on disk. Check disk symlink-aware (skills register as symlinks into a shared store, e.g. .claude/skills/map-project → ../../.agents/skills/map-project): use ls -laL .claude/skills/<name> or test -e .claude/skills/<name> (follows symlinks) — NOT find -type d (silently misses symlinks). Report these as "installed — RESTART Claude to load", with NO install command (it's already installed).
• Missing — not in the loaded list and not on disk. Show the full install command.

The loaded list is the source of truth for what's USABLE now; the symlink-aware disk check only distinguishes "installed but not loaded (restart)" from "truly missing", so an installed-but-not-yet- loaded skill is never mislabeled plain "missing". Sanity check: if you'd report an obviously-present skill (one you just used) as missing, your method is broken. Disk/PATH probing for the external kiro-cli binary is separate (see below).

Detect the project's stack(s), then check (against those loaded lists) what's present vs missing across:

• Composed skills — plan-to-task-list-with-dag, plan-founder-review, go-live-audit, map-project / map-project-monorepo.
• Specialist agents for this stack — the engineer + reviewer pairs the build would assign. The reviewer name is the FULL engineer name + -reviewer (NOT an abbreviation): e.g. nextjs-senior-engineer + nextjs-senior-engineer-reviewer; go-senior-engineer + go-senior-engineer-reviewer; laravel-senior-engineer + laravel-senior-engineer-reviewer. Use the exact registered names — never shorten to nextjs-reviewer/go-reviewer. Missing ones force general-purpose, which is lower quality.
• Stack skills — /nextjs, /laravel, /rust, … for the detected stack.
• Optional harness tooling (only if the user might pick codex/kiro): the codex plugin (codex:codex-rescue); for kiro, the CLI plus the kiro-review skill (reviewing) and hand-over-to-kiro skill (building). Detecting the kiro CLI — two gotchas:
  • The binary is named kiro-cli, NOT kiro (bare kiro is usually the Kiro IDE symlink, not the CLI). Check kiro-cli.
  • It's commonly in ~/.local/bin, which the sandboxed Bash PATH may NOT include — so command -v kiro-cli can come back empty even when it's installed. Detect with a location-tolerant check, e.g. command -v kiro-cli || ls ~/.local/bin/kiro-cli ~/.kiro/bin/kiro-cli /usr/local/bin/kiro-cli 2>/dev/null, and confirm it runs (kiro-cli --version). Docs: https://kiro.dev/docs/cli.

Present TWO separate tables — one for skills, one for agents — listing only items that are NOT ready (i.e. "missing" OR "installed, needs restart"). Do NOT list ready items at all (no "present / ready" section). Each row shows the item, its state, and the action:

• state = installed, needs restart → action: "Restart Claude to load" (NO install command — it's already on disk).
• state = missing → action: the full, copy-paste install command:
  • skills → npx skills add https://github.com/ulpi-io/skills --skill <name> (composed skills, stack skills, kiro helpers kiro-review/hand-over-to-kiro; kiro-cli itself → its docs link https://kiro.dev/docs/cli);
  • agents → npx agentshq add ulpi-io/agents@<agent-name>, using the EXACT registered name per row — e.g. …@nextjs-senior-engineer and …@nextjs-senior-engineer-reviewer (the reviewer is the full engineer name + -reviewer, never …@nextjs-reviewer).

If a table has no not-ready items, omit it entirely. Then offer two choices with AskUserQuestion:

• Continue now with what's installed (missing specialists fall back to general-purpose; missing harness options simply won't be offered).
• I'll install them — restart : the user installs the listed items, then RESTARTS Claude (newly installed skills/agents are only loaded at startup) and re-runs /ship-playbook. Tell them to come back and re-invoke after restarting.

Record what's available — it feeds availableAgents and constrains which intake options you offer.

Step 2 — The workflow gate questions (ask these FIRST)

The prompt is $request. Ask the SEVEN gate questions (across two AskUserQuestion calls — up to 4 each), in EXECUTION order so they read like the run, unless $request already pins them.

RESUME mode. If $request points at an existing reviewed plan (a .ulpi/plans/<name> path, or the user asks to resume), the run starts at BUILD: skip gate questions 1 (who writes the plan) and 2 (who reviews it) — both are already done — and ask only the remaining five (code writer, code reviewer, impl review, go-live, map). Read the plan's .json and confirm it is well-formed (tasks[] with id / agent / writeScope / validate, and layers[][]) before proceeding; if it is malformed or stale, say so and offer to (re)plan instead of resuming.

These gate questions come FIRST — immediately after the dependency check (Step 1). Do NOT precede them with scope/feature-clarification questions ("full platform or just the API?", "which SSO protocol?", etc.). The prompt IS the scope; if it's broad or ambiguous, you ground it in Step 3 (AFTER these gates) or let the plan phase challenge scope during planning — never with a question round before the gates. The user expects the workflow configuration first.

Every role independently picks its executor (each write and each review is separate — write with codex, review with kiro is fine). Only offer codex/kiro for roles whose tooling Step 1 found installed. Defaults are LIGHT to control token cost; the user can dial each up to full rigor or skip.

Option ordering rule: list native first (mark it Recommended/default), then codex, then kiro, and put skip as the LAST option you provide (it then renders second-to-last, right before the auto-added "Other"). Plan writing and code writing are NOT skippable (they must happen); the four optional gates (plan review, code review, impl review, go-live audit, map) each include skip.

1. Who WRITES the plan — the DAG decomposition: native (plan-to-task-list-with-dag — default), codex, or kiro. Passed as planHarness. (No skip — the plan must be written.)
2. Who REVIEWS the plan — founder review (scope, decomposition, phantom paths): native (default), codex, kiro, or skip. Passed as planReview.
3. Who WRITES the code — every task + its fixes: native (the plan's specialist engineer agents — default), codex, or kiro. Passed as buildHarness. (No skip.)
4. Who REVIEWS the code — each built task in the build loop: native (the matched -reviewer — default), codex, kiro, or skip (no per-task reviewer or fix loop — biggest token save). Passed as taskReview.
5. Implementation review after all tasks — the plan-vs-implementation review: native (default), codex, kiro, or skip. Passed as implReview.
6. Run the go-live audit — run (the go-live audit, only fires if build+impl come back verified-clean) or skip (default). Passed as goLive (run → true).
7. Run map-project at the end — map-project, map-project-monorepo, or skip (default). Detect the repo layout and recommend the matching variant. Held as mapRefresh — this is NOT a Workflow arg (it isn't in the args object); the SKILL runs the chosen map skill itself in Phase 3, after the Workflow returns, on a real (non-aborted) run.

Defaults (light, kept safe): planHarness native, planReview native, buildHarness native, taskReview native, implReview native, goLive skip, map skip. The user can go full swing (every review on, codex/kiro where wanted, go-live on), delegate writing and reviewing to harnesses (any write/review role → codex|kiro — and the writer and reviewer may be DIFFERENT harnesses), or go fast (skip the reviews). Warn (do not block) if BOTH taskReview skip AND implReview skip: nothing then checks the build, so a clean verdict only means the engineer validates passed.

Step 3 — Scope grounding, project facts, git preflight, agent list

Now (AFTER the gate questions) ground the scope. Read the repo to understand what exists. If $request is broad or ambiguous (e.g. "a self-hostable SaaS platform with SSO"), narrow it HERE: prefer inferring scope from the repo, and only ask focused scope questions if you genuinely cannot proceed — or pass the broad prompt through and let the plan phase challenge scope. Fold the resolved scope into the prompt you pass in args.

Gather the facts the Workflow needs (do not ask the user — read the repo): root (absolute repo path), workingBranch (never build on a protected branch without confirmation), validate (the workspace typecheck+lint+test command), and hardRules (the load-bearing invariants from root CLAUDE.md / the spec).

Verify root is a git work tree — git -C <root> rev-parse --is-inside-work-tree must print true, and workingBranch must exist with at least one commit. The build creates and merges task branches, so a non-git folder (or a branch with no commit) cannot be built. If root is not a git repo, STOP and tell the user — offer git init + a baseline commit, or correct the path — and do not launch.

Pass availableAgents (the specialist engineer + -reviewer names that exist here, from Step 1) and allowGeneralFallback (true only if the user chose Continue with gaps) into the Workflow args. The plan then assigns ONLY agents from that list (it can't invent one that isn't installed); the Workflow returns missingAgents for anything that still slips through. Never silently substitute general-purpose for a missing specialist without the user having seen the gap in Step 1.

When RESUMING from an existing plan, also resolve the plan here: read .ulpi/plans/<name>.json (the .md renders from it), validate the DAG shape (tasks[] with id / agent / writeScope / validate, acyclic layers[][]), and pass planPath (the path) — or the parsed plan object — in args. Do NOT re-plan. The Workflow loads/validates it and skips both the plan and plan-review phases. If the plan is missing or malformed, stop and offer to (re)plan instead.

Open a master TodoWrite mirroring the phases in references/playbook-state.md.

Success criteria: dependency status was shown and the user chose continue-or-restart; planHarness, planReview, buildHarness, taskReview, implReview, goLive, mapRefresh, root (a confirmed git work tree), workingBranch, validate, hardRules, and availableAgents (+ allowGeneralFallback if gaps) are all resolved.

Phase 2 — Run the playbook Workflow (steps 3–14)

If goLive == yes, FIRST author the go-live audit so step 13 composes the proven audit rather than a thin pass: run the go-live-audit skill to generate the project-tailored audit workflow and capture the scriptPath the Workflow tool persists for it; pass that path in as auditScriptPath. (If you skip this, step 13 falls back to an inline finder pass.)

First, create the live status file (the Workflow sandbox has no filesystem access, so the SKILL must create it). Pick a workflowId — ship-<UTC timestamp>-<short-slug-of-the-prompt> (e.g. via Bash date -u +%Y%m%dT%H%M%SZ) — set statusFile = <root>/.ulpi/workflows/<workflowId>.json (ABSOLUTE), and Write the initial document so a watcher sees the run the instant it launches.

RESUME — do NOT clobber an existing status file. The build now does CHECKPOINT RESUME: it reads the status file and SKIPS every task already marked done (passed/integrated/reviewing/fixing/blocked), rebuilding only the rest. So when resuming a prior run, REUSE its existing <root>/.ulpi/workflows/<id>.json (pass that same workflowId/statusFile) — do NOT overwrite it with a fresh all-pending document, or the checkpoint is lost and everything rebuilds. Only Write the initial document for a brand-NEW run.

{ "schemaVersion": 1, "workflowId": "<id>", "skill": "ship-playbook", "status": "initializing",
  "prompt": "<prompt>", "root": "<root>", "workingBranch": "<branch>", "createdAt": "<UTC now>",
  "config": { "planHarness": "...", "planReview": "...", "buildHarness": "...", "taskReview": "...",
              "implReview": "...", "goLive": false },
  "plan": null,
  "phases": { "plan": {"status":"pending"}, "plan_review": {"status":"pending"},
              "build": {"status":"pending"}, "impl_review": {"status":"pending"},
              "verify": {"status":"pending"}, "audit": {"status":"pending"} },
  "tasks": {}, "openRegister": [], "result": null }

Then launch references/workflow-template.js via the Workflow tool, passing intake as args:

Workflow({ scriptPath: ".../references/workflow-template.js",
           args: { prompt, root, workingBranch, validate, hardRules, goLive,
                   planHarness, planReview, buildHarness, taskReview, implReview,
                   auditScriptPath, availableAgents, allowGeneralFallback, warmWorktree,
                   planPath, kiroModel,
                   workflowId, statusFile, trackStatus, checkpointResume } })   // planPath → RESUME at build;
                                                              // workflowId/statusFile → live .ulpi/workflows/<id>.json
                                                              // (trackStatus:false disables); checkpointResume:false →
                                                              // force a full rebuild (default true: skip done tasks);
                                                              // warmWorktree:false → plain per-worktree install
                                                              // (default true: CoW-seed node_modules/vendor/Pods; Rust uses kache or CoW-seeds target/)

After launch, stamp the run id AND the full launch args. The Workflow tool returns a runId (wf_…) immediately (it runs in the background). Write runId, status:"running", and — critically — the COMPLETE launchArgs (the exact args object you just passed: prompt, root, workingBranch, validate, hardRules, all harnesses, goLive, …) into the status file via Bash+jq: jq --argjson la '<the args object>' '. + {runId:"<runId>", status:"running", launchArgs:$la}' This makes the status file a self-describing, deterministic resume source — wf-status.mjs --resume reads launchArgs back verbatim so a resume re-fires the identical config (no hand-assembly, no drift).

Resuming a previous run? Use wf-status.mjs --resume — do NOT hand-assemble args. From the repo root: node <skill-dir>/helpers/wf-status.mjs --resume [<runId>] reads the run's status file and prints the exact Workflow({ scriptPath, args }) to relaunch — already carrying planPath (skip re-planning), checkpointResume:true (skip tasks already done), and the same statusFile. Launch that verbatim. The durable status-file checkpoint makes resume session-independent — no resumeFromRunId needed. (If the run predates v1.7.0 / has no launchArgs, --resume warns and you supply the missing validate/hardRules; --write [<runId>] first backfills a status file from the journal.)

mapRefresh is deliberately NOT in args — it's the only intake answer the Workflow doesn't run. The map refresh regenerates CLAUDE.md from the FINISHED code, so the skill runs it itself in Phase 3 after the Workflow returns (see Q7). All other gate answers go in args above.

Pass args as a real JSON object, NOT a JSON-encoded string. A stringified blob reaches the script as one string, fails its typeof args === 'object' check, and every input silently falls to a FILL: placeholder. The script hard-THROWS on that instead of returning a fake converged:true, so a stringified-args launch errors loudly — if you hit it, relaunch as a FRESH run (no resume) with args as an object. (Each role arg coerces to a safe default if invalid, so a typo degrades gracefully.)

The Workflow then executes the playbook in one pass, running each gate at the level the user chose:

• Plan (step 3) — the planner (per planHarness: native / codex / kiro) follows the plan-to-task-list-with-dag methodology unattended (mode auto-selected), grounds every path in the real repo, assigns a specialist engineer + -reviewer + stack skill to each task, writes .ulpi/plans/<name>.md+.json, returns {tasks, layers}. RESUME: when planPath/plan is supplied, this phase instead LOADS that already-reviewed plan (an agent reads + validates + normalizes it; no re-planning) and plan review is skipped — the run resumes at build.
• Plan review (steps 4–9) — reviewer per planReview (skip / native / codex / kiro). ONE bounded loop → fix the plan (JSON-first, re-render MD; fix is always native) → re-review; exits on no BLOCK/CONCERN (OBSERVATIONs never block) OR non-convergence, capped at MAX_REVIEW (2).
• Build (steps 10–11) — walk the DAG layers; per task: engineer (worktree, task branch) → in-workflow integrate agent (git merge onto the working branch, removing each merged worktree as it goes) → reviewer (unless taskReview skip) → bounded fix loop until it passes; barrier between layers. Each fresh worktree is provisioned fast (warmWorktree, default on): a one-time warm step (overlapping planning) primes caches, then engineers CoW-clone node_modules/vendor/Pods from the primary checkout when the lockfile is unchanged (Rust shares crate compilation via kache — a path-independent, hardlink-based rustc-wrapper cache wired in .cargo/config.toml, so worktrees restore compiled crates instead of cloning target/; when kache is absent it CoW-seeds the warm target/ instead), falling back to a normal frozen install; warmWorktree:false restores a plain per-worktree install. Engineer routes per buildHarness; reviewer per taskReview — and the two are INDEPENDENT (write codex, review kiro is fine). The build and verify fan-outs run behind concurrency gates so a wide DAG layer or a long findings list can't trip Claude's API rate limits: at most MAX_BUILD_PARALLEL (4) worktree engineers and MAX_PARALLEL (6) reviewers/verifiers run at once. Total agent count is unchanged — only how many run simultaneously is bounded. Tune those two constants in references/workflow-template.js if you hit 429s (lower) or have a high-limit account (raise); never set them to 1–2. If an agent is still rate-limited despite the caps (returns empty / cut off mid-flight), it is retried with exponential backoff (RETRY_DELAYS, up to 4 attempts) before being recorded as blocked — so a rate-limit storm no longer turns into false "blocked task" noise.
• Impl review (step 12) — reviewer per implReview (skip / native / codex / kiro). The plan-vs-implementation review of everything built.
• Verify (step 14) — dedup + adversarially verify the build+impl findings. These become the returned openRegister — the feedback. No automatic re-plan/re-build; the workflow returns and stops.
• Audit (step 13) — runs only when goLive AND build+impl come back verified-clean: COMPOSE the proven go-live-audit workflow inline via the workflow() hook (auditScriptPath) — gates → finders → dedup → dual-lens verify → critic — ∥ a second-harness audit lane; its findings become openRegister.

Watch progress three ways: the /workflows panel (live agent tree), the status file (cat <root>/.ulpi/workflows/<id>.json — overall status, per-phase, per-task), or the bundled reader node <skill-dir>/helpers/wf-status.mjs (reconstructs per-task status straight from the run's journal — works even mid-flight and even if status tracking is off). See references/status-tracking.md. To iterate on the script, edit the saved scriptPath the tool returns and re-invoke with {scriptPath} (and resumeFromRunId to reuse cached agent results). Whenever you pass resumeFromRunId, re-pass the SAME args object — it reuses cached agent results but the script re-executes from the top, so omitting args empties CFG and the script hard-throws on the FILL: guard. Always include the full args object you launched with (including workflowId/statusFile). To RESUME a prior run (not iterate on the script), use wf-status.mjs --resume instead — see the resume verb below; it carries the full args for you.

Success criteria: The Workflow runs to completion and returns { converged, ranReal, plan, planSupplied, build, openRegister, missingAgents, reviewConfig, noReviewGate, planReviewRan, implReviewRan, taskReviewDowngraded, auditRan, workspaceValidatePassed, endStateUngated, blockedTaskCount, workflowId, statusFile }.

Phase 3 — Report and escalate

Read the Workflow result:

• First, confirm the run is real — not a false-clean. If the result has ranReal: false (or an aborted message), the inputs never reached the script (or a preflight failed). Report that failure and relaunch (fresh run) with args as a real JSON object; do NOT treat converged as meaningful.
• If missingAgents is non-empty, some tasks ran on general-purpose because the assigned specialist isn't installed here. Surface the list (which agents, how to install) so the user can decide whether to install them and re-run for higher-quality output.
• If noReviewGate: true (the user skipped BOTH per-task review and impl review), CAVEAT any clean verdict: it only means the engineer validates passed, nothing reviewed the build. Report reviewConfig so the user sees which gates ran.
• Gate honesty — a configured gate that did NOT actually run is never "clean". The Workflow already keeps openRegister non-empty (so converged is false) when a gate died, but report the cause so the user knows WHY: planReviewRan === false / implReviewRan === false → the configured plan/impl reviewer couldn't run (e.g. kiro CLI absent); taskReviewDowngraded non-null → the requested per-task reviewer (e.g. codex) couldn't run here and was downgraded to native (it shows {requested, ranAs}) — the tasks WERE reviewed (natively), but tell the user their requested reviewer didn't run; auditRan === false → the go-live audit died (launch NOT confirmed); workspaceValidatePassed === false → the final validate on the integrated tree is RED (it does not typecheck/lint/test — the most load-bearing blocker). endStateUngated === true (impl review skipped) → CAVEAT that the whole-codebase semantic end-state was never gated even if the tree compiles.
• blockedTaskCount > 0 → that many tasks did not pass (engineer-failed, review-blocked, or dep_blocked because an upstream dependency never integrated — a blocked on dependency <X> reason points at the ROOT). These are in openRegister; surface them with their reasons.
• Pre-existing-failure attribution. A build[] entry may carry a preexistingNote — its slice is correct and was integrated, but its validate was red ONLY from pre-existing / out-of-scope failures it doesn't own (the build no longer discards such correct work; the engineer self-classifies new-vs-pre-existing against the base). And when workspaceValidatePassed === false, the workspace-validate marker now distinguishes failures INTRODUCED by this run (the real blockers) from ones PRE-EXISTING on the base (need a separate owning task — not caused by this run), with a per-step [steps: typecheck=pass, lint=FAIL, …] breakdown. Surface this split so the user fixes the right thing and a green-slice build whose tree is red from inherited breakage is read correctly (work preserved + real cause named), not as "the build broke it."
• If planSupplied: true, the run RESUMED from a pre-reviewed plan: planning and plan-review were skipped by design — say so, so a clean verdict isn't misread as "the plan went unreviewed."
• converged: true (real run, openRegister empty) → DONE. Report the build outcome per task, the review/audit verdicts (per reviewConfig), and where the plan landed.
• openRegister non-empty → PRESENT the feedback and let the user decide. List the verified BLOCK/CONCERN findings (file:line, issue, suggested fix, which gate found them). Then offer the next move: run a fix round (re-invoke the workflow with the findings as the prompt — same intake), hand-fix, or accept-with-risk. The workflow does not loop on its own; never represent open findings as clean.

The Workflow already wrote the final state into <root>/.ulpi/workflows/<id>.json (status = done/needs_fix/aborted, per-task outcome, openRegister). Read it to enrich the report and tell the user where it lives — it is the durable record of this run. If a run died mid-flight (no final write), refresh the file from the journal with node <skill-dir>/helpers/wf-status.mjs --write before reporting.

Live status, stop & resume — three verbs, all backed by the status file + run journal:

• status → cat <root>/.ulpi/workflows/<id>.json (or node <skill-dir>/helpers/wf-status.mjs) — at a glance: overall status, which phase, and each task's state (pending → in_progress → dev_done → integrated → passed/blocked).
• stop → TaskStop the run, or the /workflows panel. Nothing is lost — the journal caches every finished agent.
• resume → from the repo root run node <skill-dir>/helpers/wf-status.mjs --resume [<runId>] and launch the Workflow({ scriptPath, args }) it prints verbatim. It re-fires the run's stored launchArgs with planPath (skip re-planning), checkpointResume:true (skip work already done), and the same statusFile — a FRESH, session-independent run that carries the full args. This is the canonical resume path. Do NOT resume with resumeFromRunId alone: it reuses cached agent results but the script re-executes from the top, and on a new session args is dropped → CFG empties → the script hard-throws on the FILL: guard (in older versions it ran a fake-clean pass that did nothing). Only use resumeFromRunId while iterating on the script to reuse cache, and then you MUST still pass the SAME full args object.

A run launched before v1.5.0 (no status file)? Backfill one from its journal: node <skill-dir>/helpers/wf-status.mjs --write [<runId>] — recovers the plan, branch, task list + status, and conflicts. The journal has no launch args, so add --args '{…gate config + validate…}' (which only the launching session knows) to complete the resume recipe. See references/status-tracking.md.

Then, if the user chose a project-map refresh at intake AND the run was real (ranReal, not aborted), run it last — invoke the chosen skill (map-project or map-project-monorepo) so the CLAUDE.md context map reflects the code the build just landed. Skip it on an aborted/false-clean run (there's nothing new to map). This is the final step, after reporting.

Success criteria: Either the enabled gates are genuinely clean (caveated by reviewConfig / noReviewGate), or the user is handed an honest list of what still blocks plus next moves; the durable status file reflects the final state; and the project map is refreshed if requested.

Guardrails

• Do not run proactively; this is explicit-user-only (it spawns many agents across rounds).
• The workflow runs ONE pass and never loops on its own; a fix round is a deliberate user choice (re-invoke with the findings as the prompt). Review gates are user-selected per run — honor the user's planReview/taskReview/implReview choices, and warn (don't block) when both per-task and impl review are skipped. The Workflow owns steps 3–14; the skill owns intake (dependency check + questions) and the Phase-3 report.
• Do not hand-roll the plan — the Workflow's plan phase follows the plan-to-task-list-with-dag methodology and assigns a specialist agent per task.
• The build assigns the closest AVAILABLE specialist per task; fall back to general-purpose only with the user's consent after notifying them a specialist is missing (never silently). When a stack skill is installed, the engineer MUST use it (/nextjs, /laravel, /rust, …).
• Never fabricate a clean verdict — open BLOCK/CONCERN findings are returned as feedback, not hidden.
• The workflow runs ONE pass and never loops on its own; a fix round is a deliberate user choice (re-invoke with the findings as the prompt). Do not re-introduce autonomous recursion.
• Do not pass secrets/tokens into any agent brief; reference by location, redact values.
• Do not build on a protected branch without explicit confirmation of workingBranch.
• Do not launch the build in a non-git folder or an empty repo — the build creates and merges task branches, so it requires a git work tree with a committed workingBranch.
• Keep build worktrees from poisoning the gate: the workflow prunes its .claude/worktrees/ build checkouts (at preflight, after each integrate, and at end), and the integrate validate must never scan .claude/worktrees/** or sibling agent dirs. If a run's gate fails on files outside the task's scope, suspect leftover worktrees before suspecting the code.
• Follow the DAG; never build a task before its dependencies are integrated. The build integrates layer-by-layer with a barrier, so correctness depends on the PLAN ordering tasks properly: every task's dependsOn must be complete and layers must be a topological o

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