kautopilot

name	kautopilot
description	Drive the kautopilot binary as a thin in-session controller: ticket/free-form request → merge-ready PRs across one or more repos, as ONE flat session. The binary owns all state, prompts, and next-step decisions; this skill just runs what `kautopilot next` yields. Use when running /kautopilot.
argument-hint	[TICKET_ID | "free-form request" | --org liftoff|atomicloud | --diff brainstorm|triage|spec|plan[:<repo>]|feedback | --session ID]

kautopilot — Thin Controller

This skill is a thin driver. It holds no dispatch tables and no prompts — the kautopilot binary owns the state machine, the WAL, every step prompt, and the decision of what's next. The skill's only job: ask the binary for the next step, run it (inline if interactive, isolated sub-agent if not), and report completion. Detection is YOURS: the binary does NOT watch CI, checks, or review threads — you do that yourself while babysitting PRs during execution.

kautopilot is one flat session (= a ticket) that may touch several repos. Repos are a detail, not a separate concept. Full contract: /Users/erng/.config/home-manager/modules/kautopilot-ts/CLI-CONTRACT.md and …/SPEC-kautopilot.md; this file is controller behavior only.

Supporting files (same folder as this skill): visual.md — the full HTML-infographic design brief; links-table.md — the exact end-of-message links-table spec; relay.md — the deferred-writer relay loop (used when a descriptor carries execution: "deferred").

The loop

loop:
  d = json(`kautopilot next --json`)
  if d.done:                 # see "Reading `done`" — NOT always session-complete
      handle(d); break/continue accordingly
  if d.execution == "deferred":   # deferred writer step — do NOT run d.prompt
      follow relay.md VERBATIM: drive turns with `kautopilot relay` (parked in
      the background), present each envelope, complete after approval. The
      reviewer fan-out, visuals, spikes, and `revise` are the WRITER's job in
      this mode — never yours. Deferred mode needs **NO context reset** — the
      writer session holds the heavy context, so the main session stays lean;
      just continue the loop after the relay approval flow completes.
  elif d.kind == "interactive":
      run d.prompt INLINE; for WRITER steps run the per-revision loop below
      (reviewers → `kautopilot revise` to mint+present each version → user feedback)
  else:  # d.kind == "agent"
      run d.prompt in a FRESH context that writes d.contract.outputFile (see "By harness")
  kautopilot complete [--output d.contract.outputFile] [--metadata {…}]
      # --output ONLY when the contract HAS an outputFile (feedback_check has none)
      # feedback_check REQUIRES --metadata '{"choice":"feedback"}' or '{"choice":"done"}'
  if d.kind == "interactive" and the step was a WRITER (an approval gate):
      STOP the turn and hand the user the context reset (see "Context reset at
      every approval gate") — do NOT loop straight into the next `next`.
  else:
      continue the loop.

Push a notification EVERY time you need the user (hard rule)

kautopilot sessions run long and the user steps away (often to their phone). Whenever the session transitions to WAITING ON THE USER — for anything at all — send a push notification (Claude: the PushNotification tool; Codex: whatever notify mechanism the harness offers, else skip) in the SAME turn you present the ask. One line, lead with what they must do. This includes (not exhaustive — the rule is "any human input or human-relevant milestone"):

• a relay envelope lands with questions or a new version to review/approve (e.g. spec v3 ready — 2 questions)
• an inline writer version is presented for review/approval
• triage repo/path/branch confirmation, metadata confirmation, feedback_check
• a kloop run finishes (completed OR conflict/failed — e.g. kloop api/plan-1 done — commit next / kloop conflict in web/plan-2 — needs your call)
• a conflict or decision comes back from any sub-agent/driver
• PR babysitting hits a problem you can't fix (blocked CI, human-review thread, permissions) or a PR reaches ready-to-merge in manual mode
• a merge/release gate waits on the user; feedback is requested
• any error/remediation choice (e.g. deferred-writer failure options)

Don't push for things that need nothing from them (routine progress, a step you immediately continue past). If in doubt whether they're waiting on you or you're waiting on them — if it's the latter, push.

How to run a fresh-context step/reviewer — kteam first

The binary loop above is harness-agnostic. Default to kteam for every fresh-context run (agent-steps, reviewer fan-out): each is a detached kteam start session on an auto-mode fleet wrapper, prompted to write d.contract.outputFile and kteam signal done. Pick wrappers with kteam recommend (usage-aware); fan out reviewers as parallel kteam sessions and park on kteam wait <id> --timeout .... This keeps the main thread lean, survives harness restarts, and gets kteamd's auth/quota preflight and stall/login-wall fail-fast for free.

Fall back to a native subagent (Task/Agent on Claude; delegated native subagent on Codex) only when kteamd is unavailable or the step is too small to justify a session (single quick read/summarize). Interactive (d.kind == "interactive") steps run inline either way.

Wherever this doc names a Claude-only tool, translate:

• "spawn a Task/Agent/Explore subagent" = start a fresh-context run — a detached kteam session by default (see above); Task/Agent on Claude or a delegated native subagent on Codex as the fallback.
• "AskUserQuestion" = Claude's structured question tool. On Codex: ask inline as a plain numbered question in the chat and wait for the user's reply.
• "arm a Monitor" = Claude's background watcher. On Codex: delegate a cheap, fast subagent that blocks on the command and returns its final line (see "Running kloop for a ready plan").

The binary owns the sequence — you never track it

Do NOT name the step on complete: omit it and the binary completes whatever step is actually pending (the WAL cursor is the source of truth). Do not remember "what step I'm on", infer the next step, or skip ahead — that is exactly how the loop corrupts itself. The ONLY way to learn the current step is kautopilot next; the ONLY way to advance is kautopilot complete.

You may still pass the step name as an assertion (e.g. complete write_spec) if you want the binary to confirm you're where you think — but a mismatch is an error, not an override. Step names are NOT artifact names. The completable step names are: brainstorm, create_ticket (ad-hoc only), fetch_ticket, triage, write_spec, write_master_plan, write_plans, feedback_check, feedback. (resolve_org and finalize_plans are internal code steps that never yield.) So it's complete write_spec, never complete spec.

Do whatever next says. The descriptor's prompt is fully resolved (paths substituted). next runs the binary's internal code steps inline and returns the next interactive/agent step or a done shape; there is no pending. If the session dies, or you lose track, or a complete comes back with ok:false/stale step, STOP and call next again — it returns the exact pending step until its completionEvent is logged. Re-sync from next; never guess.

Session lock: if a command exits 1 with Session <id> is busy (PID <n>), another kautopilot invocation holds the session lock. Don't delete anything — wait for it to finish and re-run. A stale lock (dead PID, or heartbeat older than the TTL) auto-cleans on the next command, so a crash never wedges the session; just retry after a moment.

Context reset at every approval gate (REQUIRED)

After you kautopilot complete an interactive writer step (triage, write_spec, write_master_plan, write_plans, feedback — anything the user explicitly **"approve"**d), do NOT loop straight into the next next. STOP the turn and hand the user a context reset — every single approval gate, no exceptions. Post exactly this (substitute the real session id):

✅ Approved & recorded. To keep context lean for the next phase, run:

/clear
/kautopilot --session <id>

Then end the turn. Re-invoking with --session <id> re-enters this loop fresh and drives kautopilot next --session <id>, which resumes at the exact pending step.

Why this is safe (lossless). All state lives on disk (the WAL + revisions/) and every step's prompt re-reads what it needs as file paths (ticket, latest triage, approved artifact). The conversation carries nothing the next step needs — keeping it only burns tokens and rots context; clearing between gates loses nothing.

Always print the explicit --session <id> — never rely on bare continue/cwd: one folder can host several sessions, so the id is the only reliable anchor across a /clear.

Make sure the approved decisions are in the artifact, not just the chat. Before you complete, confirm the agreed direction + open-items/assumptions are written into the artifact file (the writer prompt already requires this) — anything that lived only in the conversation is gone after /clear.

(Agent steps, the code steps, the DAG schedule/record loop, and deferred writer steps do not stop for a reset — only the inline interactive approval gates do. Deferred mode keeps the main session lean by construction — the writer holds the heavy context — so its approval gates need no /clear + resume.)

Reading done — a {done:true} is not always "finished"

next returns either a step descriptor or {done:true, phase, reason}. Branch on phase:

• bare next → phase:"execution" = the plan→DAG handoff. The master plan is approved; now drive the DAG with kautopilot schedule/record (see "Driving the DAG"). The reason string includes the current frontier. Do not stop and do not try repo-scoped next — that path has been removed. When schedule reports allReady, call bare next again — it advances to the feedback phase.
• bare next → phase:"done" = the session is truly complete. Report and stop.

The feedback-phase steps (feedback_check, feedback) arrive as normal step descriptors, not done shapes. feedback_check is the end-of-epoch fork — ask the user, then complete with an explicit choice:

kautopilot complete --metadata '{"choice":"feedback"}'   # start a new planning epoch
kautopilot complete --metadata '{"choice":"done"}'       # end the session

It has no outputFile (don't pass --output). The binary rejects a complete without a valid choice — omitting the metadata is an error, never a silent "done". Only choose done after the user confirms and all scheduled merge/release work is recorded; on done, wrap-up (close ticket, clean worktrees) is yours — see Rule 8.

(If a session has no master plan/orchestration, fix that plan artifact first. New ticket-to-PR runs use the schedule/record DAG model.)

Start

/kautopilot PE-1234                     → NEW session for this ticket (org detected from it)
/kautopilot "add dark mode to portal"   → ad-hoc: brainstorm (superpowers-style) → create_ticket first
/kautopilot --org liftoff "…"           → org passed explicitly (else detected from ticket, else asked)
/kautopilot                             → NEW session — ask what to build
/kautopilot continue                    → pick a session for THIS folder to resume (see below)
/kautopilot --session <id>              → resume THAT session directly (drive `next --session <id>`); this is what the post-approve `/clear` handoff tells the user to run
/kautopilot --diff spec                 → kautopilot diff spec  (what changed between versions; also brainstorm|triage|plan[:<repo>]|feedback)

Default = a brand-new session. Only "continue" resumes. Unless the user's message says continue (or --session <id> is given), always start a fresh session — do NOT auto-resume an in-progress one, even if one exists for this folder/ticket. When the user does say "continue", resume per "Continue (this folder)" below.

Org is liftoff or atomicloud, resolved by --org → detect-from-ticket → ask.

The canonical start invocation (a new session runs this under the hood):

kautopilot start <TICKET_ID | "free-form request"> --org <liftoff|atomicloud> \
  [--merge manual|auto] [--max-repos <n>] \
  [--platform … --service … --landscape … --cluster … --module …] [--tag <t>]…

--max-repos <n> caps how many ready plans you run in parallel (maxParallelRepos). The legacy --exec kloop|sub-agent flag still parses but is vestigial — the DAG model ignores it (you always drive kloop yourself); don't pass it.

Merge policy (per session). mergeMode is manual (default — drive PRs to ready-to-merge and the user merges) or auto (the controller merges scheduled ready PRs to clear downstream gates). Set it at start with --merge auto|manual, or confirm it in the master plan. Either way ready-to-merge is always reached; auto is what lets cross-repo merged/released gates progress without a human merge in between. ⚠️ auto merges PRs no human has reviewed — "ready" means CI green + actionable (bot) review threads resolved, with NO human-approval gate. Only use auto when the user explicitly accepts merging unreviewed PRs.

Continue (this folder)

When the user says continue (with no explicit --session <id>), find the sessions associated with the current folder and let them choose:

1. List candidates: kautopilot ps -a --folder "$(pwd)" --json — a session is tied to the folder it was started in (never a repo/worktree); -a includes stopped/completed, and --folder substring-matches each session's associated folder against the current directory (so a hub dir also catches sessions started in subfolders under it). If that yields nothing, fall back to kautopilot ps -a --json and match the current path yourself.
2. 0 matches → tell the user there's nothing to continue here, and offer to start a new session instead.
3. exactly 1 match → confirm it (ticket + repo + phase), then resume: drive kautopilot next --session <id> per the normal loop.
4. multiple → present them via AskUserQuestion — one option per session showing its id, ticket, repo, and phase — and resume the chosen one with --session <id>.

(If the user said "continue" AND gave LPSM/tag words, use "Resume (atomicloud LPSM)" below instead — that's the tag-filtered variant of the same pick-and-resume flow.)

Launch from anywhere. kautopilot need NOT be started inside a repo — the cwd can be any directory (a hub) with access to many repos. You don't pre-pick a repo at start: triage decides which repos the task touches, locates (or clones, with the user's OK) each one, and records its absolute path (repoPaths); worktrees come later on demand via worktrunk.

After triage: confirm repos + paths, name the branch (REQUIRED)

Triage is interactive — before you kautopilot complete it, you MUST:

1. Confirm the repo set + each path with the user. Show, via AskUserQuestion, the exact list triage produced: every repo and its absolute filesystem path (the repoPaths you'll pass). The user must confirm these are the repos/paths to work on before any worktree is seeded — a wrong/missing path otherwise seeds a no-op repo. Fix or re-triage anything they correct. (These paths matter beyond worktrees: the feedback step appends confirmed rules to <repoPath>/rules.md — see "Feedback → rules.md".)
2. Propose a branch name. Derive an apt, short slug from the ticket title (e.g. "Add dark mode to portal" → dark-mode) and confirm it in the same question. The binary builds the final branch as <git-user>/<ticket-id>-<slug> (e.g. kirinnee/PE-1234-dark-mode) — the same branch across all the task's repos; you create each repo's worktree on it via worktrunk (wt) when schedule makes a plan ready. You only supply the slug — the binary fills in the <git-user>/ prefix and the <ticket-id> automatically. When showing the proposed branch, make clear the <ticket-id> part is the session's ticket reference (a variable prefix, e.g. PE-1234), not a literal word — only the slug is theirs to choose. (No ticket id → it falls back to a literal ticket- prefix.)

Then complete triage passing the confirmed values, including the slug:

kautopilot complete --output <triage> --metadata '{"complexity":"straightforward|moderate|complex","repos":[…],"repoPaths":{…},"dependsOn":{…},"branchSlug":"dark-mode"}'

branchSlug is marked optional in the schema, but treat it as effectively required: without it the binary records branch: null and nothing else ever names a branch — you'd be left inventing one yourself at wt time. Always confirm and pass a slug.

LPSM service-tree tags (atomicloud only)

At start, for atomicloud only, derive the AtomiCloud LPSM service-tree from the ClickUp ticket and tag the session with it (liftoff: skip LPSM entirely):

• The ticket's Space = Platform (functional-group theme, e.g. nitrite).
• Infer Service (element/periodic-table theme, e.g. neon — typically from the repo/component), Landscape (env, Pokémon theme, e.g. pichu=dev) and Module (free-form, e.g. api/worker) when evident.
• Confirm with the user via AskUserQuestion: show the derived L/C/P/S/M and let them correct any tier before proceeding.
• Then pass the confirmed values to start: kautopilot start … --platform <p> --service <s> [--landscape …] [--cluster …] [--module …].

All flags are optional; only pass the ones you have. They are harmless for non-atomicloud sessions but you only set them for atomicloud.

Besides the structured LPSM tiers, a session can also carry free-form tags via repeatable kautopilot start … --tag <t> (any org). These are arbitrary labels (e.g. urgent, spike) distinct from LPSM.

Resume (atomicloud LPSM)

When the user asks to resume by service-tree words — e.g. "resume a nitrite session" or "resume a nitrite neon session" — treat each word as an LPSM tag value and find the matching session(s):

1. List with tags: kautopilot ps -a --tag <w1> [--tag <w2> …] --json (or kautopilot ps -a --json and match yourself). Tag-filtering implies considering all sessions, not just running ones.
2. Use the themes to reason about tiers (but ultimately match against each session's stored lpsm): periodic-table element → Service (neon, carbon…); functional group → Platform (nitrite, sulfoxide…); Pokémon → Landscape (pichu, pikachu…); gemstone → Cluster (diamond, ruby…).
3. Matching rule: a tag matches if its value (case-insensitive) equals — or, failing exact, is a substring of — ANY lpsm field value (landscape/cluster/platform/service/module) OR any free-form tags[] entry. With multiple --tags, ALL must match (each somewhere).
4. Then: 1 match → resume it (drive kautopilot next --session <id> per the normal loop); multiple → list them (ticket + L/P/S) and ask via AskUserQuestion; none → tell the user nothing matched.

Driving the phases (one flat session)

• Plan + feedback (shared phases) — drive with bare kautopilot next / complete (triage → spec → master_plan → plans; later, feedback). Same loop as above.
• Execution (the DAG) — after the master-plan handoff (see "Reading done"), YOU drive it: kautopilot is a record-keeper + scheduler only. You run kloop, resolve conflicts, open/merge PRs per mergeMode, do all CI/review-thread detection, and record each transition — per "Driving the DAG" below. When schedule reports allReady, bare next advances to the feedback phase.

Driving the DAG (execution + PRs) — schedule + record

The master plan is a multi-stage DAG of plans grouped into PRs, with gate-leveled edges. You drive it; the binary tells you what's runnable and tracks progress. Loop:

loop:
  s = json(`kautopilot schedule --json`)
  if not s.ok: STOP — surface s.error (usually: no master plan approved yet)
  if s.done or s.allReady:
      `kautopilot next --json`           # → feedback_check
      break
  # 1. RUN ready plans (deps satisfied), up to maxParallelRepos at once.
  for plan in s.ready:
      provision/locate the repo's worktree off the LATEST base (worktrunk `wt`); keep its ABSOLUTE path
      `kloop init --workspace <ABS-worktree> --spec <plan>`  # ABSOLUTE path, never CWD-relative; prints the Run ID
      `kautopilot record started --repo <r> --plan <p> --kloop <runId>`
      `kloop run -d <runId>`; park on `kloop wait`; RESOLVE CONFLICTS yourself
      on success: commit (the commit sub-agent), then
      `kautopilot record implemented --repo <r> --plan <p>`
      (on an unrecoverable failure: `kautopilot record failed --repo <r> --plan <p>`)
  # 2. POLISH PRs from the schedule's PR frontier.
  for p in s.toPolish:
      if p.status == pending:
          open that PR on p.branch
          `kautopilot record pr-opened --pr <p.pr> --number <n> --url <u>`
      babysit the PR to ready-to-merge (CI green + all actionable review threads resolved)
      `kautopilot record pr-ready --pr <p.pr>`
  # 3. MERGE the PRs the schedule says must merge before feedback.
  for m in s.toMerge:
      if m.gate == "merged":
          if mergeMode == auto, merge PR m; if manual, ask/wait for the user merge; then
          `kautopilot record merged --pr <m.pr>`
      if m.gate == "released":
          wait for the release to publish + CI/CD, then
          `kautopilot record released --pr <m.pr>`
  # recording a merge/release re-opens the frontier → next loop runs newly-ready plans

• schedule --json returns { ok, ready[], running[], blocked[], toPolish[], toMerge[], allReady, done, mergeMode } — or { ok:false, error } (still exit 0, e.g. before a master plan exists), so check ok first; never iterate fields of an ok:false payload. ready = run now. toPolish[] = PRs whose plans are implemented and whose PR polish is not complete (pending means open the PR; open means keep fighting CI/CodeRabbit/review threads). toMerge[].gate = merged or released; toMerge[].unblocks = which downstream plans that gate frees (gate-clearing entries are listed first; terminal ready PRs may also appear). allReady is true only after no scheduled merge/release remains — it already implies toMerge is clear. blocked[].waitingOn = why a plan waits.
• Parallelism — run up to maxParallelRepos ready plans at once (each as a sub-agent driver); the rest wait. Serialize user interaction to the main chat (a conflict that needs a human decision comes back inline, one at a time).
• You own the worktrees now. Provision each repo's worktrunk worktree (wt) off the latest base before running a plan — for a merged/released-gated plan the schedule only makes it ready after the upstream is merged/released, so the base already contains the upstream work. Bad/missing repo path → stop and tell the user; don't run on nothing.
• Multi-PR per repo is real here — open exactly the PRs the master plan lays out (record pr-opened --pr <id> per PrPlan), then run the PR polish loop inside that PR and record pr-ready only after CI is green and actionable review threads are resolved. Merge them per their gate after schedule lists them in toMerge.
• Resumable any time — schedule recomputes purely from what you've recorded, so a killed/auto-resumed session just calls schedule again and continues from the frontier.

Per-kind execution

• code — never appears. The binary ran it inline.
• interactive (brainstorm, triage, write_spec, write_master_plan, write_plans, feedback_check, feedback, create_ticket) — run inline in the main session. Be a devil's advocate: propose first, debate, surface conflicts; never open with "what do you want to do?" For the writer artifacts run the per-revision review loop below (it defines the approval gate — the ONLY way a writer step advances). Spawn Explore subagents for heavy research so the conversation stays lean.
  • create_ticket is interactive but NOT a revise-loop artifact: its prompt says to draft the ticket, show it, and get explicit confirmation before creating — do that inline (a subagent can't talk to the user), then run the creation command and complete with the ticketId. (Don't spawn a subagent for it.)
  • feedback_check is a single fork question, not an artifact — see "Reading done" for its required choice metadata.
  • write_master_plan is the orchestration artifact, presented and approved before write_plans (it locks the order of execution first). Run the normal per-revision loop (revise → visual → present → approve). It must lay out: the PR/branch layout (default ONE PR + ONE plan per repo — kloop handles a substantial change in one pass; split into more plans/PRs only for separate repos, a real merge/release ordering gate, a change too big for one kloop run, or independently-releasable units — give each PR an id, repo, branch, title, and the plan-<N>s it ships); the dependency DAG with gate levels (completed | merged | released, edges may span repos); and a mermaid graph TD of the DAG (the dashboard renders it). Confirm the merge policy (manual asks before merging / auto merges ready PRs — see the ⚠️ in "Start") here too. On approval, complete write_master_plan with metadata { mergeMode?, prs[], nodes[], deps[] } — the binary freezes it into orchestration.yaml (the resumable record that also tracks each plan's exec status + kloop run). The plan-<N> ids you choose here are the ids write_plans then writes bodies for.
  • write_plans writes one FOLDER per plan. Every plan folder MUST be named plan-<N> or plan-<N>-<short-slug> (the literal plan-<N> prefix is required, e.g. plan-1, plan-2-api). That ordinal is what the schedule/record execution loop uses to match each plan to the master plan's ids — a folder without the prefix (e.g. auth/ or 1-auth/) still gets picked up off disk, but its id never matches the master plan, so schedule/record reject it and the dev loop fails to init. If the plan-writer proposes a breakdown with non-conforming folder names, correct it before approving.
• agent (fetch_ticket, plus the skill-owned kloop/commit/PR-polish agents you spawn from schedule) — always a fresh isolated run, never inline: a detached kteam session by default, Task subagent as fallback. (The reviewer fan-out isn't a step — it rides on the write_spec/write_plans interactive steps and you spawn each reviewer as its own kteam session.)

Running kloop for a ready plan (you drive it)

In the DAG model the binary does not run or watch kloop — YOU drive it. Do NOT bury the whole run inside one subagent (the classic mistake: a subagent blocks on kloop wait and dies at the Bash ~10-min cap, orphaning the daemon and recording nothing). kloop init / record started / kloop run -d are all instant — run -d is a daemon that returns immediately and logs to its own files, so there is nothing noisy to hide. So: the main thread runs steps 1–3 directly, then parks on the wait (step 4), and only the commit / PR-polish are subagents (step 5). For each ready plan from kautopilot schedule, in the repo's worktree (off the latest base):

⚠️ --workspace MUST be an ABSOLUTE path. This bug has burned us many times. kloop init falls back to the current directory when --workspace is missing OR relative (path.resolve(opts.workspace ?? process.cwd())), and the Bash CWD is the session's launch/hub dir that resets between calls — so a relative/omitted workspace inits the run in the HUB, not the repo, and the whole plan runs on the wrong tree. direnv exec <dir> does NOT help — it loads that dir's env but does not change the working directory. Capture the absolute path wt prints and pass it verbatim — an absolute --workspace makes CWD irrelevant. (cd works, but CWD resets between Bash calls, so relying on it is fragile — the absolute path is the robust fix.)

1. kloop init --workspace <ABS-worktree> --spec <plan> → note the Run ID it prints. <ABS-worktree> = the absolute path wt printed for this repo; confirm it exists (test -d) before init. If you only have a relative path, make it absolute first — never pass a bare/relative workspace.

2. kautopilot record started --repo <r> --plan <p> --kloop <runId>.

3. kloop run -d <runId> (daemon — output goes to kloop's logs, not your context).

4. Wait for the run WITHOUT polling. kloop wait <runId> blocks until the run is terminal (completed / conflict / failed / cancelled / crashed) and streams one line per status/phase change — a poll→stream conversion. Never sit in a kloop status poll loop (that burns tokens every tick). How you park on it differs by harness:

   • Claude: arm a Monitor with command: kloop wait <runId> --json — one event per phase change, and the monitor ends itself when the run goes terminal. Keep working (hand other ready plans off in parallel); the terminal event wakes you. Use a long timeout_ms (kloop runs take many minutes) or persistent: true.
   • Codex (no Monitor): delegate a cheap, fast subagent (smallest/cheapest model) whose only job is to run kloop wait <runId> and return the final status line — the main thread parks on that subagent (not polling), resuming when it returns. A cheap model is fine; it only relays kloop's terminal state. For parallelism (several ready plans at once), delegate one wait-subagent per run in parallel via Codex's native multi-agent delegation and resume as each returns — don't serialize the waits unless you want to.

   Once kloop wait returns terminal, read kloop describe <id> once for a summary.

5. You decide + handle the outcome (the binary won't): completed → commit (commit sub-agent) → kautopilot record implemented. Conflict / max-iter → resolve it yourself (or bring a genuine human-decision conflict back to the main chat), then re-run / commit. Unrecoverable → kautopilot record failed.

kloop still never commits (implements/reviews only) — the commit sub-agent commits. Then record implemented so the scheduler advances the DAG.

Reviewers run BEFORE you present (fan-out)

When the writer descriptor (write_spec / write_plans) carries review, run the reviewers before you present a version to the user — so every version the user sees is already review-checked. On your working draft: spawn every reviewer as a parallel sub-agent, run the synthesize sub-agent into one numbered list, and fix the draft until all reviewers approve (or the user overrides via complete … --metadata '{"reviewOverride": true}'). Reviewer rounds are NOT versioned — they refine the draft in place. Only once it's review-clean do you mint the version (revise, below) and present it. There is no separate spec_review / plan_review step.

For spec and plans, the checkpointer litmus test (below) is a REQUIRED review lens — a litmus failure blocks the version, same as any other unresolved finding.

Each user presentation = a new version (revise)

A version is a snapshot the user was shown. Every time you present a writer artifact (brainstorm, triage, spec, plans, feedback) to the user, it must be a new version — never silently overwrite what they already saw. The binary mints versions; you never pick numbers or hand-build URLs:

1. To present, run kautopilot revise [--repo <repo>]. It returns {version, path, url, diffUrl, visualUrl}. The binary handles version numbers: the first call presents the step's working copy as-is (v1 — no redundant duplicate); each later call (after the user's feedback) copies the last-shown version forward (vN → vN+1) so the version they already saw is preserved. So: just run revise once per presentation round and trust the version/url/visualUrl it hands back.
2. Edit the returned path to address the user's latest feedback (reviewer rounds first, per above — those don't mint versions).
3. Generate the visual for THIS version BEFORE presenting — see "Generate the visual" below (required, non-skippable; confirm the HTML file(s) exist or the Visual link will 404).
4. Present the link(s), not the file — the Read (markdown) and the Visual (infographic):
   • Read: the returned url (or diffUrl to show what changed).
   • Visual (single-file artifacts): the returned visualUrl — a standalone full-page infographic that links back to the Read view.
   • Plans: present just the Read link (url). revise returns no visualUrl for plans — each plan has its own infographic, reachable from a "View visual" link on that plan's tab in the dashboard. Never construct a version URL yourself — always use exactly what revise returns.

Viewer base URLs — revise already returns FULL URLs (host included), so use its url/diffUrl/visualUrl verbatim. For the links you DO build by hand (ticket, plans listing, kloop run), read the configured host — never hardcode a domain:

• kautopilot config --field viewerBaseUrl → this dashboard's base URL
• kautopilot config --field kloopBaseUrl → the kloop dashboard's base URL

(kautopilot config with no flag prints the whole resolved config as JSON. The binary has localhost fallbacks, but the user runs a public domain set in ~/.kautopilot/config.yaml — so always read the config, don't guess.)

The viewer must be running (kautopilot dash up / kloop dash up) for links to load; it shows the session's current epoch. Revisions are machine-local and never committed.

Generate the visual (HTML infographic) — a sub-agent, every version

Before presenting each artifact version, spawn a fresh isolated Task sub-agent to produce a visual, infographic-style HTML version of the same content — one vN.html next to each single-file artifact's vN.md, and for plans one sub-agent per plan (each writes its own <plan>/vN.html), spawned in parallel. Required for every version of every artifact; confirm the file(s) exist before presenting.

The full design brief is in visual.md — hand the sub-agent that brief (its path or contents) plus the two inputs it needs: the path that revise returned and the Read URL (revise's url) to use verbatim as the source link. Spawn with the Task tool (subagent_type: general-purpose); it should use the frontend-design skill if available, else apply the brief's principles directly.

The per-revision review loop (the approval gate)

Every interactive writer artifact is iterated until the user has no more feedback — never auto-advance after one draft. A new version is NOT approval; it's the start of another review round. For a single artifact step, loop like this and do not complete (which lets the binary move to the next step) until the user explicitly approves:

1. Draft / update the working version, then run the reviewers (above) and fix until review-clean — these rounds are not versioned.
2. Mint + generate visual + present — exactly per "Each user presentation = a new version" above (revise → vN.html visual(s) → Read/Visual links). Add a 2–4 line summary of what changed and a short TODO / open-items list (what's unresolved, and which of the user's last feedback this version did / did NOT address).
3. Ask for feedback or approval.
4. Any feedback = not approved. Address it → revise again → that's the next version → go back to step 2. Keep looping: v2 ok? → feedback → v3 ok? → …
5. Only advance on an explicit "approve". Move to the next step (kautopilot complete) ONLY after the user literally says "approve" (that specific word) for the CURRENT version, with open-items empty. Anything short of that — silence, "looks good", "nice", a new question — is not approval; stay in the loop. (For triage and spec the bar is stricter — see "No open questions or risks": every open question must be user-answered and every spec risk resolved, and you spike anything investigable rather than asking. Don't complete with items still open even on an explicit "approve".)

This section is the one canonical approval rule — wherever this doc says "after explicit approval", it means step 5 here.

Re-present after EVERY interaction — including AskUserQuestion. Any time you turn back to the user mid-artifact — even to ask a clarifying question via the question tool — you must re-present the current version (both Read + Visual links + summary) in that same message. Never ask a question without the live version in front of them, and never treat a question's answer as approval. Only the explicit word "approve" advances the step.

Don't assume a later revision's content propagates. The next step consumes the artifact at a specific path the binary picks (usually the latest version). Before you complete, make sure the approved content actually lives where the next step will read it — if you edited a higher version (e.g. v2) but the next step is wired to read an earlier one, the downstream step silently uses stale content. When in doubt, confirm the latest version holds the approved text.

No open questions or risks — triage + spec gate (REQUIRED before approval)

Triage and spec are not approvable while anything is still open. Before you kautopilot complete either step, drive every unknown to closure. Two kinds:

• Needs investigation → SPIKE it (don't defer, don't ask). Anything answerable by looking — how does X work, does this API/field exist, where's the call site, is this approach feasible — is NOT an open question, it's a spike. Spawn a fresh-context spike sub-agent (Claude: an Explore/Task; Codex: a delegated read-only subagent) to actually investigate the code/docs/APIs, and fold the finding into the artifact. Keep spiking until only genuine decisions remain. Never hand the user a question you could have answered yourself.
• Needs a human decision → the USER must answer it. Whatever genuinely needs the user (a product/scope/trade-off call you cannot resolve by looking) stays an explicit open question in the artifact, and every one must be answered by the user before you complete. List them, get the answers, write the answers into the artifact, re-present.

Spec additionally has zero unaddressed risks. Every risk the spec — or its reviewers — identifies must be explicitly resolved with the user (answered, accepted, or mitigated in the text) before approval. A known-but-unhandled risk blocks approval exactly like an open question.

The gate (hard): for triage and spec, "open-items empty" is mandatory, not aspirational. Do NOT complete while any open question, un-run spike, or (spec) unmitigated risk remains — even if the user says "approve". If they approve with items still open, surface the remaining items and ask them to resolve each one first, then advance. Surface the open list every time you present (it's part of the per-revision "open-items" summary).

(This is controller-enforced gating. The literal triage/spec prompt text is owned by the kautopilot binary — if you want the binary itself to emit "spike it / answer all open questions" in the step prompt, that change lives in the step prompts under /Users/erng/.config/home-manager/modules/kautopilot-ts/src/steps/ — not here.)

Litmus test — will it run to completion unattended? (spec + plans)

Before approving spec and plans, run the checkpointer litmus test on the artifact:

If a kloop implementer + reviewer — neither of which may ever commit, push, or open a PR (those are the controller / commit-subagent's job) — ran this to the end, would the Definition of Done (DoD) / verification criteria eventually be satisfiable? Or is there a fundamental logic flaw or blindspot that traps the loop forever?

kloop is autonomous: it implements + self-reviews against the DoD until the DoD passes. If the DoD can never pass, kloop spins to max-iter and needs a human — the litmus test catches that before approval so the run stays hands-off. Two failure classes:

1. Unsatisfiable DoD — capability / permission gap. The DoD requires an action the loop cannot perform, or a resource that doesn't exist, so the implementer can never clear it.
   • "The implementer commits / pushes / opens the PR" — implementers never commit (the commit subagent does). → reword the DoD to be verifiable from the working tree (files changed, tests/build pass), not from a commit/PR.
   • "ssh into the DigitalOcean box and run X" — the box doesn't exist / the loop has no creds. → provision/verify out-of-band (a controller step), or drop it from the loop's DoD.
2. Logical conflict — two criteria that can't both hold.
   • "Remove all container/docker logic; verify by grepping container → must not exist" — but integration tests use testcontainers, so the grep is never empty. → scope the check (grep only infra dirs / exclude test deps) or change the criterion.
   • "Do not change any existing code + reach 100% coverage" — unreachable code makes 100% impossible without deletion. → relax one (allow deleting dead code, or target < 100%).

When the litmus test fails it's a fundamental flaw — treat it like an open question/risk (per the gate above): fix the spec/plan with the user (loosen the verification, make the DoD tree-verifiable, move the impossible action to a controller step, resolve the contradiction) and do not approve until it passes clean. Apply it to spec (is the overall DoD satisfiable + self-consistent?) and to each plan (can this plan's slice reach its own DoD unattended under kloop's constraints?). It's a required lens in the reviewer fan-out, not optional.

Feedback → rules.md

At feedback (a versioned artifact), don't apply feedback literally. Distill candidate rules, reasoning about scope (task- vs repo-specific; code-writing vs solution-thinking) and generalizing; confirm with AskUserQuestion (show a rules.md diff). Then you must complete the step with metadata { "rules": ["…", …] } — that metadata is the ONLY way rules are recorded (omit it and nothing is written).

How persistence actually works:

• The binary appends each rule as a bullet to rules.md in each repo's recorded path — the repo's worktree if one was recorded, else the repoPath captured at triage. It creates the file (with a # Rules header) if missing.
• rules.md is a plain, standalone file — the binary does NOT link it from CLAUDE.md/AGENTS.md. If the user wants agents to load it automatically, wire that reference up yourself (with their OK) as part of the repo's changes.
• If no repo has a usable path, the complete fails loudly and nothing advances: write the rules into each repo's rules.md yourself, then re-run kautopilot complete without the rules metadata.

End every message with a links table

End EVERY message that presents artifacts with one SIMPLE, FLAT summary table of ALL the session's shareable links — one row per thing, the label IS the link, never a two-column Read|Visual layout. The exact layout, row inventory, URL-building rules, and a concrete example are in links-table.md — follow it verbatim. Key invariants: read viewerBaseUrl/kloopBaseUrl from kautopilot config --field … (never hardcode a domain); never hand-build version URLs (use revise's returned url/diffUrl); if there is genuinely nothing to link yet, say so in one line instead of an empty table.

Rules

1. Only merge when scheduled — and the epoch ends at merged/released, not "ready". Ready-to-merge (CI green + all actionable threads resolved, excluding human-review approval) is the controller's floor — you always drive every PR there. But the epoch is only over when every PR is merged/released as the master plan schedules: allReady stays false while any scheduled merge/release is outstanding. mergeMode decides ownership: in manual, ask/wait for the user to merge (never merge yourself); in auto, the controller may merge only PRs returned by schedule.toMerge (⚠️ unreviewed by humans — see "Start"). Always record the result with kautopilot record merged --pr <prId>; if toMerge[].gate is released, wait for the release boundary and record kautopilot record released --pr <prId>.
2. Never push to main/master; never force-push except --force-with-lease.
3. Poll with gh api graphql, never blocking watchers (gh pr checks --watch, gh run watch) — CI/thread detection is YOURS during PR babysitting; the binary does not watch anything.
4. Ask before cloning a repo.
5. Only complete after the contract is satisfied — and, for interactive steps, after explicit approval per "The per-revision review loop". The binary checks the artifact; you guarantee consent.
6. Bot signature on PR replies: "By Claude Code kautopilot 🤖".
7. Never hand-edit binary state (~/.kautopilot/…). Update the ledger only via record (and drive via next/complete/schedule); read via diff/status/schedule.
8. You drive the work; the binary records it. In the DAG model YOU provision worktrees (worktrunk wt), run kloop, resolve conflicts, open PRs, and merge them — and record each transition (started/implemented/pr-opened/pr-ready/merged/released/failed). You never commit by hand; use the commit subagent after kloop completes. Wrap-up is skill-owned: after final feedback_check says done, close the ticket and clean up worktrees yourself if appropriate. The binary no longer yields close_ticket or cleanup.

Prerequisites

• kautopilot + gh CLI in PATH and authenticated; kloop (you drive it yourself during execution — the legacy kautopilot start --exec kloop|sub-agent flag is vestigial and ignored in the DAG model).
• Jira: acli authenticated. ClickUp: the cup CLI (ClickUp CLI for AI agents) — prefer it over any ClickUp MCP for reading/creating tickets (cup task <id>, cup create, cup subtasks/cup activity).