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control for long running pi work: interview drafted goals, an audited task queue, and metric or audit loops that run for hours. Every completion is rechecked by a detached auditor with raw evidence, while Confirm drafts, decision pauses, and conse","maintainers":[{"name":"dracond","email":"adamnagywork@gmail.com"}],"readme":"# pi-goal-list-loop-audit\n\n<p align=\"center\">\n  <img src=\"media/glla2.png\" alt=\"GLLA mission control\" width=\"960\">\n</p>\n\n> **Long running, high leverage autonomy for pi.**\n>\n> Give pi a meaningful outcome. GLLA helps it research, plan, execute,\n> recover, and prove the result over hours or days instead of treating one\n> chat turn as the whole job.\n\n`pi-goal-list-loop-audit` (GLLA) is mission control for autonomous work in\n[pi](https://github.com/badlogic/pi-mono). It fits work that is too broad,\ntoo long, or too important to leave to a single uninterrupted prompt:\nrepo-wide changes, migrations, audits, research, documentation overhauls,\nlarge refactors, and continuous improvement.\n\nGLLA does not promise that an agent never makes a mistake. It makes the\nagent's work **more effective, durable, recoverable, and hard to declare\nfinished without evidence**:\n\n- You state the outcome and what “done” means.\n- The agent researches, decomposes, and executes across many turns.\n- GLLA keeps durable state, checks lifecycle/progress signals continuously, and\n  recovers failures with bounded per-attempt backoff plus policy-driven stop rules.\n- Every terminal objective leaves a useful six-label recap; missing evidence is\n  shown as `not recorded`, never guessed.\n- Optional subagents can do parallel research and focused implementation work.\n- A separate detached auditor checks the saved completion claim before GLLA\n  accepts it.\n\nThe aim is not \"run forever.\" The aim is **more useful work per unit of\nattention, with event-driven progress instead of guessed-duration waiting, and\nbetter evidence at the end**. See `docs/DESIGN-long-running-supervision.md` for\nthe long-running policy.\n\nUse `/glla version` to inspect the installed version and compare it with the\nregistry. This checkout may contain unreleased changes; npm is authoritative\nfor published versions. The npm/Pi package listing displays this README from\nthe published tarball, so release the package after updating it when store\nreaders need the latest guidance.\n\n## Is GLLA the right tool?\n\nUse GLLA when the work benefits from an autonomous operator that can keep\ncontext, make progress without a prompt after every step, and return with an\nevidence-backed result:\n\n- a feature that spans several files or subsystems;\n- a migration, security review, or repository audit;\n- research followed by implementation;\n- a documentation or test-quality overhaul;\n- a backlog of independently verifiable changes;\n- an improvement process that should run until a metric, specification, or\n  audit cadence says to stop.\n\nUse ordinary pi for a one-line edit, a quick question, or work where you want\nto supervise every action manually. GLLA is a **supervisor for high-level\noutcomes**, not a replacement for judgment or a reason to remove a human from\nimportant decisions.\n\n## Install\n\nInstall GLLA into pi:\n\n```bash\npi install npm:pi-goal-list-loop-audit\n```\n\nFor the intended interview and confirmation experience, also install the\nstructured-question companion:\n\n```bash\npi install npm:@juicesharp/rpiv-ask-user-question\n```\n\nIf pi was already open, run `/reload` in that session. GLLA works without the\nquestion companion through plain-text fallbacks, but structured questions are\nthe recommended experience.\n\n## Your first goal\n\nStart pi in the project you want it to work on, then just say what you want:\n\n```text\n/goal logins are broken, sort it out\n```\n\nThere is no required format — vagueness is fine. A plain seed leads into\na draft: GLLA researches the problem itself, asks focused questions at\ndynamic length to draw out whatever detail matters, and shows a Confirm\ndialog before anything activates. You never have to front-load the whole\nspec; the draft pulls it out of you. If your seed already carries enough\ndetail (alone or with the recent conversation), it skips the questions\nand goes straight to confirmation.\n\nWhen you already know the finish line, spell it out — a `Done when:`\ncontract starts directly and is independently audited at the end:\n\n```text\n/goal \"Improve the login flow.\n\nDone when:\n- failed logins return a useful, safe error;\n- the relevant tests cover the new behavior and pass;\n- the change is documented and committed.\"\n```\n\nBare `/goal` always interviews, `/goal plan \"...\"` always forces the full\nresearch-first draft, and `/goal start \"...\"` is the explicit shortcut for\nskipping the interview when that is intentional.\n\n### What happens next\n\n1. **Intake:** GLLA preserves the objective and its verification contract.\n2. **Research and planning:** the agent can inspect the repository, ask for\n   decisions that materially change scope, and propose bounded tasks.\n3. **Execution:** the main pi session keeps working after each agent turn;\n   optional subagents can handle parallel, focused work.\n4. **Durability:** goals, queue items, progress, pauses, retries, and audit\n   claims are written to inspectable state on disk.\n5. **Recovery:** provider failures, silent turns, session replacement, and\n   frozen workers are handled through bounded, visible recovery paths.\n6. **Verification:** `complete_goal` saves a claim, runs mechanical checks, and\n   queues a detached auditor. The goal archives only after the auditor accepts\n   evidence for the contract.\n\nThe status widget and `/glla status` show whether work is active, queued,\npaused, recovering, auditing, or waiting for an explicit decision. Silence is\nnot presented as progress.\n\n## Choose the work surface\n\nGLLA has three work shapes. Pick the one that matches the outcome rather than\nforcing every problem into a loop.\n\n| Surface | Use it for | Completion model |\n|---|---|---|\n| `/goal` | One meaningful outcome: feature, fix, audit, migration, research, or docs | The saved `Done when:` contract is independently audited |\n| `/list` | Several outcomes or a backlog of independently verifiable items | Each item is worked and audited separately; the queue advances safely |\n| `/loop` | Ongoing improvement with no single final item | A metric, specification, audit cadence, bound, or `/loop stop` ends the process |\n\n### `/goal`: one outcome\n\n```text\n/goal                                      # interview + Confirm\n/goal sort out logins                      # vague seed → draft draws out detail + Confirm\n/goal \"... Done when: ...\"                 # direct contract start\n/goal start \"...\"                          # explicit no-interview start\n/goal start                                  # use one clear recent request, or draft safely\n/goal plan \"...\"                           # research-first extended plan\n/goal status                               # inspect the current goal\n/goal pause                                # pause automatic continuation\n/goal resume                               # explicitly resume\n/goal verify                               # audit the current claim now\n/goal tweak \"...\"                          # revise the objective with Confirm\n/goal cancel                               # cancel the active goal\n```\n\nA goal is the best default for work with a finish line. If the agent discovers\nthat the objective is too large, it can propose a bounded task plan instead of\nquietly inventing an unbounded backlog.\n\n### `/list`: a durable work pool\n\n```text\n/list \"fix the cache. Done when: tests pass\"\n/list plan.md                              # import a checklist or plan file\n/list                                     # interview + Confirm for a context draft\n/list show                                # show active and waiting items\n/list start                                # activate the queued head, or draft one clear recent request\n/list next                                 # explicitly skip/activate the next item\n/list next <n>                             # explicitly choose a specific item\n/list resume                               # explicitly retry/resume the list\n/list remove <n>\n/list clear\n/list cancel                               # stop the active item and drop waiting items\n/list add <text...>                        # queue one item directly (no interview)\n/list import <file>                        # import a file: one Confirm for the whole batch\n```\n\nA pasted multi-line, bulleted, numbered, or checklist-style list keeps its\nitem wording and boundaries; GLLA does not ask for an “exact or refined” choice.\nOnly a genuinely ambiguous individual item needs clarification. The direct\n`/list add` path skips the interview but not consent: pasted text and files\nstill get one Confirm for the whole batch before anything is queued. The packaged\n`skills/glla-delegate/SKILL.md` records the safe normal-chat delegation path:\nexplicit queue requests may use `list_add`, while discovered follow-ups are\noffered first and durable goals remain Confirm-gated.\n\nOrder is the default, not the law. Automatic advance normally uses the head of\nthe queue, while `/list next <n>` or the agent's `list_activate` tool can choose\nanother item. Numbering always matches `/list show` output. After a list item is\napproved and archived, the next queued item starts automatically; no manual\n`/list next` is needed between items.\n\nIf a saved item is malformed or needs a repair, the repair card preserves the\nfull original target, explains the concrete recovery action, and permits one\nbounded bootstrap turn containing `propose_task_list`. Confirm the redraft;\nautomatic repeats are fenced. Use `/list resume` or `/glla resume` for an\nintentional retry of a waiting/restored queue, and `/list next` when you\nintentionally want to skip or choose another queued item. `/list start` is\nalso explicit: it activates the queued head, or, when the queue is empty, uses\none clear recent user request as a seed for the normal Confirm-gated list\ndrafting flow. Ambiguous context is never queued automatically.\n\n### `/loop`: an improvement process\n\n```text\n/loop                                     # interview + Confirm\n/loop start                                # use one clear recent target as an explicit metricless start\n/loop plan                                # research-first loop design\n/loop start \"reduce flaky tests\" measure=\"...\" direction=min\n/loop start \"keep improving the spec\" measure=none max=20 cadence=900\n/loop audit                               # recurring project-audit cadence\n/loop status\n/loop stop\n```\n\nBare `/loop start` infers only one clear recent target. It does not invent a\nmeasure, direction, bound, cadence, or branch setting; the command uses the\nexisting explicit metricless-start path. If the context is ambiguous, GLLA\nreturns to loop drafting so the target and any numeric metric/consent gates\nremain visible.\n\nThere are three loop styles:\n\n- **Metric:** a bounded command prints one number that honestly represents\n  progress, such as test failures or bundle size. GLLA test-runs the measure\n  before you confirm it and stops on plateau or a configured bound.\n- **Metricless specification:** no honest number exists, so the loop advances\n  a specification or checklist. It ends at its time/token/iteration bound or\n  `/loop stop`; it has no fake plateau metric. Add optional\n  `cadence=<seconds>` to put a minimum gap between successful automatic\n  iterations; explicit starts/resumes remain urgent and `/loop status` shows\n  the armed cadence.\n- **Project audit:** each iteration looks for the next important finding,\n  appends evidence to the audit ledger, and works through the findings.\n\nIf the work has a finish line, use `/goal`, not an endless loop.\n\n## The autonomy model\n\nGLLA is designed for **high-level autonomy with low-level accountability**.\nYou provide direction and acceptance criteria; the agent owns the ordinary\nresearch and implementation decisions; GLLA owns continuity, state, recovery,\nand verification.\n\n### What produces better results\n\n1. **Name the outcome, not a list of keystrokes.** Say what should be true\n   when the work is finished.\n2. **Make “done” inspectable.** Include tests, files, behavior, or user-visible\n   checks in the contract.\n3. **Give broad work room to research.** `/goal plan` is useful for greenfield\n   or ambiguous work; it researches before asking its deeper interview.\n4. **Let the agent decompose, but keep bounds.** Task plans have confirmation\n   and bounded task/subtask counts. A list item remains one auditable unit.\n5. **Use subagents for parallel leverage, not ceremony.** Spawn workers when\n   independent research or implementation can happen concurrently.\n6. **Treat the auditor as a gate, not as decoration.** A completion message is\n   a claim; acceptance requires evidence tied to the contract.\n\nAutonomy is intentionally not blind: Confirm dialogs, decision pauses,\nexplicit resume paths, bounded retries, and durable status keep important\ncontrol points visible.\n\n### What GLLA verifies\n\nWhen the agent calls `complete_goal`, GLLA:\n\n1. runs the contract's mechanical checks when a release or command check is\n   specified;\n2. refuses the claim before audit when committed tasks are still open\n   (tasks with a recorded deferral are exempt), naming each open task;\n3. writes an identity-bound completion claim;\n4. starts a detached, fresh pi RPC worker for the audit;\n5. asks the worker to inspect the repository and run bounded checks;\n6. requires raw evidence for each verification-contract item through the\n   orchestrator-side regression shield;\n7. keeps the goal open on infrastructure failure, missing evidence, or\n   disapproval instead of silently archiving it.\n\nThe auditor is intentionally isolated from the implementing conversation and\nGLLA extension state. It mirrors the session's extension packages by default\nso provider-extension models remain available; GLLA itself is excluded.\nDisable extension mirroring in `/glla` for an extension-less auditor and\nchoose a model usable in that configuration. Skills, prompt templates,\nthemes, and context files remain disabled. It is independent verification,\nnot an OS sandbox: the auditor's\n`bash` tool can still change files if a prompt or verifier tells it to. Keep\nverification commands bounded and treat repository permissions accordingly.\nOn Linux, both direct contract checks and the detached auditor enforce a\n256-process process-group ceiling to contain recursive helper/test launches;\ncross-platform timeout and process-tree cleanup remain in place as well.\n\n## Recommended pi extensions\n\nGLLA is the supervisor. These companions add capabilities around it:\n\n### Recommended for almost everyone\n\n- **`@juicesharp/rpiv-ask-user-question`**: structured questions, multi-select,\n  previews, and Confirm dialogs for drafting and decisions. GLLA has a prose\n  fallback, but this is the intended UX.\n\n### Recommended for power: parallel orchestration (`pi-subagents`)\n\n- **`pi-subagents`: the optional parallel-orchestration companion for GLLA.** Use it\n  when you want the best automation and quality: `runs.all` parallel fan-out,\n  `runs.lanes` worker→review→fix chains, `outputSchema` + `acceptance` structured\n  verification, `runs.host` gated shell, worktree isolation, model routing\n  (`subagents.defaultModel` / `subagentModelOverrides` / `modelScope`), durable\n  missions/schedules/recovery, and versioned control RPC. Built-ins are `scout`,\n  `researcher`, `worker`, `reviewer`, `oracle`, `delegate` plus external-CLI\n  writers (`claude-code-writer` etc.); all inherit the parent model by default\n  so there is no hidden Explore/Plan quota pool. This is the companion GLLA\n  supervises via `subagent:*` lifecycle events + durable `status.json` + versioned\n  stop RPC (ownership/generation-checked). GLLA's `subagentModelOverrides`\n  can still pin an individual role.\n\n  The main pi session remains the owner of the goal/list/loop; subagents are\n  workers and cannot silently replace the parent's objective. A short or mostly\n  sequential goal can still run cleanly without workers; install when\n  parallelism will pay for its coordination and model usage.\n\n  Display coexistence: pi-subagents renders its own inline run panels +\n  FleetView, GLLA renders one compact widget line + the status-bar worker\n  count + `/glla agents`. If you see the same run stacked 3× or panels\n  swapping order, set pi-subagents `inlineToolDisplay: \"summary\"` (one\n  stable row per run) and pin `fleetViewPlacement`; GLLA's own richness is\n  the `subagentDisplayRichness` setting (`/glla` → Subagents): `quiet`\n  (default: troubled workers + the count line; HUNG is never silent),\n  `compact` (count line), `rich` (all worker rows). Upstream triple-render report:\n  nicobailon/pi-subagents#1931.\n\nInstall the current companion (GLLA does not require a pinned version):\n\n```bash\npi install npm:pi-subagents\n```\n\nThe companion is installed separately; it is not a GLLA runtime dependency.\nOur development lockfile records the version used for reproducible checks,\nnot a version requirement for your Pi session. See\n[compatibility boundaries](docs/COMPATIBILITY.md).\n\nDo not install the older `@tintinweb/pi-subagents` provider alongside this\nrecommendation in the same session. Existing Tintin-era agent files are\ncleaned only when GLLA's management marker proves that GLLA owns them; old\nsettings are not silently remapped to a different role. Do not stack\n`@quintinshaw/pi-dynamic-workflows` as a competing orchestrator alongside\nGLLA + `pi-subagents` in the same session: duplicate tools and competing\norchestration events create ambiguous ownership. Use its quality helpers\n(`verify`/`judgePanel`/`loopUntilDry`) only as isolated complements if needed.\n\n### Useful, but optional\n\n- **`@pi-unipi/notify`**: Telegram, Gotify, or ntfy delivery when you need\n  alerts away from the desktop. GLLA's local notifications work without it;\n  when no command is configured, it auto-detects `notify-send`/`osascript`;\n  `notify=off` silences notifications.\n- **`pi-chrome`**: logged-in browser research and interaction when a goal needs\n  a real web session. It is not required for repository-only work.\n\n### What not to combine with GLLA\n\nThese are coexistence rules, not a ranking of other projects:\n\n- Do **not** run a second extension that also drives agent turns on\n  `agent_end` while GLLA owns the session. Two supervisors can schedule\n  contradictory continuations. Choose one driver for a session.\n- Do not run a second task/queue extension for the same work. GLLA's `/list`\n  already provides durable queue state, statuses, auto-advance, and an audit\n  trail. Keep a separate task manager only when you specifically need a\n  dependency DAG or another workflow outside GLLA.\n- Avoid overlapping compaction, retry, or watchdog supervisors while a GLLA\n  goal/list/loop is active; duplicate nudges make liveness harder to reason\n  about.\n- A ralph-style loop can remain installed, but do not run it simultaneously\n  with a GLLA-driven loop or goal in the same pi session.\n\n## State, recovery, and user control\n\n### State roots\n\nBy default, GLLA stores state in:\n\n```text\n<working-directory>/.pi-glla/\n```\n\n`/glla` offers an opt-in **State root → sessionDir** setting that uses pi's\ncanonical top-level session directory. The session root must be admitted by\nthe host lifecycle first. If it is unresolved, GLLA fails closed rather than\nrecreating ambiguous state under whichever directory happens to be current.\nChanging the root does not silently migrate or delete the old working-directory\ntree. Unreadable or invalid root settings defer writes and keep reads on the\nlast validated root; cold startup reports unresolved selection explicitly.\nRestoring valid settings lets persistence retry in the selected root.\n\nThe state is inspectable: active JSONL, goal markdown, queue state, audit jobs,\nledger history, and archived goals are kept under `.pi-glla/` (or the selected\nsession root). Repository audit findings remain repository-only; the npm package\nships the user-facing docs, not local audit history. The list-audit findings\nfile and its fan-out follow the same selected state root, including the\nopt-in `sessionDir` root.\n\n### Recovery behavior\n\nLong-running work encounters provider outages, context compaction, process\nreplacement, slow tools, and workers that stop making progress. GLLA records\nthese as state transitions and uses bounded recovery rather than pretending\nthat silence means success. Error text is **not trusted** to pick a retry policy;\nfailure wording is retained as bounded diagnostics, not interpreted as\nproof of a quota or billing state.\n\n- automatic retries are bounded and visible; a BUSY/no-stream turn is parked\n  and re-dispatched within the configurable **Zero-stream retries** budget\n  (default 3, range 0 to 10), then requires explicit resume;\n- `/goal resume`, `/list resume`, and `/loop resume` are explicit recovery\n  paths;\n- a user abort means stop, not “try again behind my back”;\n- a loaded objective can be displayed without injecting stale auditor context\n  until continuation consent exists;\n- frozen tracked subagents receive warning telemetry first and, after the\n  configured long threshold, at most one child-specific abort; the parent goal\n  is not aborted;\n- interrupted completion claims remain available for retry and inspection.\n\nUse `/glla pause` to freeze supervisor automation without killing active work,\n`/glla resume` to release it, `/glla bug [message]` to capture failure context to `bugs/` without touching durable goal state, and `/glla status` or `/goal status` to inspect\nwhat happened.\n\n### Settings worth knowing\n\nOpen `/glla` for the settings table. The most important choices are:\n\n- **Auditor model / thinking level:** the verifier's model and depth; when\n  unset, auditor thinking inherits the parent session dial (including `max`);\n- **Main-agent and auditor fallback models:** both roles use the same ordered,\n  deselectable, bounded fallback-chain picker for provider failures; the\n  auditor's session model remains the final last resort. Saving a non-empty\n  auditor chain also offers the thinking-level pick so the selection sticks;\n- **Auto-resume:** whether persisted work may restart automatically after a\n  session loads; explicit resume commands are always available;\n- **State root:** `workingDir` by default, opt-in `sessionDir`;\n- **Aggressive mode:** long-running keep-going defaults; explicit per-setting\n  choices win;\n- **Subagent hang escalation:** warning-only at `0`, or one child-specific\n  action after a confirmed frozen interval;\n- **Zero-stream retries:** automatic GLLA recovery attempts after a busy,\n  stream-silent Pi turn; `0` keeps recovery manual and `1 to 10` bounds repeats;\n- **Audit cap and retry cadence:** bounds for repeated objections and\n  infrastructure recovery.\n\nFor an attended first run, keep the default confirmation and inspect the\nstatus surfaces. For an unattended machine, configure auto-resume and notify\nbehavior deliberately rather than assuming a terminal left open is a\nsupervisor.\n\n## Model and auditor requirements\n\nThe main agent may use the model/provider you normally use in pi. The detached\nauditor starts a fresh pi process that mirrors your session's extension\npackages by default, so session-resolved models (including\nprovider-extension models) work there too; disable the mirror in `/glla`\nsettings if you want the fully isolated extension-less auditor. Choose an\nauditor model in `/glla` if the session model depends on something the\nworker cannot reach.\n\nThe worker inherits normal pi provider configuration and resolves `pi` from\n`PATH`. If needed, set:\n\n```bash\nGLLA_PI_BINARY=/absolute/path/to/pi\n```\n\nCredentials are not written into `.pi-glla/audit-jobs/` or command arguments.\nThe isolated worker is an evidence checker, not a second implementation agent.\n\n## From source and maintainer checks\n\nPrerequisites: Node `22.19.0+`, [Bun](https://bun.sh/) for the test runner,\npi-coding-agent, and TypeScript `5.9+`.\n\n```bash\ngit clone https://github.com/DraconDev/pi-goal-list-loop-audit.git\ncd pi-goal-list-loop-audit\npi install .\n```\n\nTry the local extension without installing it globally:\n\n```bash\npi -e /absolute/path/to/pi-goal-list-loop-audit\n```\n\nRun the checks used for a release:\n\n```bash\nnpm test\nnpm run check\nnpm run release:check\n```\n\n`npm test` runs the fast set (the full serialized suite minus the 12\nslowest files listed in `tests/slow-files.mjs`). `npm run test:slow` runs\nthose slow files, `npm run test:changed` runs only git-affected files,\nand `npm run test:all` runs everything. `npm run release:check` runs\nthe serialized Bun suite, TypeScript, the jiti reproduction, offline\nauditor-extension validation, and npm pack. The test count changes as\nregressions are added; the useful result is `0 fail`.\n\nFor design rationale, see [`docs/DESIGN.md`](docs/DESIGN.md). For the shipped\ndocument index, see [`docs/INDEX.md`](docs/INDEX.md). For publishing, see\n[`docs/RELEASING.md`](docs/RELEASING.md).\n\n### Maintainer source map\n\nThe implementation is intentionally split by lifecycle concern. Start here\nwhen tracing behavior:\n\n| Area | Entry points |\n|---|---|\n| Commands and UI | `extensions/goal-commands.ts`, `extensions/goal-loop-display.ts` |\n| State and roots | `extensions/goal-state.ts`, `extensions/glla-state-root.ts` |\n| Continuation and recovery | `extensions/goal-continuation.ts`, `extensions/goal-heartbeat.ts`, `extensions/goal-recovery.ts` |\n| Queue and lifecycle | `extensions/loops/goal-list-queue.ts`, `extensions/loops/goal-orchestrator.ts` |\n| Completion audit | `extensions/goal-loop-auditor-process.ts`, `extensions/loops/goal-auditor-hooks.ts`, `extensions/loops/goal-auditor-surface.ts` |\n| Auditor launcher | `scripts/goal-auditor-worker.mjs`, `scripts/goal-auditor-launch.d.mts` |\n| Safety boundaries | `extensions/payload-guard.ts`, `extensions/context-hygiene.ts` |\n| Tests and design | `tests/`, `docs/DESIGN.md`, `PLAN.md` |\n\nThe package contains the extension entry point\n`extensions/loops/goal.ts`, prompt templates, schemas, scripts, docs, examples,\nand the user-facing README/install/changelog files. The full test suite remains\nrepository material for maintainers and is exercised by `npm run test:all`; it is\nnot included in the published tarball. `audit/` and `.research/` are also\nrepository material, not first-use package content.\n\n## License\n\nGNU Affero General Public License v3.0-only; see [LICENSE](LICENSE).\n\nCompatibility and process limits: [COMPATIBILITY.md](docs/COMPATIBILITY.md).\nReliability metrics and opt-in canaries: [RELIABILITY-AND-MEASUREMENT.md](docs/RELIABILITY-AND-MEASUREMENT.md).\nGenerated runtime inventory: [RUNTIME-INVENTORY.md](docs/RUNTIME-INVENTORY.md).\n","readmeFilename":"README.md"}