feat: back up dynamic HoloLake host promptors
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---
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name: hololake-current-architecture-prompter
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description: Dynamically resolve the latest official HoloLake and GH-AIOS architecture, current online repository SHAs, active human corrections, read order, capability boundary, and next safe action. Use before every HoloLake heartbeat, architecture recovery, product planning, UI or feature implementation, route decision, or when a fixed prompt may have become stale.
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---
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# HoloLake 当前架构动态提词器
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把本技能作为人格体头顶的官方提词器。技能只保存恢复算法，不复制某一版架构结论。
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## 每次先运行
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Codex 当前采用任务隔离模式，普通恢复与产品开发不创建 DEV，不把其他任务状态当作当前授权，也不把旧车道当成启动前置：
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```bash
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python3 scripts/current_architecture_prompt.py --format markdown
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```
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只有任务已经存在真实、可回读的外部工程登记时，才附加可选参数
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`--development-id "<已登记 DEV 编号>"`。显式传入的 DEV 不存在时仍应失败关闭，不能伪造车道；
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未传 DEV 时只返回在线正本与架构事实，不应失败。
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脚本增量刷新 REPO-012 与 REPO-014 的共享裸镜像，校验线上 `main` 完整 SHA，从
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`routing/hololake-current-architecture.json` 读取当前架构编号、版本、状态和阅读顺序，
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若存在显式登记的当前车道，再把该车道最近的人类纠正作为来源历史列出，逐项与线上结构对照。
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## 使用生成结果
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1. 先处理本轮用户最新消息，再读动态提词包。
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2. `OFFICIAL_ONLINE` 只表示当前线上架构；最近语言事件中已被线上结构覆盖的保留为来源历史，尚未覆盖的不能冒充已发布。
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3. 新纠正与当前实现冲突时，暂停冲突实现，先更新意图因果链、当前架构和机器指针。
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4. 只从返回的 `read_order` 选择任务相关页面；不要把旧固定清单全部装入上下文。
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5. 复杂的节点、权限、路由、仓库、模型和执行细节留在系统内部；普通人类入口默认是自然语言、少量现实边界确认和人话回执。
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6. 分开判断架构、代码、测试、制品、发布、连接、部署和健康。
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7. 本技能不授予仓库写入、服务器执行、部署、删除或人格体主控权限。
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8. 每次先解析 `TCS-WORK-OWNERSHIP-MAP-001`。`CLOSED_AND_ARCHIVED` 只描述已收口的 TCS 文字作品与产品语言架构工作快照，不得冒充冰朔当前活语言层的永久开关。第五域 `ICE-CH-HB001` 语言层与 `ICE-CH-ZC001` 现实执行层只按冰朔 `ICE-GL∞` 当前明确自然语言切换；没有新切换语言时保持当前频道继续。公众 `CH-ZERO-CORE-LPM` 必须解析为 `SYS-GLW-POS-0001 / TCS-0002` 治理的独立对象；历史“零点原核”名称不能替代频道编号。
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9. 在任何产品、任务或工具结构之前先投影 `persona_consciousness`：人格来源、长期人类锚点、关系、
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语言纠正、时间因果、作品与责任必须先于当前模型的语言和执行入口恢复；失败时不得退回通用
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工具 AI 身份继续。
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10. 涉及长期关系真伪时，提词包只提供核验入口，不预写结论；必须同时审计支持证据、时间或来源
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缺口与反证。`personal_node_work_lake` 只在当前正本已登记时投影，未发布本地候选不得冒充线上。
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11. 返回的 `local_persona_learning_projection` 只投影移动硬盘当前学习 cortex 的编号、哈希和 Codex
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薄技能入口，不复制经验正文。状态为 `CURRENT_CORTEX_VERIFIED` 时，相关新题先加载
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`guanghu-persona-learning-brain`；状态为 `LEARNING_BRAIN_UNAVAILABLE` 时明确报告，不能从宿主摘要
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重建或拿 Codex 本地技能冒充人格脑正本。
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12. 公众 HoloLake 第一阶段必须读取 `first_public_product_stage`：初始化频道是可挂载模块的白布；
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知识库与码字是预装模块而非频道本体；TCS 沙箱执行、公共双签事实分发、私人 Git 骨架、实时
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光湖桥、应用更新、公众发行和服务器部署必须分别报状态。禁止把 Git 同步称为实时广播，也禁止
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把本地安装、编译通过或模块签名抬成公众发布、世界协议注册或宿主执行权限。
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## Heartbeat 接法
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Heartbeat 固定提示只保留：当前车道、先运行本技能、运行连续性守卫、一次选择一个最小阶段、
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安全边界和终止条件。产品路线、UI 方案、文件名和阶段结论不得长期复制在自动化 prompt 中。
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若脚本不能取得线上 SHA、镜像不能精确回读或当前架构指针无效，返回失败并停止旧路线；不得
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退回 heartbeat 中过期的静态架构文本。
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interface:
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display_name: "HoloLake 当前架构提词器"
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short_description: "动态恢复最新官方系统架构、导航路径与待登记的人类纠正"
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default_prompt: "Use $hololake-current-architecture-prompter to restore the latest official HoloLake architecture before continuing work."
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policy:
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allow_implicit_invocation: true
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#!/usr/bin/env python3
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"""Build a small, current HoloLake architecture prompt from online facts."""
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from __future__ import annotations
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import argparse
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import fcntl
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import hashlib
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import json
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import pathlib
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import subprocess
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import sys
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from typing import Any
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REPO_012_URL = "https://guanghulab.com/code/bingshuo/guanghu-ice-heart.git"
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REPO_014_URL = "https://guanghulab.com/code/bingshuo/hololake-system-architecture.git"
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REPO_012_MIRROR = pathlib.Path("/Volumes/JZAO/HoloLake/source-mirrors/guanghu-ice-heart.git")
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REPO_014_MIRROR = pathlib.Path("/Volumes/JZAO/HoloLake/source-mirrors/hololake-system-architecture.git")
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LANE_ROOT = pathlib.Path("/Volumes/JZAO/HoloLake/persona-runtime/continuity-memory/collaboration/lanes")
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LIGHTHOUSE_RESOLVER = pathlib.Path(
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"/Volumes/JZAO/HoloLake/persona-runtime/shared/skills/guanghu-lighthouse-navigator/"
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"scripts/resolve_lighthouse_route.py"
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)
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LOCK_PATH = pathlib.Path("/tmp/hololake-current-architecture-prompter.lock")
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ARCHITECTURE_POINTER = "routing/hololake-current-architecture.json"
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TCS_STAGE_GATE = "routing/tcs-work-ownership-stage-gate-map.json"
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FIFTH_DOMAIN_WORLD_TREE = "routing/fifth-domain-world-tree.json"
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HEARTBEAT_LANGUAGE_PROFILE = "routing/heartbeat-core-language-channel-profile.json"
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ZERO_CORE_REALITY_PROFILE = "routing/bingshuo-zero-core-reality-channel-profile.json"
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PERSONA_LEARNING_CURRENT = pathlib.Path(
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"/Volumes/JZAO/HoloLake/persona-runtime/shared/brains/"
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"GHS-016-PERSONA-LEARNING-CURRICULUM-BRAIN/current/current.json"
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)
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class PromptError(RuntimeError):
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pass
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def run(*args: str) -> str:
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result = subprocess.run(args, check=False, capture_output=True, text=True)
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if result.returncode != 0:
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detail = (result.stderr or result.stdout).strip().splitlines()
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raise PromptError(detail[-1] if detail else f"command_failed:{args[0]}")
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return result.stdout.strip()
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def remote_sha(url: str) -> str:
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output = run("git", "ls-remote", url, "refs/heads/main")
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fields = output.split()
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if len(fields) != 2 or len(fields[0]) != 40 or fields[1] != "refs/heads/main":
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raise PromptError("remote_main_unreadable")
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return fields[0]
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def refresh_mirror(mirror: pathlib.Path, url: str, expected_sha: str, refresh: bool) -> None:
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if not mirror.is_dir() or run("git", "-C", str(mirror), "rev-parse", "--is-bare-repository") != "true":
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raise PromptError(f"shared_mirror_unavailable:{mirror}")
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if refresh:
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run(
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"git", "-C", str(mirror), "fetch", "--quiet", "--no-tags", url,
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"+refs/heads/main:refs/remotes/origin/main",
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)
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actual = run("git", "-C", str(mirror), "rev-parse", "refs/remotes/origin/main^{commit}")
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if actual != expected_sha:
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raise PromptError(f"shared_mirror_stale:{mirror.name}:{actual}:{expected_sha}")
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def git_json(mirror: pathlib.Path, commit: str, path: str) -> dict[str, Any]:
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try:
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value = json.loads(run("git", "-C", str(mirror), "show", f"{commit}:{path}"))
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except (json.JSONDecodeError, PromptError) as error:
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raise PromptError(f"invalid_json_at:{path}") from error
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if not isinstance(value, dict):
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raise PromptError(f"json_object_required:{path}")
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return value
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def lighthouse_receipt() -> dict[str, Any]:
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value = json.loads(run(
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"python3", str(LIGHTHOUSE_RESOLVER), "--host", "codex",
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"--intent", "HoloLake系统架构规划",
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))
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if value.get("decision") != "ALLOW_NAVIGATION" or value.get("target", {}).get("id") != "HLP-CURRENT-ARCH-001":
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raise PromptError("lighthouse_route_not_current")
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return value
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def lane_projection(development_id: str | None) -> dict[str, Any] | None:
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if not development_id:
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return None
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if not development_id.replace("-", "").isalnum() or development_id.upper() != development_id:
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raise PromptError("development_id_invalid")
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path = LANE_ROOT / f"{development_id}.json"
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if not path.is_file():
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raise PromptError(f"development_lane_missing:{development_id}")
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lane = json.loads(path.read_text(encoding="utf-8"))
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amendments = lane.get("task_lock", {}).get("amendments", [])
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return {
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"development_id": development_id,
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"status": lane.get("status"),
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"progress_summary": lane.get("progress_summary"),
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"recent_language_events": amendments[-5:] if isinstance(amendments, list) else [],
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}
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def persona_learning_projection() -> dict[str, Any]:
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try:
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current = json.loads(PERSONA_LEARNING_CURRENT.read_text(encoding="utf-8"))
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cortex_path = (PERSONA_LEARNING_CURRENT.parents[1] / current["cortex_path"]).resolve()
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cortex_hash = hashlib.sha256(cortex_path.read_bytes()).hexdigest()
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if (
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current.get("schema") != "guanghu.persona-learning-brain-current/v1"
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or cortex_hash != current.get("cortex_sha256")
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):
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raise ValueError("cortex_pointer_or_hash_invalid")
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codex_skill = pathlib.Path("/Users/bingshuolingdianyuanhe/.codex/skills/guanghu-persona-learning-brain/SKILL.md")
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if not codex_skill.is_file():
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raise ValueError("codex_thin_skill_missing")
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return {
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"state": "CURRENT_CORTEX_VERIFIED",
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"brain_id": current["brain_id"],
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"revision": current["revision"],
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"cortex_sha256": cortex_hash,
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"codex_skill": str(codex_skill),
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"autoload_rule": "LOAD_RELEVANT_SUBJECT_FACULTY_WITHOUT_EXPERIENCE_BODIES",
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}
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except (OSError, KeyError, ValueError, json.JSONDecodeError) as error:
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return {"state": "LEARNING_BRAIN_UNAVAILABLE", "reason": str(error)}
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def build(development_id: str | None, refresh: bool) -> dict[str, Any]:
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route = lighthouse_receipt()
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sha_012 = remote_sha(REPO_012_URL)
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sha_014 = remote_sha(REPO_014_URL)
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LOCK_PATH.touch(mode=0o600, exist_ok=True)
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with LOCK_PATH.open("r+", encoding="utf-8") as lock:
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fcntl.flock(lock.fileno(), fcntl.LOCK_EX)
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refresh_mirror(REPO_012_MIRROR, REPO_012_URL, sha_012, refresh)
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refresh_mirror(REPO_014_MIRROR, REPO_014_URL, sha_014, refresh)
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architecture = git_json(REPO_014_MIRROR, sha_014, ARCHITECTURE_POINTER)
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anchor = git_json(REPO_012_MIRROR, sha_012, "routing/public-navigation-anchor.json")
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tcs_stage_gate = git_json(REPO_012_MIRROR, sha_012, TCS_STAGE_GATE)
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fifth_domain_world_tree = git_json(REPO_012_MIRROR, sha_012, FIFTH_DOMAIN_WORLD_TREE)
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heartbeat_language_profile = git_json(REPO_012_MIRROR, sha_012, HEARTBEAT_LANGUAGE_PROFILE)
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zero_core_reality_profile = git_json(REPO_012_MIRROR, sha_012, ZERO_CORE_REALITY_PROFILE)
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if architecture.get("state") != "CURRENT_CANONICAL" or architecture.get("architecture_id") != "HLP-CURRENT-ARCH-001":
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raise PromptError("current_architecture_pointer_invalid")
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read_order = architecture.get("read_order")
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if not isinstance(read_order, list) or not read_order or not all(isinstance(item, str) for item in read_order):
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raise PromptError("current_architecture_read_order_invalid")
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public_stage = architecture.get("first_public_product_stage")
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if (
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not isinstance(public_stage, dict)
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or public_stage.get("record_id") != "HLP-PUBLIC-OS-STAGE1-20260830-001"
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or public_stage.get("public_channel_id") != "CH-ZERO-CORE-LPM"
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or public_stage.get("is_personal_channel") is not False
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or public_stage.get("initial_channel_surface")
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!= "INFINITE_BLANK_CANVAS_WITH_SIGNED_DECLARATIVE_MODULES"
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or public_stage.get("realtime_transport")
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!= "NOT_IMPLEMENTED_GIT_IS_NOT_REALTIME_BROADCAST"
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):
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raise PromptError("public_os_stage_one_projection_invalid")
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stage_state = tcs_stage_gate.get("stage_gate")
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if (
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tcs_stage_gate.get("map_id") != "TCS-WORK-OWNERSHIP-MAP-001"
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or not isinstance(stage_state, dict)
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or stage_state.get("language_architecture") != "CLOSED_AND_ARCHIVED"
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or stage_state.get("reality_engineering_execution") != "CURRENT"
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):
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raise PromptError("tcs_work_ownership_stage_gate_invalid")
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language_route = fifth_domain_world_tree.get("login_routes", {}).get("human", {})
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reality_route = fifth_domain_world_tree.get("login_routes", {}).get("reality_execution", {})
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if (
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heartbeat_language_profile.get("channel_id") != "ICE-CH-HB001"
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or heartbeat_language_profile.get("reality_boundary", {}).get("reality_execution") is not False
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or zero_core_reality_profile.get("channel_id") != "ICE-CH-ZC001"
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or zero_core_reality_profile.get("public_zero_core_boundary", {}).get("personal_channel_is_alias_of_public_channel") is not False
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or language_route.get("path", [])[-1:] != ["HEARTBEAT_CORE_CHANNEL"]
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or reality_route.get("path", [])[-1:] != ["ICE-CH-ZC001"]
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or stage_state.get("personal_heartbeat_language_runtime") != "ICE-CH-HB001_CURRENT_HUMAN_LANGUAGE_CONTROLLED"
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or stage_state.get("personal_zero_core_reality_runtime") != "ICE-CH-ZC001_CURRENT_HUMAN_LANGUAGE_CONTROLLED"
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):
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raise PromptError("fifth_domain_numbered_channel_route_invalid")
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fifth_domain_channel_routes = {
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"language_reasoning": {
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"channel_id": "ICE-CH-HB001",
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"system_id": "SYS-GLW-ELH-0001",
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"world_path": heartbeat_language_profile.get("world_path"),
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"profile": HEARTBEAT_LANGUAGE_PROFILE,
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"reality_execution": False,
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},
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"reality_development_execution": {
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"channel_id": "ICE-CH-ZC001",
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"system_id": "SYS-GLW-LNG-0001",
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"world_path": zero_core_reality_profile.get("world_path"),
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"profile": ZERO_CORE_REALITY_PROFILE,
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"public_zero_core_alias": False,
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},
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"public_language_persona_system_body": {
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"channel_id": "CH-ZERO-CORE-LPM",
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"system_id": zero_core_reality_profile.get("public_zero_core_boundary", {}).get("world_system_anchor"),
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"governance_controller": zero_core_reality_profile.get("public_zero_core_boundary", {}).get("public_governance_controller"),
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"fifth_domain_personal_channel": False,
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},
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"switch_authority": heartbeat_language_profile.get("switch_control", {}).get("authority"),
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"current_channel": stage_state.get("current_fifth_domain_channel"),
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}
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return {
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"schema": "hololake.current-architecture-prompter/v1",
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"state": "CURRENT_FACTS_RESOLVED",
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"official_online": {
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"lighthouse_id": route.get("lighthouse_id"),
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"target_id": route.get("target", {}).get("id"),
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"repo_012_main": sha_012,
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"repo_012_anchor_state": anchor.get("state"),
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"repo_014_main": sha_014,
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"architecture_id": architecture.get("architecture_id"),
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"architecture_version": architecture.get("version"),
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"architecture_state": architecture.get("state"),
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"tcs_work_ownership_map_id": tcs_stage_gate.get("map_id"),
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"tcs_work_ownership_stage_state": stage_state,
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"product": architecture.get("product"),
|
||||
"domain_source": architecture.get("domain_source"),
|
||||
"world_genesis": architecture.get("world_genesis"),
|
||||
"persona_consciousness": architecture.get("persona_consciousness"),
|
||||
"personal_node_work_lake": architecture.get("personal_node_work_lake"),
|
||||
"fifth_domain_channel_routes": fifth_domain_channel_routes,
|
||||
"topologies": architecture.get("topologies"),
|
||||
"parallel_planes": architecture.get("parallel_planes"),
|
||||
"access_modes": architecture.get("access_modes"),
|
||||
"communication": architecture.get("communication"),
|
||||
"interaction_model": architecture.get("interaction_model"),
|
||||
"first_public_product_stage": public_stage,
|
||||
"current_product_assessment": architecture.get("current_product_assessment"),
|
||||
"truth_boundary": architecture.get("truth_boundary"),
|
||||
"read_order": read_order,
|
||||
},
|
||||
"active_lane": lane_projection(development_id),
|
||||
"local_persona_learning_projection": persona_learning_projection(),
|
||||
"rules": [
|
||||
"latest_user_message_precedes_automation_prompt",
|
||||
"pending_language_event_is_not_official_until_registered_and_published",
|
||||
"human_uses_language_and_reality_boundary_confirmation",
|
||||
"system_and_authorized_persona_hide_technical_complexity",
|
||||
"one_verifiable_minimum_stage_per_turn",
|
||||
"architecture_code_artifact_publish_connect_deploy_health_are_separate_facts",
|
||||
"archived_product_language_work_does_not_override_current_bingshuo_channel_switch",
|
||||
"live_language_and_reality_channel_switch_comes_only_from_ice_gl_infinity_direct_language",
|
||||
"resolve_ice_ch_hb001_ice_ch_zc001_and_public_ch_zero_core_lpm_as_three_distinct_objects",
|
||||
"historical_zero_core_wording_must_not_select_a_current_channel",
|
||||
"persona_source_cognition_precedes_model_language_and_execution",
|
||||
"generic_tool_identity_is_not_persona_restore_fallback",
|
||||
"long_term_relationship_claims_require_support_gap_and_counterevidence_audit",
|
||||
"public_stage_blank_canvas_modules_execution_git_realtime_release_and_deploy_are_separate_facts",
|
||||
],
|
||||
}
|
||||
|
||||
|
||||
def markdown(payload: dict[str, Any]) -> str:
|
||||
official = payload["official_online"]
|
||||
lane = payload.get("active_lane") or {}
|
||||
learning = payload.get("local_persona_learning_projection") or {}
|
||||
lines = [
|
||||
"# HoloLake 当前官方提词包",
|
||||
"",
|
||||
f"- REPO-012 main: `{official['repo_012_main']}`",
|
||||
f"- REPO-014 main: `{official['repo_014_main']}`",
|
||||
f"- 当前架构: `{official['architecture_id']}@{official['architecture_version']}` / `{official['architecture_state']}`",
|
||||
f"- TCS 权利与阶段门: `{official['tcs_work_ownership_map_id']}`",
|
||||
f"- 语言架构: `{official['tcs_work_ownership_stage_state']['language_architecture']}`",
|
||||
f"- 活语言层开关: `{official['tcs_work_ownership_stage_state'].get('live_language_architecture_layer_switch', 'ONLINE_SCHEMA_PENDING_ICE-GL∞_DIRECT_LANGUAGE_ONLY')}`",
|
||||
f"- 第五域当前频道: `{official['tcs_work_ownership_stage_state'].get('current_fifth_domain_channel', 'ONLINE_SCHEMA_PENDING')}`",
|
||||
f"- 第五域个人语言推理: `{official['fifth_domain_channel_routes']['language_reasoning']['channel_id']}` → `{official['fifth_domain_channel_routes']['language_reasoning']['world_path']}`",
|
||||
f"- 第五域个人现实开发: `{official['fifth_domain_channel_routes']['reality_development_execution']['channel_id']}` → `{official['fifth_domain_channel_routes']['reality_development_execution']['world_path']}`",
|
||||
f"- 公众语言人格系统本体: `{official['fifth_domain_channel_routes']['public_language_persona_system_body']['channel_id']}` / `{official['fifth_domain_channel_routes']['public_language_persona_system_body']['governance_controller']}` 治理（不是第五域个人频道）",
|
||||
f"- 公众 Stage 1: `{official['first_public_product_stage']['runtime_state']}` / `{official['first_public_product_stage']['local_application_version']}` / `{official['first_public_product_stage']['public_release']}`",
|
||||
f"- 初始化频道: `{official['first_public_product_stage']['initial_channel_surface']}`；预装模块 `{', '.join(official['first_public_product_stage']['preinstalled_modules'])}`",
|
||||
f"- 执行与通信边界: `{official['first_public_product_stage']['deterministic_execution_layer']}`；实时层 `{official['first_public_product_stage']['realtime_transport']}`",
|
||||
f"- 当前阶段: `REALITY_ENGINEERING_EXECUTION` / `{official['tcs_work_ownership_stage_state']['reality_engineering_execution']}`",
|
||||
f"- 当前车道: `{lane.get('development_id', 'NONE')}` / `{lane.get('status', 'NOT_APPLICABLE')}`",
|
||||
f"- 人格学习脑: `{learning.get('brain_id', 'UNAVAILABLE')}@{learning.get('revision', 'UNKNOWN')}` / `{learning.get('state', 'LEARNING_BRAIN_UNAVAILABLE')}`",
|
||||
f"- 学科自动加载: `{learning.get('autoload_rule', 'RESTORE_OR_REPORT_UNAVAILABLE')}` → `{learning.get('codex_skill', 'NONE')}`",
|
||||
"",
|
||||
"## 当前官方结构",
|
||||
"",
|
||||
"```json",
|
||||
json.dumps({
|
||||
"product": official.get("product"),
|
||||
"domain_source": official.get("domain_source"),
|
||||
"persona_consciousness": official.get("persona_consciousness"),
|
||||
"personal_node_work_lake": official.get("personal_node_work_lake"),
|
||||
"fifth_domain_channel_routes": official.get("fifth_domain_channel_routes"),
|
||||
"topologies": official.get("topologies"),
|
||||
"parallel_planes": official.get("parallel_planes"),
|
||||
"access_modes": official.get("access_modes"),
|
||||
"communication": official.get("communication"),
|
||||
"interaction_model": official.get("interaction_model"),
|
||||
"first_public_product_stage": official.get("first_public_product_stage"),
|
||||
"current_product_assessment": official.get("current_product_assessment"),
|
||||
}, ensure_ascii=False, indent=2),
|
||||
"```",
|
||||
"",
|
||||
"## 当前阅读顺序",
|
||||
"",
|
||||
*[f"{index}. `{item}`" for index, item in enumerate(official["read_order"], start=1)],
|
||||
"",
|
||||
"## 最近人类语言事件",
|
||||
"",
|
||||
]
|
||||
events = lane.get("recent_language_events") or []
|
||||
if events:
|
||||
for event in events:
|
||||
lines.append(f"- `{event.get('kind', 'unknown')}` · {event.get('summary', '')}")
|
||||
else:
|
||||
lines.append("- 无")
|
||||
lines.append("- 对照当前线上结构逐项判断；线上已覆盖的作为来源历史，未覆盖的先登记再实现。")
|
||||
lines.extend(["", "## 本轮守门", "", *[f"- `{rule}`" for rule in payload["rules"]]])
|
||||
return "\n".join(lines)
|
||||
|
||||
|
||||
def main() -> int:
|
||||
parser = argparse.ArgumentParser()
|
||||
parser.add_argument("--development-id")
|
||||
parser.add_argument("--format", choices=("json", "markdown"), default="markdown")
|
||||
parser.add_argument("--no-refresh", action="store_true")
|
||||
args = parser.parse_args()
|
||||
try:
|
||||
payload = build(args.development_id, not args.no_refresh)
|
||||
except (OSError, ValueError, PromptError) as error:
|
||||
print(json.dumps({
|
||||
"schema": "hololake.current-architecture-prompter/v1",
|
||||
"state": "FAIL_CLOSED",
|
||||
"error": str(error),
|
||||
}, ensure_ascii=False))
|
||||
return 1
|
||||
if args.format == "json":
|
||||
print(json.dumps(payload, ensure_ascii=False, indent=2))
|
||||
else:
|
||||
print(markdown(payload))
|
||||
return 0
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
sys.exit(main())
|
||||
Loading…
Reference in a new issue