feat(reward-memory): consume query-ready decisions through TS policy

docs/architecture/rfcs/goal-scoped-capability-portfolio-v0.md

@@ -534,6 +534,17 @@ an engineering and a research question; no host-session-file copying. The
 current continuation and Decision Context contracts own the work; missing
 provenance/update fields belong to their owners, not a new continuity store.
 
+The optional [query-ready Reward Memory caller](../../reference/reward-memory-decision-consumption.md)
+provides a bounded prerequisite: TS admission/completion, existing Python
+provider/applier adaptation, context delivery distinct from semantic assessment,
+and exact caller-retained replay. It does not complete the fresh-session journey,
+automatically compose capabilities, or establish memory utility; those remain
+subject to real caller and held-out outcome qualification.
+
+可选的 query-ready Reward Memory 调用方提供有界前置切片：TS 准入/完成、原
+Python provider/applier 适配、上下文交付与语义判断分开、调用方保留的精确复用。
+它不宣称已完成跨会话纠正、自动组合或记忆效果；真实调用和留出结果仍须验收。
+
 ## 6. Alternatives and design choices
 
 ### Domain skills organize capabilities

docs/reference/reward-memory-decision-consumption.md

@@ -0,0 +1,158 @@
+# Query-ready Reward Memory consumption / 决策就绪的经验消费
+
+This optional caller API closes **qualified recall → private context delivery →
+explicit semantic assessment**. It does not generate a query, enable a provider,
+write memory, or prove utility. Existing experiment configuration, corpus scope,
+freshness/conflict checks and provider adapters remain their owners.
+
+此可选 API 连接「合格召回 → 私有上下文交付 → 显式语义判断」。它不生成问题、
+开启 provider、写入记忆或证明效果；配置、corpus 范围、时效/冲突和 provider
+仍由既有 owner 持有。应先冻结具体问题和当前产物，再调用，不在每次心跳重复召回。
+
+## Entry and ownership / 入口与归属
+
+Import `run_reward_memory_decision` and `assess_reward_memory_decision` from
+`loopx.capabilities.reward_memory`. Resolve the original normalized configuration
+with `resolve_reward_memory_experiment`; an unavailable binding must not be
+replaced with an unverified configuration. Pass the existing automatic-recall
+hook arguments unchanged: surface, workspace/project, revision, bounded queries,
+observation time, freshness/conflict, read-authority checkpoints and provider.
+Add `query_ready`, the consumer mode and an explicit application strategy.
+`application_id` and `artifact_ref` identify this question and current artifact,
+not a fresh identity on every retry. The caller's baseline/arguments must be
+JSON-compatible; non-serializable input fails before recall.
+
+Read-authority checkpoints must match the exact consumer surface and corpus;
+a turn-admission checkpoint cannot authorize a different review surface.
+`freshness_context.age_seconds`, when supplied, is a nonnegative integer.
+Rejected requests expose only the original hook's allowlisted
+`boundary_reason_code`, never exception text or private input values.
+
+使用上述导出入口和 `resolve_reward_memory_experiment` 的原配置读回；不可用时
+不能拿未经验证的配置替代。原 hook 的范围、revision、问题、时点、时效/冲突、
+读授权 checkpoint 和 provider 原样传入，另加 `query_ready`、模式和应用策略。
+`application_id` / `artifact_ref` 绑定同一问题和当前产物，不因重试换身份。
+基线和参数须可 JSON 序列化，非法输入在 provider 调用前 fail-open。
+
+读授权 checkpoint 必须匹配本次 surface/corpus，不能拿 Turn 准入的 checkpoint
+授权另一评审入口；age_seconds 如提供，须为非负整数。拒绝回执仅投影原 hook
+白名单内的 boundary_reason_code，不暴露异常正文或私有参数。
+
+TypeScript owns admission and completion (`reward_memory.decision.plan/project`);
+Python adapts the existing provider/applier and retains transient private values.
+TS receives only compact references, typed statuses, counts and receipt digests:
+never the query, lesson, baseline, provider payload or model rationale.
+No new store, SDK, key, enablement switch or action authority is introduced.
+
+TS 负责准入和完成语义；Python 只适配现有 provider/applier 并保留瞬时私有值。
+TS 只收到引用、状态、计数与摘要，不收到问题、经验正文、原产物或模型判断内容；
+不新增存储、SDK、密钥、开关或行动授权。
+
+| Mode / 模式 | Provider / 调用 | Meaning / 意义 |
+| --- | --- | --- |
+| Disabled/unconfigured / 未配置或关闭 | Zero; returns `None` / 零调用，无新 packet | Original path unchanged / 原路径不变 |
+| `preview` | Zero / 零调用 | Admission preview, never adoption / 预检，不代表采用 |
+| `recall_only` | Existing bounded route / 原有界路由 | Redacted recall observation, base unchanged; no semantic claim / 脱敏观察，不表示语义采用 |
+| `execute` without strategy/artifact / 缺策略或产物 | Zero / 零调用 | `incomplete`, research may continue / 不完整，研究可继续 |
+| `execute` + `context_delivery` | Existing bounded route / 原有界路由 | Private context available, **not** semantic application / 私有上下文可读，非语义采用 |
+| `execute` + `semantic_application` | Existing bounded route / 原有界路由 | Exact attributed `applied/ignored/refuted` / 当前产物的归因判断 |
+
+## Minimal caller integration / 最小接入
+
+`hook_arguments` below are the already-qualified arguments from the caller's
+existing surface. The callback is the original SDK applier contract, not a
+provider response interpreted as authority:
+
+下例 `hook_arguments` 来自既有已验证 surface；callback 复用原 SDK 的 applier
+契约，不把 provider 内容解释成授权。
+
+```python
+from loopx.capabilities.reward_memory import (
+    run_reward_memory_decision, assess_reward_memory_decision,
+)
+
+def deliver_context(base, items):
+    return {
+        "outcome": "applied",  # SDK delivery; NOT semantic-use evidence
+        "output": {"baseline": base, "private_context": items},
+        "memory_refs": [item.memory_ref for item in items],
+        "current_artifact_verified": True,  # caller must actually verify it
+        "reasoning_summary": "Qualified context delivered for separate review.",
+    }
+
+delivered = run_reward_memory_decision(
+    config, query_ready=True, mode="execute",
+    application_kind="context_delivery", apply_memory=deliver_context,
+    **hook_arguments,
+)
+if delivered is not None and delivered.public_packet["context_delivery_verified"]:
+    # The real caller/model reads delivered.output and the CURRENT artifact.
+    # judge returns output, outcome, current_artifact_verified, memory_refs
+    # from these exact items, and a bounded evidence-backed reasoning_summary.
+    assessed = assess_reward_memory_decision(delivered, apply_memory=judge)
+    public_receipt = assessed.public_packet
+```
+
+`judge` must represent actual comparison, not unconditional adoption. For
+`ignored/refuted`, keep the original baseline. All semantic dispositions require
+nonempty attribution to these exact recalled items and verified current artifact.
+An applied lesson may preserve the decision; application is still not utility.
+
+`judge` 必须表达真实比较，不能无条件采用；ignored/refuted 保持原基线。
+所有语义判断都需引用本次实际条目并核验当前产物。经验被采用也可能不改变结论，
+更不代表质量、成本、收益或 alpha 已改善。
+
+Only `public_packet` is a display projection. Output, session, original
+application receipt, baseline and request remain caller-private, never generic
+frontend/Lark/registry payloads. Retain the result in the caller's existing
+execution context. `previous_result=result` replays only an exact request digest
+(configuration and input included) without another provider call; changed input
+returns `replay_request_mismatch`. Reassessment uses retained qualified items and
+the original **cumulative** multi-corpus counters, not a second query. This is
+caller-retained replay, not automatic cross-process persistence or a new cache.
+
+仅 `public_packet` 用于展示，其余结果私有。通过既有执行上下文保留结果；
+`previous_result` 仅复用配置和输入均匹配的请求，变化则拒绝复用。后续判断使用
+原条目和累计多 corpus 遥测，不重复查询。这不是自动跨进程存储或新的缓存。
+
+Empty/filtered/unavailable and invalid model/transport results preserve the base
+and allow ordinary research. Post-provider transport failure retains actual
+call/filter counts and the original private receipt. The existing route still
+owns its call cap: one query per corpus can mean multiple provider calls.
+A caller with a one-call budget must use a qualified one-corpus route.
+
+空结果、过滤、故障和无效判断不阻塞独立研究。provider 后 TS 故障仍保留真实
+计数和原私有回执。预算由原路由负责；每 corpus 一次不等于全路由一次，单次预算
+须使用已验证的单 corpus 路由。
+
+## Validation, surfaces and rollback / 验证、产品入口与回滚
+
+```sh
+uv run --extra test pytest -q tests/capabilities/test_reward_memory_decision.py
+node --experimental-strip-types --test tests/control_plane_ts/reward_memory_decision.test.ts
+```
+
+This delivery adds a caller API for CLI/managed decision boundaries. Configuration
+is unchanged: Dashboard's existing Reward Memory editor still controls
+`config_path` and `enabled_agents` through the same preview/apply/readback owner;
+Lark keeps its existing status-only coverage. No new frontend control or packaged
+frontend change is needed for these unchanged settings. The new typed receipt
+can be returned by an integrated caller; **universal frontend/Lark consumption
+and cross-session persistence are not delivered by this API**.
+
+本次交付是 CLI/managed 决策边界的调用 API。配置未变，Dashboard 继续通过原
+preview/apply/readback 编辑 config_path 和 enabled_agents；Lark 仍为原状态
+投影。无需新增配置控件或前端包；接入的调用方可回传同一 typed receipt，
+但此 API 不宣称已打通所有前端/Lark 或自动跨 session 持久化。
+
+Rollback the caller to `run_reward_memory_automatic_recall_hook`, whose optional
+callback/`available_not_applied` behavior is unchanged. To disable recall, use
+the original configuration owner to set `automatic_recall=false` and requalify
+the binding, or disable the experiment with `configure-goal --clear-reward-memory-config`.
+No recall, disposition or receipt grants orders, signing, transfer, publishing
+or legacy-record migration rights.
+
+回滚调用方至原 automatic hook 即可；其可选 callback 语义未变。关闭召回通过
+原配置 owner 设置 automatic_recall=false 后重新验证绑定，或用原
+configure-goal --clear-reward-memory-config 关闭实验。任何回执均不扩大交易、
+签名、转账、发布或旧记录迁移权限。

loopx/capabilities/reward_memory/README.md

@@ -650,6 +650,11 @@ performs no provider or external write.
 
 ## Stage 3 recall and application seam
 
+For an explicit query-ready decision, use the optional
+[decision-consumption caller API](../../../docs/reference/reward-memory-decision-consumption.md).
+It distinguishes private context delivery from attributed semantic assessment,
+reuses the existing provider/applier, and retains the original optional-callback SDK path.
+
 Stage 3 accepts only an explicit `reward_memory_recall_request_v0` naming one
 registered corpus and one module-owned surface. The request carries a matching
 read-authority checkpoint and current freshness/conflict observations. A

loopx/capabilities/reward_memory/__init__.py

@@ -36,6 +36,11 @@
     normalize_reward_memory_standing_policy,
 )
 from .evaluation import run_reward_memory_evaluation
+from .decision import (
+    RewardMemoryDecisionResult,
+    assess_reward_memory_decision,
+    run_reward_memory_decision,
+)
 from .dogfood import (
     build_reward_memory_dogfood_batch,
     build_reward_memory_dogfood_receipt,
@@ -65,6 +70,9 @@
 
 __all__ = [
     "build_reward_memory_architecture_packet",
+    "RewardMemoryDecisionResult",
+    "assess_reward_memory_decision",
+    "run_reward_memory_decision",
     "RewardMemoryFilteredRecallItem",
     "RewardMemoryRecallItem",
     "RewardMemoryRecallSession",