Merge origin/master into codex/invariant-service-seam

# Conflicts:
#	docs/module-graph.md

.agents/notes/implemented/architecture/2026-07-19-package-invariant-runtime-contracts.i18n.yaml

@@ -2,5 +2,5 @@
 # side as of the last confirmed-consistent state. Both languages carry equal authority;
 # after editing either side, bring the other along and re-record with:
 #   pnpm run verify-translation-pairing --write
-2026-07-19-package-invariant-runtime-contracts.md: 80a2f41ee0b97026c145db4f884a99fe25479a76
-2026-07-19-package-invariant-runtime-contracts.zh.md: c440b682465fb8549f8e6c6c319129eb3954f7df
+2026-07-19-package-invariant-runtime-contracts.md: 3b1cf1e1a9c0985bb55a7a41089b39fed823a74f
+2026-07-19-package-invariant-runtime-contracts.zh.md: ca1f20b79b14446342fc663849d20a23ad5b501a

.agents/notes/implemented/architecture/2026-07-19-package-invariant-runtime-contracts.md

@@ -27,7 +27,7 @@ The central `dsh-invariants` service owns only configuration, registration uniqu
 
 ### Implemented checks
 
-The current 99-package workspace has 21 executable companions and 78 justified empty companions.
+The current 100-package workspace has 21 executable companions and 79 justified empty companions.
 
 | Owner | Runtime relationship |
 |---|---|

.agents/notes/implemented/architecture/2026-07-19-package-invariant-runtime-contracts.zh.md

@@ -27,7 +27,7 @@ Status: implemented
 
 ### 已实施的检查
 
-当前 99 个包的 workspace 包含 21 个可执行 companion 和 78 个有理由的空 companion。
+当前 100 个包的 workspace 包含 21 个可执行 companion 和 79 个有理由的空 companion。
 
 | 所有者 | 运行时关系 |
 |---|---|

.agents/notes/implemented/feature/2026-07-16-harness-level-loop.i18n.yaml

@@ -0,0 +1,6 @@
+# Bilingual-pair consistency record (docs/i18n/README.md): the git blob hash of each
+# side as of the last confirmed-consistent state. Both languages carry equal authority;
+# after editing either side, bring the other along and re-record with:
+#   pnpm run verify-translation-pairing --write
+2026-07-16-harness-level-loop.md: 9a9511b9dcea1b5fdc90f4fc716c4399f2346967
+2026-07-16-harness-level-loop.zh.md: 284e73051eaaa4633b9f56367de9096dadc8184e

.agents/notes/implemented/feature/2026-07-16-harness-level-loop.md

@@ -0,0 +1,129 @@
+# Agent Note: Harness-level goal-based execution
+
+Status: implemented
+
+English | [中文](2026-07-16-harness-level-loop.zh.md)
+
+## Problem
+
+The concrete agent loop owns one turn: it drains admitted input, performs one or more model-and-tool steps, and stops. Substantial objectives often need an outer policy that can begin another turn, retain progress, stop at a budget, and remain intelligible to humans. A timed prompt, a same-session continuation, and a fresh-agent Ralph attempt all repeat work, but they do not share the same state, authority, memory, or lifecycle.
+
+Treating every repeated action as one generic “loop” obscures those differences. Same-session work must persist the human objective in the existing transcript while preserving conversation context. Ralph work must intentionally discard conversation context and use the workspace plus a bounded handoff. Human-facing status must not imply that reopening a session silently authorizes more work. Completion and blocker claims also need an explicit trust boundary rather than being smuggled into a scheduler abstraction.
+
+The repository therefore needs goal-based execution above the turn/step loop, but it does not need a speculative universal loop service that combines persistence, evaluation, budgeting, scheduling, handoff, background tasks, and UI.
+
+## Decision
+
+This proposal is implemented in amended form as two explicit plugin policies over existing seams:
+
+1. **Same-session goals** retain one durable objective in the current session and admit goal-attributed continuation turns only while live activation is armed.
+2. **Fresh-agent Ralph runs** execute a fixed foreground workflow whose rounds each spawn a new structured child with no conversation seed.
+
+There is no `packages/loop/` family, `LoopDriver`, `LoopId`, universal `StopCondition`, or model-facing generic `loop` tool. The two policies share the repository's ordinary agent, session, tools, workflow, subagent, and UI extension seams, but they do not pretend that one lifecycle fits both.
+
+### Vocabulary and policy boundary
+
+The same-session hierarchy is **Goal → Goal Round → Turn → Step**. A goal round is one continuation cycle admitted for the current goal and materialized as one goal-sourced turn. Human or unrelated turns in the same session do not consume the goal-round cap, and a turn may still contain multiple model/tool steps.
+
+The fresh-agent hierarchy is **Ralph Run → Ralph Round → fresh child Turn → Step**. One Ralph round creates one child session. The parent transcript and prior child transcripts are not seed context; the shared workspace and one bounded structured report carry cross-round state.
+
+“Round” is therefore an outer policy iteration, not a synonym for every session turn. The concrete `dsh-agent-loop` remains the turn/step engine. The same-session driver uses public agent and session events; its only core addition is the generic observe-before-cancel `agent/cancel-requested` notification needed by any lifecycle policy that must settle cancellation safely.
+
+Time-based `/loop` or scheduled execution is a third policy and is not implemented by this decision. It belongs with a scheduler rather than either goal family.
+
+### Package topology and owning verbs
+
+| Package | Repository category | Owned structures and verbs |
+|---|---|---|
+| `@deepseek-ai/dsh-goal` | `packages/goal/goal/`, domain service | Owns `GoalId`, compare-and-set `GoalRef`, `GoalSnapshot`, four-state `GoalPhase`, structured `GoalBlockReason`, process-local `GoalActivation`, replay folding, and `get`, `create`, `edit`, `pause`, `resume`, `complete`, `block`, `clear`, and `disarm` verbs. |
+| `@deepseek-ai/dsh-tool-goal` | `packages/goal/tool-goal/`, model-facing consumer | Registers exclusive `get_goal`, `create_goal`, and `update_goal`; authenticates live turn provenance and narrows autonomous-round authority to completion or blocking reports with machine-routable reason codes. |
+| `@deepseek-ai/dsh-goal-session` | `packages/goal/goal-session/`, continuation policy | Reserves, fences, admits, attributes, settles, cancels, and quiescently drains same-session goal rounds without importing the concrete loop. |
+| `@deepseek-ai/dsh-commands` | `packages/ui/commands/`, UI registry | Owns `CommandDefinition`, discovery, scoped registration, direct dispatch, `CommandResult`, and request cancellation for human-only commands. |
+| `@deepseek-ai/dsh-command-goal` | `packages/goal/command-goal/`, human-command producer | Registers `/goal` status, creation, edit, pause, resume, and clear over the goal domain for TUI and ACP. |
+| `@deepseek-ai/dsh-tool-ralph` | `packages/workflow/tool-ralph/`, fixed workflow consumer | Registers `ralph({ objective, maxRounds? })`, validates the fresh structured provider and bounded `RalphRoundReport`, and returns `complete`, `blocked`, or `budget-limited`. |
+
+The detailed contracts live in the [goal-domain](2026-07-19-persisted-same-session-goal-domain.md), [model goal-tools](2026-07-19-model-facing-goal-tools.md), [goal-round driver](2026-07-19-same-session-goal-round-driver.md), [command registry](2026-07-19-plugin-command-registration.md), [human goal-command](2026-07-19-human-goal-command.md), and [Ralph workflow-tool](2026-07-19-fresh-agent-ralph-workflow-tool.md) Agent Notes.
+
+### Durable goal state and live authority
+
+One session has at most one current goal. Every non-clear mutation appends a full, versioned, model-visible goal snapshot through `Agent.inject()`; clear appends a revisioned tombstone. The session log is the only durable source of truth, so normal persistence, resume, compaction semantics, and `SessionStore.fork()` carry the goal without a second database or an artificial cancellation record.
+
+Durable phases are only `active`, `paused`, `blocked`, and `complete`. A blocked goal carries a required `GoalBlockReason` with a stable lower-kebab-case `code` and a non-empty human-readable `message`; usage limits, round exhaustion, model failures, and policy rejection are reason codes rather than extra lifecycle phases. Separate activation is `armed` or `disarmed` and is never persisted. Creation and explicit resume arm a goal; stop transitions, session start, fork replay, driver replacement, and driver teardown leave it disarmed.
+
+This separation makes session restoration observable and unsurprising. Reopening a session never starts goal work by itself. A later human prompt such as “continue”, “resume the goal”, or an equivalent request in any language gives the runtime-root model a new turn in which it may read the goal and call `update_goal(..., action: 'resume')`. `/goal resume` is the direct human-command path. The runtime authenticates that the request came from a live direct-human turn; prompt policy lets the model interpret whether the wording semantically authorizes creation or resumption.
+
+Forked sessions inherit the durable goal prefix because that is the natural replay result. The fork starts disarmed, so inheritance does not imply execution authority and no synthetic goal cancellation is inserted into history.
+
+`defaultMaxGoalRounds` is configurable and defaults to `256`. The cap counts only admitted goal rounds. `blockedAfterConsecutiveRounds` is separately configurable in the model-tool policy and defaults to `3`; it is a mechanical lower bound before an autonomous round may report a repeated blocker, not an evaluator of semantic sameness.
+
+### Same-session continuation
+
+The goal-round driver owns at most one pending reservation per exact live agent. It admits a reservation only when the goal is active and armed, the agent is idle, no competing human work exists, pending mutations are durable, the exact goal id/revision/round still matches, and downstream prompt policy accepts it. The prompt-submit fence checks those facts both before and after asynchronous listeners, preventing an edit, pause, human message, or unload race from admitting obsolete work.
+
+Only the durable goal-sourced `user/message` charges a round. Stale reservations become rejected zero-step turns without consuming the cap. A concurrent goal revision wins over settlement from an older round.
+
+Normal turn completion schedules another round only while the goal remains active, armed, and below its cap. Cancellation pauses. Rate limiting or quota exhaustion blocks with code `usage-limited`; cap exhaustion blocks with `round-limit`; queue failure uses `queue-failed`; turn errors, max-token stops, policy rejection, and unknown terminal results use their corresponding blocker codes. An independently composed request-recovery plugin may retry transient provider failures within that same turn; the goal driver never invents another round after an abnormal terminal outcome. A human can later authorize resume through ordinary language or `/goal resume`.
+
+### Human and model surfaces
+
+The human UX follows the compact Codex shape in the [public OpenAI Codex TUI dispatcher at commit `678157a`](https://github.com/openai/codex/blob/678157acaa819d5510adfe359abb5d0392cfe461/codex-rs/tui/src/chatwidget/slash_dispatch.rs#L750-L805): `/goal` shows status, `/goal <objective>` creates, and `edit`, `pause`, `resume`, or `clear` perform direct lifecycle actions. The commit permalink keeps the researched grammar verifiable as Codex evolves. Status includes durable phase, admitted/capped rounds, and live armed/disarmed activation. Direct status and command output do not enter model history; accepted domain mutations remain reconstructable because the goal service records them.
+
+The model receives only `get_goal`, `create_goal`, and `update_goal`. It may create a goal when a direct human request clearly asks for substantial multi-round work, and it may infer that intent in any language. It must not turn routine one-turn work into a goal. Direct-human provenance is enforced in code; semantic interpretation remains model judgment. An autonomous goal round may report `complete` or `blocked` for the exact current goal round but cannot edit, pause, resume, or replace the human objective.
+
+TUI and ACP mount the shared command registry and complete goal stack by default and expose `/goal` through one producer. Every effective registered command is discoverable and invocable through every composed command adapter; a plugin incompatible with an application omits its command producer from that composition rather than relying on registry-level surface masks. The UI-less agent spine is opt-in so one-shot callers do not silently become multi-round operations. The headless CLI and JSON-RPC front doors do not consume the command plane; ordinary human text can still authorize model goal tools when that stack is composed.
+
+### Fresh-agent Ralph execution
+
+Ralph is a first-class model tool in its own plugin, demonstrating that a sophisticated fixed execution policy can be composed without a new loop core. The plugin owns a fixed workflow script over `ctx.workflows` and `ctx.subagents`; it does not create session-goal state or add a branch to `dsh-agent-loop`.
+
+Each round uses an explicit `WorkflowStartRequest.subagentProvider`, defaulting to `spawn`. The provider must exist, support structured output, and declare that it does not inherit parent context. Ralph also passes its resolved round cap as `WorkflowStartRequest.maxTotalAgents`; the worker engine validates both per-run policies before publishing work, so provider misconfiguration or an engine ceiling below the requested Ralph scale fails before a run exists. The child inherits cwd and lineage but receives only the immutable objective, round/cap, workspace-as-authority instruction, and previous normalized report.
+
+A report contains status, summary, evidence, next steps, and blocker text. Status-specific invariants and serialized size are validated inside the fixed script and again at the consumer boundary. `maxRounds` is configurable, defaults to `256`, and is the ceiling for a call override. `maxHandoffChars` defaults to `16384`; oversized reports fail rather than being silently truncated. `maxResultChars` separately defaults to `16384` and bounds the complete successful parent-facing text, including its envelope and truncation marker.
+
+An ordinary child failure ends the run without retry. The fixed script reports the failed round and last successful handoff when one exists, and the tool returns that state as an error instead of misclassifying it as a malformed report or budget exhaustion. Fatal workflow infrastructure failures can settle before the script returns that state; richer reason transport and retry policy remain deferred.
+
+The tool is foreground and process-local. The parent tool call waits for the terminal result, propagates cancellation into the worker engine, and awaits `run.dispose()` so child work is quiescent before return. The model sees one call and one bounded successful terminal result or an error; completion and blocker envelopes explicitly say that a worker reported the outcome rather than presenting it as independent certification. Intermediate child conversations remain outside the parent transcript.
+
+### External design lineage
+
+Codex provides the minimal observable goal UX used here: a persistent chat-attached target with set, view, edit, pause, resume, and clear controls. This implementation adopts that discoverability while using this repository's event-sourced goal record, plugin scopes, and runtime authority checks.
+
+Current [Claude Code goals](https://code.claude.com/docs/en/goal) reinforce the distinction between a goal that starts another turn after the previous turn and a timed `/loop`. Claude Code also uses a separate small-model evaluator after each turn. This implementation adopts the policy distinction but intentionally does not copy that evaluator: evaluator inputs, tool access, deterministic checks, provider choice, isolation, and authority need a separately designed plugin contract rather than an implicit self-certification layer.
+
+External products are comparators, not compatibility targets. The local source studies informed the boundaries, while the shipped interfaces follow this repository's “everything is a plugin”, model-visible-is-logged, explicit default resolution, and quiescent teardown rules.
+
+### Verification
+
+The six owning Agent Notes record unit, integration, process, snapshot, cancellation, replay, and built-runtime coverage. The stack exercises strict goal-record folding, compare-and-set races, session fork inheritance, disarmed restoration, natural-language direct-human authority, configurable caps and blocked thresholds, exact goal-round attribution, adapter-wide command discovery, and transcript isolation. Shipped keyless snapshots cover model goal creation/inspection through the headless app, multi-round same-session lifecycle and cancellation through ACP, direct `/goal` status without a model turn, and two real Ralph rounds through the headless app. The Ralph snapshot boots the worker-thread engine, spawn provider, structured-output runtime, and agent loop, then inspects distinct unseeded child logs and exact one-way bounded handoff while pinning the parent stream. Focused real-stack tests additionally cover completion, blocker and round-limit outcomes, malformed and oversized reports, ordinary child failure with the last good handoff, one phase event, and cancellation to child quiescence. Package sources remain under the repository's per-file 100% coverage gate, and built-binary tests cover installed-artifact resolution. The implementation experience is recorded in the root testing policy: every non-trivial model- or human-visible change must carry a real-example keyless snapshot in the same PR rather than relying on package-only or mock-only fixture coverage.
+
+## Alternatives considered
+
+- **Implement the original universal loop capability seam** — rejected because `Evaluator`, `BudgetPolicy`, `RoundHandoff`, `GoalReflector`, background task ownership, persistence, and scheduling do not form one coherent mandatory abstraction. Building all of them before their first concrete consumers would create broad speculative surface and duplicate existing session, workflow, subagent, and task machinery.
+- **Implement only same-session goals** — rejected because fresh-context iteration is materially different and is a valuable demonstration of the plugin architecture. Ralph belongs as a fixed workflow consumer with explicit context reset.
+- **Put Ralph inside the goal-round driver** — rejected because same-session goals deliberately preserve one conversation while Ralph deliberately removes it. Combining them would make activation, replay, handoff, and UI state ambiguous.
+- **Treat a fork as a fresh Ralph child** — rejected because a fork carries a conversation prefix. Fresh children plus workspace state and one explicit report are easier to bound and replay without a synthetic cancel record.
+- **Copy Claude Code's evaluator into the first goal implementation** — rejected because a transcript-only model evaluator is one useful policy, not a generally trustworthy completion certificate. Deterministic evaluation and isolation must remain possible, so the evaluator is deferred until its authority and provider seam are designed.
+- **Automatically continue after session restore** — rejected because opening a session is observation, not authority to spend resources. Durable state is restored while activation waits for a new human prompt.
+- **Route `/goal` through the model** — rejected because status and explicit lifecycle controls should be deterministic, token-free UI actions; ordinary natural-language prompts remain the semantic model path.
+- **Modify the concrete agent loop with goal or Ralph modes** — rejected because public queue, prompt, session, cancellation, workflow, and subagent seams already support both policies. The generic cancel-requested observation is the only core coordination addition.
+
+## Consequences
+
+- Goal-based execution ships without one overloaded “loop” object: same-session continuation and fresh-agent iteration have explicit, separately testable contracts.
+- Durable goal history is replayable and forkable, while process-local activation prevents accidental work on resume.
+- Humans receive a small Codex-shaped UX; models receive a compact provenance-checked tool surface; deployments can remove either independently.
+- Ralph demonstrates a nontrivial fixed policy entirely as a plugin over existing workflow and subagent primitives.
+- Round limits are generous by default but remain deployment-controlled. They bound iterations, not tokens, price, elapsed time, or external side effects.
+- The original proposal's evaluator, budget, reflector, background-task, CLI, and generic loop-session architecture is intentionally not part of the implemented public surface.
+
+## Known limitations and deferred work
+
+- **Independent evaluation** — same-session completion/blocking and Ralph terminal status are model or worker declarations. A separate evaluator, evaluator-driven feedback round, completion certificate, deterministic checker, adversarial verifier, and criteria/executor/isolation contract remain deferred.
+- **Aggregate budgets** — `maxGoalRounds` and Ralph `maxRounds` are the only aggregate effort limits. Token, currency, elapsed-time, provider-usage, and per-round price admission policies are absent.
+- **No persistent autonomous runner** — same-session goal facts persist, but activation and scheduling are process-local and deliberately wait for human input after restore. Ralph runs are foreground and cannot resume after process loss. Background collection, restart recovery, and unattended resident execution are deferred.
+- **No time scheduler** — interval `/loop`, cron, proactive maintenance, and cloud or desktop scheduling are outside this decision.
+- **No generic loop journal or execution-world rewind** — session replay reconstructs model-visible goal history, not prior files, processes, environment, credentials, or external side effects. Ralph treats the current workspace as authority and carries no cross-run journal.
+- **No goal reflector** — concern events, automatic no-progress heuristics, goal revision by an independent reflector, stuck-pattern detection, and `loop_split` are not implemented. Humans can edit, pause, clear, or resume the goal directly.
+- **Ralph policy remains narrow** — one round creates one fresh child; within-round fan-out, evaluator/worker role separation, dynamic provider/model selection, and structural recursive-Ralph tool denial need separate policy surfaces. Prompt guidance is not enforcement.
+- **Ralph does not retry a failed child** — an ordinary failure preserves the failed round and last good handoff, while fatal workflow infrastructure failures can end before that state is available. Retry count, backoff, and richer failure transport need separate policy and seam design.
+- **Portable UI remains modest** — TUI and ACP render plain-text goal status and generic Ralph cards. There is no continuous status widget, reconnectable command output, modal goal editor, or command plane in the headless CLI or JSON-RPC front doors.

.agents/notes/implemented/feature/2026-07-16-harness-level-loop.zh.md

@@ -0,0 +1,129 @@
+# Agent Note: Harness 层目标式执行
+
+Status: implemented
+
+[English](2026-07-16-harness-level-loop.md) | 中文
+
+## 问题
+
+具体 agent loop 只拥有一个 Turn：它排空已接纳输入，执行一个或多个模型与工具 Step，然后停止。大型目标通常需要一项外层策略来开始另一个 Turn、保留进度、在预算处停止，并让人类能够理解其状态。定时提示词、同会话续行和全新 agent Ralph 尝试都会重复工作，但它们并不共享相同的状态、权限、记忆或生命周期。
+
+若把每种重复动作都称为一个通用“loop”，就会掩盖这些差异。同会话工作必须在现有转录中持久化人类目标，同时保留对话上下文。Ralph 工作必须有意丢弃对话上下文，只使用工作区和一份有界交接。面向人类的状态不能暗示重新打开会话就会静默授权更多工作。完成与阻塞声明也需要显式信任边界，而不能被偷渡进调度器抽象。
+
+因此，本仓库需要位于 Turn/Step loop 之上的目标式执行，但不需要一个把持久化、评估、预算、调度、交接、后台任务和 UI 组合在一起的推测性通用 loop 服务。
+
+## 决策
+
+本提案以修订后的形式实现为构建在现有接缝之上的两项显式插件策略：
+
+1. **同会话目标**在当前会话中保留一个持久目标，并且只在实时激活态已激活时接纳带目标归属的续行 Turn。
+2. **全新 agent Ralph 运行**执行一个固定前台工作流，其中每个 Round 都生成一个不带对话种子的全新结构化子 agent。
+
+系统中没有 `packages/loop/` 包族、`LoopDriver`、`LoopId`、通用 `StopCondition` 或面向模型的通用 `loop` 工具。两项策略共享本仓库普通的 agent、session、tools、workflow、subagent 与 UI 扩展接缝，但不会假装一种生命周期可以同时适配两者。
+
+### 词汇与策略边界
+
+同会话层级是 **Goal → Goal Round → Turn → Step**。一个 Goal Round 是为当前目标接纳的一次续行周期，并实体化为一个带目标来源的 Turn。同一会话中的人类 Turn 或无关 Turn 不会消耗目标回合上限，而一个 Turn 仍可包含多个模型/工具 Step。
+
+全新 agent 层级是 **Ralph Run → Ralph Round → fresh child Turn → Step**。一个 Ralph Round 创建一个子会话。父转录和此前子转录都不是种子上下文；共享工作区与一份有界结构化报告承载跨 Round 状态。
+
+因此，“Round”是外层策略迭代，不是每个会话 Turn 的同义词。具体 `dsh-agent-loop` 仍是 Turn/Step 引擎。同会话驱动器使用公开 agent 与 session 事件；它对核心唯一的新增项是通用的取消前观察通知 `agent/cancel-requested`，任何需要安全收敛取消的生命周期策略都可以使用它。
+
+基于时间的 `/loop` 或定时执行是第三种策略，本决策不实现它。它应归属于调度器，而不是任一目标包族。
+
+### 包拓扑与所属动词
+
+| 包 | 仓库类别 | 所属结构与动词 |
+|---|---|---|
+| `@deepseek-ai/dsh-goal` | `packages/goal/goal/`，领域服务 | 拥有 `GoalId`、比较并交换 `GoalRef`、`GoalSnapshot`、四状态 `GoalPhase`、结构化 `GoalBlockReason`、进程本地 `GoalActivation`、重放折叠，以及 `get`、`create`、`edit`、`pause`、`resume`、`complete`、`block`、`clear` 与 `disarm` 动词。 |
+| `@deepseek-ai/dsh-tool-goal` | `packages/goal/tool-goal/`，面向模型消费者 | 注册互斥的 `get_goal`、`create_goal` 与 `update_goal`；认证实时 Turn 来源，并把自治 Round 权限收窄到带机器可路由原因代码的完成或阻塞报告。 |
+| `@deepseek-ai/dsh-goal-session` | `packages/goal/goal-session/`，续行策略 | 在不导入具体 loop 的情况下，预留、设围栏、接纳、归属、结算、取消并静止排空同会话目标回合。 |
+| `@deepseek-ai/dsh-commands` | `packages/ui/commands/`，UI 注册表 | 拥有面向人类专用命令的 `CommandDefinition`、发现、作用域注册、直接分发、`CommandResult` 与请求取消。 |
+| `@deepseek-ai/dsh-command-goal` | `packages/goal/command-goal/`，人类命令生产方 | 为 TUI 和 ACP 注册构建在目标领域之上的 `/goal` 状态、创建、编辑、暂停、恢复与清除。 |
+| `@deepseek-ai/dsh-tool-ralph` | `packages/workflow/tool-ralph/`，固定工作流消费者 | 注册 `ralph({ objective, maxRounds? })`，验证全新结构化 provider 与有界 `RalphRoundReport`，并返回 `complete`、`blocked` 或 `budget-limited`。 |
+
+详细契约分别由[目标领域](2026-07-19-persisted-same-session-goal-domain.md)、[模型目标工具](2026-07-19-model-facing-goal-tools.md)、[目标回合驱动器](2026-07-19-same-session-goal-round-driver.md)、[命令注册表](2026-07-19-plugin-command-registration.md)、[人类目标命令](2026-07-19-human-goal-command.md)与 [Ralph 工作流工具](2026-07-19-fresh-agent-ralph-workflow-tool.md) Agent Note 拥有。
+
+### 持久目标状态与实时权限
+
+一个会话至多有一个当前目标。每次非清除变更都通过 `Agent.inject()` 追加一份完整、带版本且模型可见的目标快照；清除会追加带修订号的墓碑。会话日志是唯一持久事实来源，因此普通持久化、恢复、压缩语义与 `SessionStore.fork()` 会携带目标，无需第二个数据库或人为取消记录。
+
+持久阶段只有 `active`、`paused`、`blocked` 与 `complete`。阻塞目标必须携带 `GoalBlockReason`，其中包含稳定的小写 kebab-case `code` 与非空的人类可读 `message`；用量限制、Round 耗尽、模型失败与策略拒绝都是原因代码，而不是额外生命周期阶段。独立激活态是 `armed` 或 `disarmed`，且永不持久化。创建与显式恢复会激活目标；停止转换、会话启动、fork 重放、驱动器替换和驱动器拆卸都会让目标保持未激活。
+
+这种分离让会话恢复可观察且符合直觉。重新打开会话绝不会自行开始目标工作。随后的人类提示词，例如“继续”、“恢复目标”或任何语言中的等价请求，会给运行时根 agent 的模型一个新 Turn；模型可在其中读取目标并调用 `update_goal(..., action: 'resume')`。`/goal resume` 是直接人类命令路径。运行时认证请求来自实时直接人类 Turn；提示策略让模型解释措辞在语义上是否授权创建或恢复。
+
+fork 会话会继承持久目标前缀，因为这是自然的重放结果。fork 从未激活状态开始，因此继承不等于执行权限，历史中也不会插入合成目标取消。
+
+`defaultMaxGoalRounds` 可配置且默认为 `256`。该上限只计算已接纳目标回合。`blockedAfterConsecutiveRounds` 在模型工具策略中单独配置且默认为 `3`；它只是在自治 Round 报告重复阻塞前的机械下限，不是对语义相同性的评估器。
+
+### 同会话续行
+
+目标回合驱动器为每个准确实时 agent 至多拥有一个待定预留。只有目标处于活跃且已激活状态、agent 空闲、不存在竞争性人类工作、待定变更已经持久、准确目标 id/修订号/Round 仍匹配，并且下游提示词策略接受时，它才会接纳预留。prompt-submit 围栏在异步监听器前后都检查这些事实，防止编辑、暂停、人类消息或卸载竞争接纳过时工作。
+
+只有持久的目标来源 `user/message` 会计入一个 Round。过时预留会成为未消耗上限的零 Step 拒绝 Turn。并发目标修订会胜过旧 Round 的结算。
+
+普通 Turn 完成后，只有目标仍活跃、已激活且低于上限时才会安排另一个 Round。取消会暂停。速率限制或配额耗尽以代码 `usage-limited` 阻塞；上限耗尽使用 `round-limit`；队列失败使用 `queue-failed`；Turn 错误、max-token 停止、策略拒绝与未知终止结果使用各自对应的阻塞代码。独立组合的请求恢复插件可以在同一个 Turn 内重试暂时性 provider 失败；目标驱动器绝不会在异常终止结果后凭空发起另一个 Round。人类随后可以通过普通语言或 `/goal resume` 授权恢复。
+
+### 人类与模型表面
+
+人类 UX 遵循 [OpenAI Codex 在提交 `678157a` 时的公开 TUI 分发器](https://github.com/openai/codex/blob/678157acaa819d5510adfe359abb5d0392cfe461/codex-rs/tui/src/chatwidget/slash_dispatch.rs#L750-L805)中的紧凑形态：`/goal` 显示状态，`/goal <objective>` 创建目标，而 `edit`、`pause`、`resume` 或 `clear` 执行直接生命周期操作。该提交永久链接让研究所得语法在 Codex 演进时仍可验证。状态包含持久阶段、已接纳/上限 Round 数以及实时已激活/未激活状态。直接状态与命令输出不会进入模型历史；已接受领域变更仍可重建，因为目标服务会记录它们。
+
+模型只接收 `get_goal`、`create_goal` 和 `update_goal`。当直接人类请求清楚要求大量多 Round 工作时，模型可以创建目标，并且可以从任何语言推断该意图。它不得把日常单 Turn 工作变成目标。直接人类来源由代码强制执行；语义解释仍是模型判断。自治目标 Round 可以为准确当前目标 Round 报告 `complete` 或 `blocked`，但不能编辑、暂停、恢复或替换人类目标。
+
+TUI 与 ACP 默认挂载共享命令注册表和完整目标栈，并通过同一个生产方暴露 `/goal`。每条有效已注册命令都能被每个已组合的命令适配器发现和调用；若插件与某应用不兼容，该应用组合会省略其命令生产方，而不是依赖注册表层面的表面掩码。无 UI agent spine 要求显式选择加入，以免单次调用方静默变成多 Round 操作。无头 CLI 与 JSON-RPC 前端不消费命令平面；挂载目标栈后，普通人类文本仍可授权模型目标工具。
+
+### 全新 agent Ralph 执行
+
+Ralph 是位于自有插件中的一等模型工具，展示了复杂固定执行策略可以在没有新 loop 核心的情况下组合完成。该插件拥有构建在 `ctx.workflows` 与 `ctx.subagents` 之上的固定工作流脚本；它不会创建会话目标状态，也不会为 `dsh-agent-loop` 增加分支。
+
+每个 Round 都使用显式 `WorkflowStartRequest.subagentProvider`，默认为 `spawn`。该 provider 必须存在、支持结构化输出，并声明不继承父上下文。Ralph 还会把解析后的 Round 上限作为 `WorkflowStartRequest.maxTotalAgents` 传递；工作线程引擎会在发布工作前验证两项每次运行策略，因此 provider 配置错误或低于所请求 Ralph 规模的引擎上限会在运行存在前失败。子 agent 继承 cwd 与谱系，但只接收不可变目标、当前 Round/上限、以工作区为权威的指令和上一份规范化报告。
+
+报告包含状态、摘要、证据、下一步与阻塞文本。固定脚本内部和消费者边界都会验证状态专用不变量与序列化大小。`maxRounds` 可配置，默认为 `256`，并作为调用覆盖值的上限。`maxHandoffChars` 默认为 `16384`；过大报告会失败，而不会被静默截断。`maxResultChars` 单独默认为 `16384`，并限制面向父级的完整成功文本，包括外层文本与截断标记。
+
+普通子 agent 失败会结束运行且不重试。固定脚本会报告失败 Round，并在存在时带回上一份成功交接；工具会把该状态作为错误返回，而不会误判为畸形报告或预算耗尽。致命工作流基础设施错误可能在脚本返回该状态前结算；更丰富的原因传输与重试策略均予以延期。
+
+该工具位于前台且只存在于进程内。父工具调用等待终止结果，把取消传播到工作线程引擎，并等待 `run.dispose()`，因此返回前子工作已达到静止。模型只看到一次调用，以及一份有界成功终止结果或一个错误；完成与阻塞的外层文本会明确说明结果由工作者报告，而不会呈现为独立认证。中间子 agent 对话不会进入父转录。
+
+### 外部设计谱系
+
+Codex 提供了这里采用的最小可观察目标 UX：一个附着于聊天的持久目标，以及设置、查看、编辑、暂停、恢复与清除控制。本实现采用这种可发现性，但使用本仓库的事件溯源目标记录、插件作用域与运行时权限检查。
+
+当前 [Claude Code goals](https://code.claude.com/docs/en/goal) 进一步验证了“前一 Turn 后启动另一 Turn 的目标”和定时 `/loop` 之间的区别。Claude Code 还会在每个 Turn 后使用独立小模型评估器。本实现采用策略区分，但有意不复制该评估器：评估器输入、工具访问、确定性检查、provider 选择、隔离与权限需要单独设计的插件契约，而不是隐式自我认证层。
+
+外部产品只是比较对象，不是兼容目标。本地源码研究帮助确定边界，而交付接口遵循本仓库“一切皆插件”、模型可见即可记录、显式解析默认值与静止拆卸规则。
+
+### 验证
+
+六份所属 Agent Note 记录了单元、集成、进程、快照、取消、重放与构建后运行时覆盖。该栈验证严格目标记录折叠、比较并交换竞争、会话 fork 继承、恢复后未激活、自然语言直接人类权限、可配置上限与阻塞阈值、准确目标回合归属、适配器范围的命令发现与转录隔离。已发布的无密钥快照覆盖通过无头应用创建/检查模型目标、通过 ACP 执行多 Round 同会话生命周期与取消、无需模型 Turn 的直接 `/goal` 状态，以及通过无头应用执行两个真实 Ralph Round。Ralph 快照会启动工作线程引擎、spawn provider、结构化输出运行时与 agent loop，随后检查互不相同且无种子的子日志和准确单向有界交接，同时固定父级事件流。聚焦的真实栈测试还覆盖完成、阻塞与 Round 上限结果、畸形及过大报告、保留上一份有效交接的普通子 agent 失败、单个阶段事件，以及取消后达到子 agent 静止状态。包源码继续受仓库逐文件 100% 覆盖率门禁约束，构建后二进制测试覆盖已安装产物解析。实现经验已记录进根测试策略：每项非平凡的模型或人类可见变更都必须在同一 PR 中携带真实示例无密钥快照，而不能依赖仅包级或仅模拟夹具的覆盖。
+
+## 考虑过的替代方案
+
+- **实现原始通用 loop 能力接缝**——不予采纳，因为 `Evaluator`、`BudgetPolicy`、`RoundHandoff`、`GoalReflector`、后台任务所有权、持久化与调度并不构成一项一致的必选抽象。在出现首个具体消费者前全部构建，会产生宽泛推测性表面，并重复现有 session、workflow、subagent 与 task 机制。
+- **只实现同会话目标**——不予采纳，因为全新上下文迭代在实质上不同，也是插件架构的重要示范。Ralph 应作为带显式上下文重置的固定工作流消费者。
+- **把 Ralph 放进目标回合驱动器**——不予采纳，因为同会话目标有意保留一段对话，而 Ralph 有意移除对话。合并两者会让激活、重放、交接与 UI 状态含糊不清。
+- **把 fork 当成全新 Ralph 子 agent**——不予采纳，因为 fork 会携带对话前缀。全新子 agent 加工作区状态与一份显式报告更容易限制和重放，并且无需合成取消记录。
+- **把 Claude Code 评估器复制进首个目标实现**——不予采纳，因为只读取转录的模型评估器是一项有用策略，但不是普遍可信的完成证书。系统必须仍能支持确定性评估与隔离，因此评估器延期到其权限与 provider 接缝完成设计之后。
+- **会话恢复后自动续行**——不予采纳，因为打开会话是观察行为，不是花费资源的权限。系统恢复持久状态，而激活态等待新的人类提示词。
+- **通过模型路由 `/goal`**——不予采纳，因为状态与显式生命周期控制应是确定、零 token 的 UI 操作；普通自然语言提示词仍是语义模型路径。
+- **为具体 agent loop 增加目标或 Ralph 模式**——不予采纳，因为公开队列、提示词、会话、取消、工作流与 subagent 接缝已经支持两项策略。通用 cancel-requested 观察是唯一核心协调新增项。
+
+## 后果
+
+- 目标式执行在没有单个过载“loop”对象的情况下交付：同会话续行与全新 agent 迭代拥有显式、可独立测试的契约。
+- 持久目标历史可以重放和 fork，而进程本地激活态会防止恢复时意外开始工作。
+- 人类获得小型 Codex 形态 UX；模型获得紧凑、带来源检查的工具表面；部署可以独立移除任一能力。
+- Ralph 展示了非平凡固定策略可以完全作为现有 workflow 与 subagent 原语之上的插件实现。
+- Round 上限默认宽裕，但仍由部署控制。它限制迭代次数，不限制 token、价格、耗时或外部副作用。
+- 原始提案中的评估器、预算、反思器、后台任务、CLI 与通用 loop-session 架构有意不进入已实现公开表面。
+
+## 已知限制与延期工作
+
+- **独立评估**——同会话完成/阻塞和 Ralph 终止状态都是模型或工作者声明。独立评估器、评估器驱动反馈 Round、完成证书、确定性检查器、对抗式 verifier 与 criteria/executor/isolation 契约均予以延期。
+- **聚合预算**——`maxGoalRounds` 与 Ralph `maxRounds` 是唯一聚合工作量限制。token、货币、耗时、provider 用量与逐 Round 价格准入策略均不存在。
+- **没有持久自治运行器**——同会话目标事实会持久化，但激活与调度只存在于进程内，并且有意在恢复后等待人类输入。Ralph 位于前台，进程丢失后无法恢复。后台收集、重启恢复与无人值守常驻执行均予以延期。
+- **没有时间调度器**——间隔 `/loop`、cron、主动维护以及云端或桌面调度不在本决策范围内。
+- **没有通用 loop 日志或执行世界回退**——会话重放会重建模型可见目标历史，而不会恢复此前文件、进程、环境、凭据或外部副作用。Ralph 把当前工作区作为权威，并且没有跨运行日志。
+- **没有目标反思器**——concern 事件、自动无进展启发式、由独立反思器执行的目标修订、卡住模式检测与 `loop_split` 均未实现。人类可以直接编辑、暂停、清除或恢复目标。
+- **Ralph 策略仍然狭窄**——一个 Round 创建一个全新子 agent；Round 内扇出、评估器/工作者角色分离、动态 provider/模型选择与结构化递归 Ralph 工具禁止都需要独立策略表面。提示词指导不是强制执行。
+- **Ralph 不会重试失败的子 agent**——普通失败会保留失败 Round 与上一份有效交接，而致命工作流基础设施错误可能在该状态可用前结束。重试次数、退避与更丰富的失败传输需要独立的策略与接缝设计。
+- **可移植 UI 仍较朴素**——TUI 与 ACP 渲染纯文本目标状态和通用 Ralph 卡片。系统没有持续状态组件、可重连命令输出、模态目标编辑器，无头 CLI 与 JSON-RPC 前端也没有命令平面。

.agents/notes/implemented/feature/2026-07-19-fresh-agent-ralph-workflow-tool.i18n.yaml

@@ -0,0 +1,6 @@
+# Bilingual-pair consistency record (docs/i18n/README.md): the git blob hash of each
+# side as of the last confirmed-consistent state. Both languages carry equal authority;
+# after editing either side, bring the other along and re-record with:
+#   pnpm run verify-translation-pairing --write
+2026-07-19-fresh-agent-ralph-workflow-tool.md: c2db4d7dd30c27a25adecdfc425db261cc3dfeb5
+2026-07-19-fresh-agent-ralph-workflow-tool.zh.md: e33e9848d71c98c8f83494ebe8bf171ef10b9305

.agents/notes/implemented/feature/2026-07-19-fresh-agent-ralph-workflow-tool.md

@@ -0,0 +1,74 @@
+# Agent Note: Fresh-agent Ralph workflow tool
+
+Status: implemented
+
+English | [中文](2026-07-19-fresh-agent-ralph-workflow-tool.zh.md)
+
+## Problem
+
+Same-session goals preserve conversation and let one agent continue a durable objective, while the general workflow tool lets the model write a fan-out orchestration script. Neither is the Ralph pattern: repeatedly give the same objective to a completely fresh worker, use the shared workspace as long-term memory, and carry only a small explicit handoff until work completes or a limit is reached.
+
+Adding Ralph behavior to `dsh-agent-loop`, the goal driver, or the public model-written workflow language would couple one policy to unrelated execution machinery. Letting each child inherit the parent conversation would also defeat context reset and make replay depend on a growing implicit prefix. The feature needs a fixed, reviewable policy built from existing plugin primitives, with cancellation quiescence, bounded cross-round data, a generous configurable cap, and no novel human-facing goal state.
+
+## Decision
+
+Add `@deepseek-ai/dsh-tool-ralph` as a separate consumer package under `packages/workflow/`. It registers `ralph({ objective, maxRounds? })`, owns a fixed workflow script, and depends only on `ctx.tools`, `ctx.systemPrompt`, `ctx.workflows`, and `ctx.subagents`. A Ralph run is not a session goal, creates no goal state, and requires no branch in the concrete agent loop.
+
+The tool is foreground-only. The calling agent parents every child for cwd and lineage, the parent tool call waits for the complete run, and the parent step's abort signal cancels the workflow. `run.dispose()` is awaited on every path, so cancellation reaches the worker engine's bounded settlement and child quiescence before the call returns.
+
+### Per-run workflow provider route
+
+`WorkflowStartRequest` gains optional `subagentProvider`. The worker-thread engine resolves that explicit per-run value before falling back to its configured provider, requires the selected normalized route to be registered before publishing the run, and uses it for every `agent()` call. The script cannot observe or replace this route. The ordinary `workflow` tool leaves the field unset and exposes no new model argument, so general workflow behavior and provider policy stay unchanged.
+
+The Ralph plugin's `subagentProvider` defaults to `spawn`. Immediately before a call it requires the named provider to exist, support structured output, and report `inheritsParentContext: false`; a fork-like or incapable provider fails loudly before workflow start. Provider lookup remains call-time because effect-scoped provider registration can change under HMR.
+
+### Per-run workflow child ceiling
+
+`WorkflowStartRequest` also gains optional `maxTotalAgents`. The worker-thread engine requires a positive safe integer no greater than its configured deployment ceiling and installs the resolved value in that run's worker limits before publishing the run. Ralph passes its resolved `maxRounds` as this ceiling, so the fixed loop's round budget and the generic runaway-child backstop cannot disagree. The ordinary workflow tool leaves the field unset and keeps the engine default.
+
+### Ralph rounds and handoff
+
+The hierarchy is Ralph Run → Ralph Round → fresh child Turn → Step. One Ralph round creates exactly one child through the selected provider. Spawn gives that child a distinct session with no seed while preserving the parent's cwd, so the shared working tree is the durable authority and neither parent conversation nor prior child history enters the request.
+
+The fixed prompt passes only the immutable objective, current round and cap, a workspace-as-authority instruction, and the previous structured report. A `RalphRoundReport` contains `status: continue | complete | blocked`, `summary`, `evidence`, `nextSteps`, and `blocker`. Strings must be normalized; `continue` requires next steps and no blocker, `complete` requires evidence with no next steps or blocker, and `blocked` requires a concrete blocker. The script validates semantics and serialized size before the report can become the next handoff; the consumer validates the materialized terminal value again across the workflow seam.
+
+`maxRounds` defaults to `256` and is also the deployment ceiling for a call override. `maxHandoffChars` and `maxResultChars` each default to `16384`. All are positive safe-integer config values. Oversized handoffs fail rather than being silently truncated; `maxResultChars` separately bounds the complete successful parent-facing text, including its envelope and truncation marker, without changing cross-round state. After a `continue` report at the last permitted round, the fixed script returns `budget-limited`; `complete` and `blocked` return immediately with the final report and number of rounds started.
+
+The workflow language maps a normally settled but unsuccessful child to `null`. The fixed script detects that value before report validation and returns `round-failed` with the failed round plus the last successful handoff when one exists; the tool turns it into an error instead of misclassifying it as a malformed report or budget exhaustion. Ralph adds no retry policy. Fatal provider-start, transport, worker, and workflow errors remain generic workflow failures because the workflow seam does not carry a recoverable child report on those paths.
+
+### Model and UI surface
+
+The model may supply only `objective` and optional `maxRounds`; provider selection, report schema, handoff cap, and script are deployment-owned. A fixed prompt section says to use `ralph` only when the direct human explicitly asks for Ralph or fresh-agent iteration, and distinguishes it from same-session goals, bounded delegation, and general fan-out workflows. This is guidance rather than a new goal UX state machine.
+
+ACP and terminal presentation use a generic `ralph` card whose raw input is the objective. Successful completion and blocker envelopes say that a worker reported the outcome rather than presenting it as independent certification. The parent transcript retains the original tool call and one bounded successful terminal report or an error, not intermediate child messages. Shipped headless, TUI, and ACP compositions load the plugin beside the existing workflow engine; JSON-RPC remains unchanged because its default composition does not expose workflows.
+
+## Testing
+
+Unit tests cover config and call-cap resolution, provider capability rejection, fixed start-request routing and child ceiling, all successful terminal outcomes, ordinary child-failure envelopes, malformed and oversized boundary values, exact successful-result truncation, abort timing, disposal, render intent, prompt lifecycle, and namespace-plugin shape at per-file 100% coverage. Worker-engine tests prove synchronous provider-route validation, per-run child ceilings below the deployment ceiling, and that a provider override selects every child without changing the configured default, including the built `lib/worker.cjs` under plain Node.
+
+A keyless real-stack integration drives the fixed script through the actual worker-thread engine, spawn provider, structured-output runtime, and agent loop. It proves distinct child identities, absent `seedLength`, inherited cwd, no parent-history markers in either child request, exact previous-report handoff only in the following round, one phase event, terminal completion, and disposal of both children. The same real stack covers blocker and round-limit outcomes, unnormalized and semantically invalid reports, oversized handoffs, ordinary child failure with the last good handoff, and cancellation to child quiescence. A shipped keyless headless snapshot additionally boots the real `examples/headless-agent` composition, invokes `ralph`, pins the parent stream transcript, and inspects persisted logs for two distinct unseeded child sessions and the round-one handoff appearing only in round two. Tool tests pin generic call/result presentation, while ACP replay header snapshots pin the shipped schema and prompt-guidance transcript surface.
+
+## Alternatives considered
+
+- **Put Ralph in the same-session goal driver** — rejected because goal rounds intentionally preserve one conversation, while Ralph's defining property is a fresh context per round; combining them would make goal lifecycle and child orchestration inseparable.
+- **Expose a `fresh` or loop flag on the general workflow tool** — rejected because the model-written script surface should remain general and provider-neutral; Ralph's fixed report protocol and stop policy deserve one reviewable consumer.
+- **Use `subagent_fork` for replay convenience** — rejected because inherited completed turns are implicit, growing handoff state and violate the fresh-context contract. The workspace plus one structured report is replayable without inserting artificial cancellation records.
+- **Call the subagent seam directly from the tool** — rejected because the existing workflow engine already owns foreground orchestration, structured children, cancellation propagation, worker termination, events, and quiescent disposal. Reusing it demonstrates plugin composition instead of building a second loop runtime.
+- **Silently truncate a large report** — rejected because truncation can remove status evidence or next steps while still looking like an authoritative handoff. A producer must emit a valid report within the configured bound.
+
+## Consequences
+
+- Fresh-agent iteration is a first-class model tool implemented entirely as a removable plugin over existing seams.
+- Goal rounds and Ralph rounds stay different concepts: the former is one same-session continuation turn, while the latter is one fresh child inside a foreground workflow.
+- The workspace becomes authoritative cross-round memory, so workers must inspect and verify it rather than trusting a narrative handoff.
+- A generous round ceiling permits substantial autonomous work, while deployment config still bounds child count and every handoff remains size-limited.
+- Provider routing and a lowerable per-run child ceiling become explicit workflow start concerns without expanding the script or ordinary workflow tool surface.
+
+## Known limitations and deferred work
+
+- Completion and blocker status are worker self-declarations. An independent evaluator, evaluator-driven feedback round, completion certificate, or adversarial verifier is intentionally deferred.
+- Runs are foreground and process-local. Background collection, persistence/resume, scheduling, and restart recovery are absent.
+- Round count is the only aggregate budget. Token, currency, elapsed-time, and provider-usage budgets remain separate future policy.
+- One round creates one child. Within-round fan-out, evaluator/worker role separation, dynamic provider or model selection, and cross-run journals are deferred.
+- An ordinary child failure ends the run without retry, while preserving the failed round and last successful handoff. Fatal workflow infrastructure failures can end before the fixed script returns that state; adding retry or richer failure transport requires separate policy and seam design.
+- Prompt guidance asks models not to invoke Ralph recursively; a structural child-tool restriction would require a separately designed workflow child-policy surface.

.agents/notes/implemented/feature/2026-07-19-fresh-agent-ralph-workflow-tool.zh.md

@@ -0,0 +1,74 @@
+# Agent Note: 全新 agent Ralph 工作流工具
+
+Status: implemented
+
+[English](2026-07-19-fresh-agent-ralph-workflow-tool.md) | 中文
+
+## 问题
+
+同会话目标会保留对话，让一个 agent 持续完成持久目标；通用工作流工具则让模型编写扇出编排脚本。两者都不是 Ralph 模式：把同一目标反复交给完全全新的工作者，以共享工作区作为长期记忆，并且在各轮之间只传递一份小型显式交接，直到工作完成或触及限制。
+
+如果把 Ralph 行为加入 `dsh-agent-loop`、目标驱动器或面向模型的公开工作流语言，就会让一项策略与无关的执行机制耦合。让每个子 agent 继承父对话也会破坏上下文重置，并让重放依赖不断增长的隐式前缀。此功能需要一项由现有插件原语组合而成的固定、可评审策略，同时具备取消静止性、有界跨轮数据、宽裕且可配置的上限，并且不引入新颖的面向人类目标状态。
+
+## 决策
+
+在 `packages/workflow/` 下新增独立消费者包 `@deepseek-ai/dsh-tool-ralph`。它注册 `ralph({ objective, maxRounds? })`，拥有固定工作流脚本，并且只依赖 `ctx.tools`、`ctx.systemPrompt`、`ctx.workflows` 和 `ctx.subagents`。Ralph 运行不是会话目标，不会创建目标状态，也不要求在具体 agent loop 中增加分支。
+
+该工具仅以前台方式运行。调用 agent 作为每个子 agent 的父级以提供 cwd 和谱系，父工具调用等待整次运行结束，父步骤的中止信号会取消工作流。每条路径都会等待 `run.dispose()`，因此调用返回前，取消会经过工作流引擎的有界收敛并达到子 agent 静止状态。
+
+### 每次运行的工作流 provider 路由
+
+`WorkflowStartRequest` 新增可选的 `subagentProvider`。工作线程引擎先解析这个显式的每次运行值，再回退到引擎配置的 provider；在发布运行前，它要求所选规范化路由已注册，并把结果用于每次 `agent()` 调用。脚本无法观察或替换此路由。普通 `workflow` 工具不设置该字段，也不暴露新的模型参数，因此通用工作流行为和 provider 策略保持不变。
+
+Ralph 插件的 `subagentProvider` 默认为 `spawn`。每次调用前，它要求具名 provider 已存在、支持结构化输出且报告 `inheritsParentContext: false`；类似 fork 或能力不足的 provider 会在工作流启动前响亮失败。provider 查找保留在调用期，因为效果作用域内的 provider 注册可能随 HMR 改变。
+
+### 每次运行的工作流子 agent 上限
+
+`WorkflowStartRequest` 还新增可选的 `maxTotalAgents`。工作线程引擎要求它是正安全整数且不高于已配置的部署上限，并在发布运行前把解析值装入该运行的工作线程限制。Ralph 把解析后的 `maxRounds` 作为此上限，因此固定循环的轮次预算不会与通用失控子 agent 后备限制冲突。普通工作流工具不设置该字段并保留引擎默认值。
+
+### Ralph 轮次与交接
+
+层级为 Ralph 运行 → Ralph 轮次 → 全新子 agent 回合 → 步骤。每个 Ralph 轮次恰好通过所选 provider 创建一个子 agent。Spawn 给该子 agent 一个没有种子的独立会话，同时保留父级 cwd，因此共享工作树是持久权威，父对话和先前子 agent 历史都不会进入请求。
+
+固定提示只传递不可变目标、当前轮次与上限、以工作区为权威的指令，以及上一份结构化报告。`RalphRoundReport` 包含 `status: continue | complete | blocked`、`summary`、`evidence`、`nextSteps` 和 `blocker`。字符串必须规范化；`continue` 要求存在下一步且没有阻塞项，`complete` 要求存在证据且没有下一步或阻塞项，`blocked` 要求具体阻塞项。报告成为下一次交接前，脚本会验证语义与序列化大小；消费者还会跨工作流接缝再次验证实体化的终止值。
+
+`maxRounds` 默认为 `256`，同时也是调用覆盖值的部署上限。`maxHandoffChars` 和 `maxResultChars` 均默认为 `16384`。三者都是正安全整数配置值。过大的交接会失败，而不会被静默截断；`maxResultChars` 单独限制面向父级的完整成功文本，包括外层文本和截断标记，并且不会改变跨轮状态。最后一个允许轮次报告 `continue` 后，固定脚本返回 `budget-limited`；`complete` 和 `blocked` 会立即返回最终报告与已启动轮次数。
+
+工作流语言会把正常结束但未成功的子 agent 映射为 `null`。固定脚本会在报告验证前检测该值，并返回 `round-failed`，其中包含失败轮次，以及存在时的上一份成功交接；工具会把它转成错误，而不会误判为畸形报告或预算耗尽。Ralph 不添加重试策略。致命的 provider 启动、传输、工作线程和工作流错误仍是通用工作流失败，因为这些路径上的工作流接缝不携带可恢复的子报告。
+
+### 模型与 UI 表面
+
+模型只能提供 `objective` 和可选的 `maxRounds`；provider 选择、报告 schema、交接上限和脚本都由部署拥有。固定提示区段说明，只有直接人类明确要求 Ralph 或全新 agent 迭代时才使用 `ralph`，并将其与同会话目标、有界委派和通用扇出工作流区分开。这是指导，而不是新的目标 UX 状态机。
+
+ACP 和终端展示使用通用 `ralph` 卡片，并把目标作为原始输入。成功完成与阻塞的外层文本会说明结果由工作者报告，而不会把它呈现为独立认证。父转录只保留原始工具调用，以及一份有界成功终止报告或一个错误，不包含中间子 agent 消息。发布的无头、TUI 与 ACP 组合会在现有工作流引擎旁加载该插件；JSON-RPC 保持不变，因为其默认组合不暴露工作流。
+
+## 测试
+
+单元测试覆盖配置与调用上限解析、provider 能力拒绝、固定启动请求路由与子 agent 上限、全部成功终止结果、普通子 agent 失败外层值、畸形及过大边界值、成功结果精确截断、中止时序、处置、渲染意图、提示生命周期和命名空间插件形状，并达到逐文件 100% 覆盖率。工作流引擎测试证明 provider 路由会同步验证、每次运行的子 agent 上限可低于部署上限，并且 provider 覆盖会选择每个子 agent 且不改变配置默认值，其中包括普通 Node 下构建后的 `lib/worker.cjs`。
+
+一项无密钥真实栈集成测试通过实际工作线程引擎、spawn provider、结构化输出运行时和 agent loop 驱动固定脚本。它证明子 agent 标识不同、没有 `seedLength`、继承 cwd、两个子请求都不含父历史标记、上一份报告只精确出现在下一轮交接中、只产生一个阶段事件、终止完成以及两个子 agent 都被处置。同一真实栈还覆盖阻塞与轮次上限结果、未规范化及语义无效报告、过大交接、保留上一份有效交接的普通子 agent 失败，以及取消后达到子 agent 静止状态。一项已发布的无密钥无头快照还会启动真实的 `examples/headless-agent` 组合、调用 `ralph`、固定父级流式转录，并检查持久化日志中存在两个不同且无种子的子会话，且第一轮交接只出现在第二轮。工具测试固定通用调用/结果展示，而 ACP 重放请求头快照固定发布的 schema 与提示指导转录表面。
+
+## 考虑过的替代方案
+
+- **把 Ralph 放进同会话目标驱动器** — 拒绝，因为目标轮次有意保留同一段对话，而 Ralph 的定义性属性是每轮使用全新上下文；合并两者会让目标生命周期与子 agent 编排无法分离。
+- **在通用工作流工具上暴露 `fresh` 或循环标志** — 拒绝，因为模型编写的脚本表面应保持通用且与 provider 无关；Ralph 的固定报告协议和停止策略值得拥有一个可评审消费者。
+- **为了方便重放而使用 `subagent_fork`** — 拒绝，因为继承的已完成回合是隐式、不断增长的交接状态，并违反全新上下文契约。工作区加一份结构化报告即可重放，无需插入人为取消记录。
+- **让工具直接调用 subagent 接缝** — 拒绝，因为现有工作流引擎已经拥有前台编排、结构化子 agent、取消传播、工作线程终止、事件和静止处置。复用它可以展示插件组合，而不是构建第二个循环运行时。
+- **静默截断大型报告** — 拒绝，因为截断可能删除状态证据或下一步，却仍看似权威交接。生产者必须在配置边界内发出有效报告。
+
+## 后果
+
+- 全新 agent 迭代成为一项一等模型工具，并完全以现有接缝之上的可移除插件实现。
+- 目标轮次与 Ralph 轮次保持不同概念：前者是一次同会话续行回合，后者是前台工作流中的一个全新子 agent。
+- 工作区成为权威跨轮记忆，因此工作者必须检查和验证工作区，而不能信任叙事性交接。
+- 宽裕的轮次上限允许大量自治工作，而部署配置仍会限制子 agent 数量，并且每次交接始终受大小约束。
+- provider 路由与可降低的每次运行子 agent 上限成为显式的工作流启动关注点，但不扩展脚本或普通工作流工具表面。
+
+## 已知限制与推迟工作
+
+- 完成与阻塞状态由工作者自行声明。独立 evaluator、evaluator 驱动的反馈轮次、完成证书或对抗式 verifier 被有意推迟。
+- 运行位于前台且只存在于进程内。后台收集、持久化/恢复、调度和重启恢复均不存在。
+- 轮次数是唯一聚合预算。token、货币、耗时和 provider 用量预算仍属于未来的独立策略。
+- 每轮创建一个子 agent。轮内扇出、evaluator/工作者角色分离、动态 provider 或模型选择，以及跨运行日志均被推迟。
+- 普通子 agent 失败会结束运行且不重试，同时保留失败轮次与上一份成功交接。致命工作流基础设施错误可能在固定脚本返回该状态前结束；增加重试或更丰富的失败传输需要独立的策略与接缝设计。
+- 提示指导模型不要递归调用 Ralph；结构化的子 agent 工具限制需要另行设计工作流子策略表面。

.agents/notes/implemented/testing/2026-06-19-acp-snapshot-tests.md

@@ -57,7 +57,7 @@ Normalization replaces session, cwd, protocol-id, timestamp, path, and process v
 
 ### Isolation: normalization now, sandbox later
 
-Tool determinism comes from a temporary cwd, scrubbed environment, fresh non-login shell, constrained commands, and normalization. It does not claim OS confinement. A sandboxed executor can replace the local backend through the existing [capability seam](../architecture/2026-06-13-capability-seams.md) if a stronger tier is needed.
+Tool determinism comes from a temporary cwd, scrubbed environment, fresh non-login shell, constrained commands, and normalization. Concurrent replay runs own separate cwd, persistence, and fixed-length scenario-keyed spill roots, so one scenario's teardown cannot delete another's in-flight full-output recovery while real-path preview budgets remain stable. This tier does not claim OS confinement. A sandboxed executor can replace the local backend through the existing [capability seam](../architecture/2026-06-13-capability-seams.md) if a stronger tier is needed.
 
 ### The replay plugin is its own package