loop

name	loop
description	Run a continuous goal-loop: work a prioritized RICE-scored backlog toward a standing goal, cycle after cycle, consuming/emitting signals. Use for ongoing autonomous improvement toward a goal; not for a single discrete task (use run).

Run a dedicated goal-loop: pursue a standing goal by repeatedly working down a prioritized backlog, learning each cycle, until the goal is met. This is the outer loop that wraps RePPITS (/run is its "act" step).

Trigger (next backlog item) → Investigate & Act → Backlog gen / Assign → Review & learn → ↺

How to run it (so it actually loops)

• Invoke: /loobster:loop <goal> (plugin commands are namespaced; the bare /loop won't resolve unless you alias it as a project command).
• One invocation runs cycles back-to-back in this session — after each Review & learn, immediately start the next cycle without asking, and keep going until an exit condition (below). Do not stop after one item; running many cycles is the whole point.
• Self-driving — no wrapper needed. /loobster:loop <goal> arms its own durable re-entry; you do not prefix it with the /loop scheduler. At setup (and re-armed at the end of each turn while status: active) it schedules a re-invocation of itself so a turn boundary or a dead turn (API drop, crash) auto-resumes the loop from its checkpoint:
  • In-session durability: ScheduleWakeup(prompt: "/loobster:loop <goal>", delaySeconds: 1200, reason: "goal-loop heartbeat") — a self-paced re-entry that resumes the loop after a turn boundary or a dead turn (reason is required; delay min 60s). Re-arm while status: active; stop arming on exit.
  • Closed-session / overnight durability: also CronCreate(cron: "*/20 * * * *", prompt: "/loobster:loop <goal>", durable: true) so it survives the session being closed. durable: true is required — without it the cron is in-memory only and dies when the session ends (defeating overnight durability). CronDelete it on exit; recurring crons auto-expire after 7 days.
  • If neither tool is available in your runtime, the loop still runs cycles in-session and the Stop hook covers graceful stops; for hard-crash durability there, supply an external driver (cron / Agent SDK).
• Crash resilience, in one line: the self-armed re-entry re-fires /loobster:loop <goal> after a dead turn → it self-heals (reclaims stale in_progress, continues from the checkpoint — see Self-healing below). The bundled Stop hook (hooks/hooks.json → bin/loop-rearm.py) additionally refuses a premature graceful stop while status: active. Together a dead turn, a crash, or a milestone-pause all resume automatically. Disable the hook with LOOBSTER_LOOP_REARM=0.

Permissions (loop autonomy ≠ tool permissions)

The loop suppresses its own questions, but Claude Code's tool-permission prompts are a separate layer the loop can't control. The subagents this loop spawns do not inherit a session's runtime --dangerously-skip-permissions flag — they resolve their permission mode from settings. So if permissions.defaultMode is auto or default, you'll be prompted per file write even though the main session shows bypass (auto mode's classifier independently evaluates each subagent's tool calls). To run the loop prompt-free:

• Set permissions.defaultMode: "bypassPermissions" in ~/.claude/settings.json (a launch flag alone is not enough for subagents).
• Add a permissions.deny list (e.g. recursive deletes, force-push, hard-reset, .env reads) — deny/ask rules still fire in bypass, so you keep guardrails.
• Then restart the session (settings load at start).

This command is executable, not advisory — do these concrete steps

On invocation, actually perform the following (don't just describe them):

Setup

1. Restate the goal in one line and write free-text success criteria. Create a goal record: TaskCreate a task titled GOAL: <one-line goal> with metadata.kind="goal", metadata.goalId="<slug>", the success criteria, and metadata.maxCycles (default 10). Also write plans/loop/<slug>.md with frontmatter (status: active, goalId: <slug>, the one-line goal, cycle: 0, plus the single-runner lease runner: + runnerHeartbeatAt: — see Self-healing) followed by the success criteria + an empty learnings log. The status: active marker is load-bearing: the Stop hook (bin/loop-rearm.py) reads it to keep the loop running across turn boundaries — set it to done only on a real exit/escalation.
2. Recommend compression (loops re-read code every cycle): tell the user "set LOOBSTER_HEADROOM=1 to compress repeated code reads (README › Token reduction; PHI caveat applies)." Proceed regardless.
3. Seed the backlog: TaskCreate one task per known work item, each with metadata.goalId=<slug> and a RICE score per .agents/skills/backlog-scoring/SKILL.md. For large scoped items, run /make-plan to decompose — its sub-tasks join the backlog.
4. Arm self-re-entry and SHOW the schedule (this is what makes the single command self-driving — and visible). Like the /loop skill confirms what it scheduled, this loop prints its own re-entry settings on kickoff so you can see exactly what's running, no separate script:
   • If CronCreate/ScheduleWakeup are callable, arm them — ScheduleWakeup(prompt: "/loobster:loop <goal>", delaySeconds: 1200, reason: "goal-loop heartbeat") for an in-session dead-turn fallback (idle ticks past the 5-min cache window are wasted, so lean 1200–1800s), plus CronCreate(cron: "*/20 * * * *", prompt: "/loobster:loop <goal>", durable: true) for closed-session durability (durable: true is required, else the cron dies when the session closes). The single-runner lease (see Self-healing) makes this safe even on a shared worktree: a fired wakeup/cron backs off if a live runner holds the lease and only takes over when the lease goes stale — so you can arm cron instead of hand-skipping it to dodge contention. Record the id in the marker frontmatter (reentry: <id>), then print the schedule: the cron expression, the human-readable cadence, the job/wakeup id, that recurring crons auto-expire after 7 days, and how to cancel (CronDelete <id> or set status: done). Lead the line with self-driving: ARMED.
   • If those tools aren't available here, print self-driving: UNAVAILABLE → in-session loop + Stop hook only and continue (re-invoke /loobster:loop manually, or add an external driver for crash durability).
   • Also print a one-line readiness so nothing is silent: Stop-hook re-arm on/off (LOOBSTER_LOOP_REARM), permission mode (is it bypassPermissions?), headroom on/off. This is the "ask loobster" answer at kickoff — and the status mode below reprints it on demand.

Self-healing — do this on every (re)entry (crash-safe resume)

A previous run may have died mid-cycle (API drop, crash, stop). Before picking work, reconcile durable state:

1. Check the marker status first. If plans/loop/<slug>.md status is not active — it's paused (a human approval gate is pending) or done (finished/escalated) — the loop is intentionally halted: do not resume or re-arm the driver; report the state and stop. A self-re-entry wakeup that fires on a paused/done loop must be a no-op (this is what keeps an approval gate from being auto-driven past). Only continue when status: active.
2. Acquire the single-runner lease (concurrency safety — only ONE loop instance runs at a time per worktree). The authoritative mutex is an atomic lock file, claimed via bin/loop-lease.py acquire plans/loop/<slug>.md <runner-id> (it uses O_CREAT|O_EXCL, so two racing instances cannot both win — a real lock, not just a convention). If it prints held by <other> and exits 3, another instance is already looping (a ScheduleWakeup/cron firing while an in-session run is live, or a parallel headless run on the shared worktree): do not start a concurrent cycle — leave the fallback armed and exit quietly. If it prints acquired (a free or stale lease), proceed and mirror runner + runnerHeartbeatAt into the marker frontmatter for humans/status. This per-runner lease (one instance per worktree) is distinct from a task's metadata.heartbeatAt in step 4, which only distinguishes an interrupted task from a running one.
3. Reload the goal task (metadata.kind=goal) + plans/loop/<slug>.md (cycle, learnings). If the goal task is gone but the marker exists, rebuild from TaskList for the goalId.
4. Reclaim stale in-progress. Any task in_progress whose metadata.heartbeatAt is missing or older than ~2 cycles was interrupted, not running → it becomes the next item. Check what already landed first (git status/diff, committed sub-issues, sub-task states) and continue it — never redo completed work, never double-commit. (This is the M19-style "stranded in_progress after a connection drop" case.)
5. Then enter the loop, refreshing the lease each cycle while you hold it — bin/loop-lease.py refresh plans/loop/<slug>.md <runner-id> — and mirror runnerHeartbeatAt in the marker. (/resume routes a goal-loop straight here, and must re-acquire the lease too.)

The loop — repeat until an exit condition

1. Trigger (next item): first consume relevant signals from the shared hub (see .agents/skills/signals/SKILL.md) — read signals/*.md with status: new|ack and a relevance tag this goal cares about; a high-confidence signal may outrank the backlog (or spawn a new scored task). Then TaskList, filter to open, unblocked tasks for this goalId, pick the highest metadata.score (ties → lowest effort, then lowest id). If none remain → go to step 4 to decide done-vs-new-work.
2. Investigate & Act — in a subagent (Agent, so the heavy reads stay out of the loop's context): the subagent investigates the item, then acts — substantial change → run /run <item> (autonomous mode; sensitive items still hit full gates + Secure); small fix → do it directly. It returns only a compact result: outcome, any new backlog items (with RICE), and a one-line learning. TaskUpdate the worked item (in_progress→completed, or keep in_progress + record the blocker). Heartbeat: when you set a task in_progress, stamp metadata.startedAt + metadata.leaseId and refresh metadata.heartbeatAt as it progresses — that timestamp is what lets a later entry distinguish an interrupted task from a running one (step Self-healing).
   • Do not force isolation: "worktree" on the act subagent. A worktree writes into an untrusted .claude/worktrees/<id>/ path, and combined with non-bypass permission modes it surfaces a write-prompt per file (see "Permissions" above) — which defeats unattended running. Use worktree isolation only when genuinely parallelizing independent sub-issues and the session is in bypassPermissions; otherwise run the act in the loop's own permission context.
3. Backlog gen / Assign: TaskCreate the new items the subagent surfaced (scored, tagged with goalId).
4. Review & learn: judge the cycle's result against the goal's success criteria → met / partial / not-met. Use a separate verifier subagent — never let the agent that did step 2 (Act) judge its own work (see the "Never self-verify" rule in run.md); the judge gets the diff + criteria and returns its verdict. Then: append a one-line learning to plans/loop/<slug>.md (re-summarize the log so it stays small); re-score the backlog from what this cycle taught (never overwrite user-set factors). Emit signals: if this cycle surfaced something other loops/teammates should know (a friction, an opportunity, a fact), write it to the shared hub per .agents/skills/signals/SKILL.md (stamp author, dedup first, no PHI). Mark any signal you acted on this cycle acted/archived.
5. Loop: if no exit condition, go straight back to step 1 — do not pause for the user between cycles.

Exit & escalation — the ONLY reasons to stop

• Exit only when one of these holds: (a) the model judges the goal met, (b) the backlog is empty with no new work justified, (c) maxCycles reached, or (d) --budget exhausted. On exit, set status: done in plans/loop/<slug>.md (releases the Stop-hook re-arm), release the runner lease (bin/loop-lease.py release plans/loop/<slug>.md <runner-id>, and clear runner: in the marker), and cancel the self-re-entry — stop arming ScheduleWakeup and CronDelete the cron recorded in the marker's reentry id — then summarize: goal status, what shipped (commits/PRs), remaining backlog, key learnings.
• Escalate (stop + summarize + set status: done + cancel the self-re-entry, hand back) only on: a stuck Investigate&Act loop (its cap), a sensitive change that fails Secure, or a per-cycle token spike. Never auto-push past unresolved work.
• NOT exit conditions — do not stop or pause to ask; continue straight to the next cycle: reaching a "clean milestone", finishing a cluster / PR / batch, having "done a lot", or hesitating to "auto-spend" more cycles/tokens. A milestone is not the goal. If you catch yourself about to write "say keep going", "want me to continue?", or "I'll hold here" — don't; keep going until a real exit/escalation condition above. Spend is bounded by maxCycles and --budget, never by a voluntary hold. (The Stop hook enforces this for interactive runs.)
• Human approval gates stay sacred. The "never stop at a milestone" rule does not override the gates: if the act step reaches the final commit/push approval, a sensitive Secure FAIL, or any mandatory gate, set the marker status: paused (or done) before stopping so the Stop hook allows it — the loop never pushes past an approval or unresolved FAIL to stay alive. Resume after the human responds.
• Checkpoint each cycle: update cycle (+ a one-line current position) and refresh runnerHeartbeatAt in the marker before/after the act step, so a crash mid-cycle resumes precisely and the runner lease stays live while you're working.

Status — ask loobster anytime

Invoke /loobster:loop status (or just ask "what's the loop doing / what's scheduled?") and report — without starting a cycle — for each plans/loop/*.md that is active or paused:

• Goal, status (active / paused / done), current cycle.
• Schedule: run CronList and match the marker's reentry: <id> → show the cron expression + cadence + 7-day expiry, and the in-session ScheduleWakeup cadence. (This is "show the cron job settings", on demand.)
• Backlog: TaskList for the goalId → counts (done / in-progress / open) + the next item.
• Runner: the runner lease + runnerHeartbeatAt — is an instance actively looping (fresh) or is the lease free (no live runner)? This tells you whether a re-entry would take over or back off.
• Readiness: Stop-hook re-arm on/off, permission mode, headroom on/off.
• Controls: stop with status: done in the marker (or CronDelete <id>, or LOOBSTER_LOOP_REARM=0); pause for a gate with status: paused.

This is the single place to see what every loop is doing and how it's scheduled — no separate script to run.

Arguments

• goal: free-text goal + success criteria. Required (unless status).
• status: report the active/paused loop(s) — schedule (cron id + cadence), backlog, readiness, and how to stop — without running a cycle.
• --max-cycles N: hard cap (default 10).
• --budget T: optional output-token budget; escalate when exhausted.

Token economics (loops are token-hungry — enforce)

• Per-cycle subagent isolation (loop step 2) is mandatory — the loop holds conclusions, not raw reads.
• Artifact compaction: each cycle loads the goal + top-N scored tasks + the rolling learnings digest, never the full history; re-compress old learnings each cycle.
• Option D AST compression is the hard recommendation for loops (LOOBSTER_HEADROOM=1) — repeated code reads are headroom's CodeCompressor (AST) sweet spot. Agent SDK driver → headroom proxy/middleware.
• Budget guard: track output tokens per cycle; on a spike or --budget exhaustion, escalate rather than silently continue.

Resuming & compliance

• Resumable: goal + backlog + learnings are durable (Tasks + plans/loop/<slug>.md); TaskList for the goalId reconstructs progress — continue from the highest-scored open item (see /resume).
• Never bypasses RePPITS gates for sensitive items, never skips Secure, never auto-pushes — it produces commits/PRs that still hit the final approval, or it escalates.