chore: update skill release readme source

Co-authored-by: Cursor <cursoragent@cursor.com>

.github/workflows/publish.yml

@@ -4,9 +4,6 @@ on:
   push:
     branches:
       - main
-    tags:
-      - "v*"
-  workflow_dispatch:
 
 jobs:
   publish:
@@ -25,13 +22,6 @@ jobs:
     steps:
       - uses: https://git.jc2009.com/admin/actions-checkout@v4
 
-      - name: Resolve and patch package version
-        env:
-          GITHUB_REF: ${{ github.ref }}
-          GITHUB_RUN_NUMBER: ${{ github.run_number }}
-          GITHUB_RUN_ID: ${{ github.run_id }}
-        run: python3.12 tools/ci_set_package_version.py
-
       - name: Install build tools
         run: python3.12 -m pip install --upgrade build twine --break-system-packages
 

.github/workflows/reusable-release-skill.yaml

@@ -108,6 +108,13 @@ jobs:
             '        shutil.copytree(src, dst, ignore=ignore_fn, dirs_exist_ok=True)' \
             '' \
             "shutil.copy2('SKILL.md', os.path.join(PACKAGE, 'SKILL.md'))" \
+            "readme_src = os.path.abspath('README.md')" \
+            "readme_dst = os.path.join(PACKAGE, 'README.md')" \
+            'if os.path.isfile(readme_src):' \
+            "    shutil.copy2(readme_src, readme_dst)" \
+            "    print('Copied README.md')" \
+            'if os.path.isfile(readme_src) and not os.path.isfile(readme_dst):' \
+            "    raise RuntimeError('README.md exists in skill root but was not packaged')" \
             "copy_dir('references', os.path.join(PACKAGE, 'references'), references_ignore)" \
             "copy_dir('assets', os.path.join(PACKAGE, 'assets'), common_ignore)" \
             "copy_dir('tests', os.path.join(PACKAGE, 'tests'), common_ignore)" \
@@ -144,7 +151,7 @@ jobs:
           skill_readme_md = (post.content or '').strip()
           skill_description = metadata.get('description')
           metadata['readme_md'] = skill_readme_md
-          readme_path = os.path.join('references', 'README.md')
+          readme_path = 'README.md'
           if os.path.isfile(readme_path):
               try:
                   readme_post = frontmatter.load(readme_path)

README.md

@@ -86,15 +86,39 @@ send_prompt_via_composer(page, "第一行\n第二行")
 
 读取背景音乐、字体、水印和 ffmpeg 工具。
 
-如果目录不存在，会优先通过 ZIP 下载公开仓库：
+如果目录不存在，会优先下载稳定 release bundle（不依赖用户电脑安装 Git）：
 
-`https://git.jc2009.com/client-commons/media-assets/archive/main.zip`
+`https://git.jc2009.com/client-commons/media-assets/releases/download/vlatest/media-assets.zip`
 
-这不依赖用户电脑安装 Git。
+bundle 内含背景音乐、字体与水印；**不包含** ffmpeg 二进制。ffmpeg / ffprobe 仍由 bundle 内 `manifest.json` 的 `tools.ffmpeg` 下载源单独拉取。
 
 可通过环境变量覆盖：
 
-`MEDIA_ASSETS_ROOT=/path/to/custom/media-assets`
+- `MEDIA_ASSETS_ROOT=/path/to/custom/media-assets` — 本地资源目录
+- `MEDIA_ASSETS_BUNDLE_URL=https://example.com/media-assets.zip` — bundle 下载地址
+
+### Runtime diagnostics（统一 health 诊断）
+
+`jiangchang_skill_core.runtime_diagnostics` 提供各 Skill 共用的 Runtime / media-assets / ffmpeg 探测，避免每个技能各自复制检查逻辑。Skill 的 `health` 命令可调用：
+
+```python
+from jiangchang_skill_core import (
+    collect_runtime_diagnostics,
+    format_runtime_health_lines,
+    runtime_diagnostics_dict,
+)
+
+diag = collect_runtime_diagnostics(
+    skill_slug="my-skill",
+    platform_kit_min_version="1.0.10",  # 可选；省略则只报告当前版本
+    skill_root="/path/to/my-skill",     # 可选；用于检测 vendored jiangchang_skill_core
+)
+for line in format_runtime_health_lines(diag):
+    print(line)
+print(runtime_diagnostics_dict(diag))  # 可 JSON 序列化
+```
+
+诊断只读探测本地状态，不会触发 media-assets 下载。
 
 ### 录屏合成（`screencast`）
 
@@ -118,17 +142,18 @@ run_screencast(
 
 ## 5. 发版流程（维护者）
 
-### main 分支自动预发布
+### 发布规则
 
-每次推送到 `main` 会触发 `.github/workflows/publish.yml`，自动构建并发布 **post 预发布版本**（仅供 CI 流水线内部使用，**不是**正式版本线）。
+- jiangchang-platform-kit **只发布正式版本**。
-
+- 每次需要发布公共能力时，先 bump `pyproject.toml` 的 `version`（例如 `1.0.10` → `1.0.11`）。
-正式版本线使用 **1.0.x** semver，通过 git tag 发布。
+- 推送 `main` 后，`.github/workflows/publish.yml` 会构建并上传该正式版本到 Gitea PyPI。
+- 发布包版本必须等于 `pyproject.toml` 中的 `version`；若该版本已存在，上传会失败，需继续 bump 版本号后再推送。
 
 ```bash
 git push origin main
 ```
 
-测试人员升级安装（始终安装当前正式 tag 对应的版本，例如 `1.0.9`）：
+升级安装：
 
 ```bash
 python -m pip install --upgrade \
@@ -137,15 +162,6 @@ python -m pip install --upgrade \
   jiangchang-platform-kit
 ```
 
-### 正式版本（tag）
-
-打 tag 并推送后，发布 **去掉 `v` 前缀** 的正式版本号（例如 `v1.0.9` → PyPI 包 `1.0.9`）：
-
-```bash
-git tag v1.0.9
-git push origin v1.0.9
-```
-
 ### 安装后验证
 
 ```bash

pyproject.toml

@@ -4,7 +4,7 @@ build-backend = "setuptools.build_meta"
 
 [project]
 name = "jiangchang-platform-kit"
-version = "1.0.10"
+version = "1.0.14"
 description = "匠厂平台共享组件:Skill 实体 SDK + 桌面应用自动化 SDK"
 readme = "README.md"
 requires-python = ">=3.10"

src/jiangchang_desktop_sdk/__init__.py

@@ -23,7 +23,7 @@ __all__ = [
     "LaunchError",
     "GatewayDownError",
 ]
-__version__ = "1.0.9"
+__version__ = "1.0.13"
 
 
 def __getattr__(name: str):

src/jiangchang_skill_core/__init__.py

@@ -25,7 +25,10 @@ from .media_assets import (
     MediaAssetsStatus,
     background_music_issue,
     ensure_media_assets,
+    is_git_lfs_pointer,
+    is_usable_audio_file,
     pick_background_music,
+    probe_background_music,
     probe_ffmpeg,
     probe_media_assets,
     resolve_ffmpeg,
@@ -33,6 +36,15 @@ from .media_assets import (
     resolve_media_assets_root,
     resolve_music_dir,
 )
+from .runtime_diagnostics import (
+    RuntimeDiagnostics,
+    RuntimeIssue,
+    collect_runtime_diagnostics,
+    format_runtime_health_lines,
+    is_jiangchang_skill_core_from_skill_tree,
+    runtime_diagnostics_dict,
+    version_ge,
+)
 
 try:
     from . import rpa
@@ -46,8 +58,16 @@ __all__ = [
     "EntitlementResult",
     "EntitlementServiceError",
     "MediaAssetsStatus",
+    "RuntimeDiagnostics",
+    "RuntimeIssue",
     "background_music_issue",
+    "collect_runtime_diagnostics",
     "ensure_media_assets",
+    "format_runtime_health_lines",
+    "is_git_lfs_pointer",
+    "is_jiangchang_skill_core_from_skill_tree",
+    "is_usable_audio_file",
+    "probe_background_music",
     "probe_ffmpeg",
     "probe_media_assets",
     "pick_background_music",
@@ -55,6 +75,8 @@ __all__ = [
     "resolve_ffprobe",
     "resolve_media_assets_root",
     "resolve_music_dir",
+    "runtime_diagnostics_dict",
+    "version_ge",
     "apply_cli_local_defaults",
     "attach_unified_file_handler",
     "ensure_env_file",

src/jiangchang_skill_core/media_assets.py

@@ -16,11 +16,12 @@ import zipfile
 from dataclasses import dataclass, field
 from datetime import datetime
 from pathlib import Path
-from typing import Optional
+from typing import Any, Mapping, Optional
 
-MEDIA_ASSETS_ZIP_URL = (
+MEDIA_ASSETS_BUNDLE_URL = (
-    "https://git.jc2009.com/client-commons/media-assets/archive/main.zip"
+    "https://git.jc2009.com/client-commons/media-assets/releases/download/vlatest/media-assets.zip"
 )
+MEDIA_ASSETS_ZIP_URL = MEDIA_ASSETS_BUNDLE_URL
 MEDIA_ASSETS_GIT_URL = "https://git.jc2009.com/client-commons/media-assets"
 
 _WIN_DEFAULT_DATA_ROOT = Path(r"D:\jiangchang-data")
@@ -28,17 +29,20 @@ _NON_WIN_DEFAULT_DATA_ROOT = Path.home() / ".jiangchang"
 
 _AUDIO_EXTENSIONS = {".mp3", ".wav", ".m4a", ".aac"}
 _GIT_LFS_POINTER_PREFIX = b"version https://git-lfs.github.com/spec/v1"
-_MIN_AUDIO_BYTES = 128
+_MIN_AUDIO_BYTES = 1024
 
 
-def _is_git_lfs_pointer(path: Path) -> bool:
+def is_git_lfs_pointer(path: str | Path) -> bool:
     try:
-        head = path.read_bytes()[:256]
+        head = Path(path).read_bytes()[:256]
     except OSError:
         return False
     return head.startswith(_GIT_LFS_POINTER_PREFIX)
 
 
+_is_git_lfs_pointer = is_git_lfs_pointer
+
+
 def _enumerate_audio_like(music_dir: Path) -> list[Path]:
     return [
         path
@@ -75,21 +79,25 @@ def _needs_music_content_repair(status: MediaAssetsStatus) -> bool:
     )
 
 
-def _is_usable_audio_file(path: Path) -> bool:
+def is_usable_audio_file(path: str | Path, *, min_bytes: int = _MIN_AUDIO_BYTES) -> bool:
-    if not path.is_file():
+    p = Path(path)
+    if not p.is_file():
         return False
-    if path.suffix.lower() not in _AUDIO_EXTENSIONS:
+    if p.suffix.lower() not in _AUDIO_EXTENSIONS:
         return False
-    if _is_git_lfs_pointer(path):
+    if is_git_lfs_pointer(p):
         return False
     try:
-        if path.stat().st_size < _MIN_AUDIO_BYTES:
+        if p.stat().st_size < min_bytes:
             return False
     except OSError:
         return False
     return True
 
 
+_is_usable_audio_file = is_usable_audio_file
+
+
 @dataclass
 class MediaAssetsStatus:
     root: Path
@@ -109,6 +117,12 @@ def _env_dict(env: dict[str, str] | None) -> dict[str, str]:
     return env if env is not None else dict(os.environ)
 
 
+def _media_assets_bundle_url(env: dict[str, str] | None = None) -> str:
+    env_map = _env_dict(env)
+    override = (env_map.get("MEDIA_ASSETS_BUNDLE_URL") or "").strip()
+    return override or MEDIA_ASSETS_BUNDLE_URL
+
+
 def _resolve_jiangchang_data_root(
     data_root: str | Path | None = None,
     env: dict[str, str] | None = None,
@@ -474,12 +488,16 @@ def _try_download_via_zip(
     shared: Path,
     target: Path,
     warnings: list[str],
+    *,
+    env: dict[str, str] | None = None,
+    url: str | None = None,
 ) -> bool:
     download_root = _download_dir(shared)
     download_root.mkdir(parents=True, exist_ok=True)
     zip_path = download_root / "media-assets.zip"
     extracted = download_root / "extracted"
     staging = download_root / "staging"
+    bundle_url = url or _media_assets_bundle_url(env)
 
     try:
         if staging.exists():
@@ -487,7 +505,7 @@ def _try_download_via_zip(
         if extracted.exists():
             shutil.rmtree(extracted, ignore_errors=True)
 
-        _download_zip(MEDIA_ASSETS_ZIP_URL, zip_path)
+        _download_zip(bundle_url, zip_path)
         _extract_zip(zip_path, extracted)
 
         found = _find_media_assets_root_in_tree(extracted)
@@ -565,10 +583,15 @@ def _needs_media_repo_content(status: MediaAssetsStatus) -> bool:
     )
 
 
-def _maybe_repair_music_content(root: Path, status: MediaAssetsStatus) -> MediaAssetsStatus:
+def _maybe_repair_music_content(
+    root: Path,
+    status: MediaAssetsStatus,
+    *,
+    env: dict[str, str] | None = None,
+) -> MediaAssetsStatus:
     if not _needs_music_content_repair(status):
         return status
-    if _media_assets_root_overridden(None):
+    if _media_assets_root_overridden(env):
         return status
 
     warnings: list[str] = []
@@ -581,7 +604,7 @@ def _maybe_repair_music_content(root: Path, status: MediaAssetsStatus) -> MediaA
             return _maybe_ensure_ffmpeg_tools(root, refreshed)
 
     shared = _shared_parent(root)
-    if _try_download_via_zip(shared, root, warnings):
+    if _try_download_via_zip(shared, root, warnings, env=env):
         refreshed = _inspect_media_assets(root, source="zip")
         for warning in warnings:
             if warning not in refreshed.warnings:
@@ -631,12 +654,13 @@ def ensure_media_assets(
     shared.mkdir(parents=True, exist_ok=True)
     warnings: list[str] = []
 
-    if _try_download_via_zip(shared, root, warnings):
+    if _try_download_via_zip(shared, root, warnings, env=env_map):
         return _maybe_ensure_ffmpeg_tools(
             root,
             _maybe_repair_music_content(
                 root,
                 _inspect_media_assets(root, source="zip"),
+                env=env_map,
             ),
         )
 
@@ -650,6 +674,7 @@ def ensure_media_assets(
                     root,
                     source="git" if _is_git_repo(root) else "local",
                 ),
+                env=env_map,
             ),
         )
 
@@ -657,7 +682,7 @@ def ensure_media_assets(
     for warning in warnings:
         if warning not in final.warnings:
             final.warnings.append(warning)
-    repaired = _maybe_repair_music_content(root, final)
+    repaired = _maybe_repair_music_content(root, final, env=env_map)
     for warning in warnings:
         if warning not in repaired.warnings:
             repaired.warnings.append(warning)
@@ -706,6 +731,46 @@ def resolve_music_dir(
     return status.music_dir
 
 
+def probe_background_music(
+    root: str | Path | None = None,
+    *,
+    env: Mapping[str, str] | None = None,
+) -> dict[str, Any]:
+    """只读探测背景音乐目录，不触发 media-assets 下载。"""
+    env_map = _env_dict(dict(env) if env is not None else None)
+    if root is not None:
+        music_dir = Path(root) / "music"
+        if not music_dir.is_dir():
+            music_dir = Path(root) if Path(root).is_dir() else None
+    else:
+        data_root = (env_map.get("JIANGCHANG_DATA_ROOT") or env_map.get("CLAW_DATA_ROOT") or "").strip()
+        assets_root = resolve_media_assets_root(data_root or None, env_map)
+        status = _inspect_media_assets(assets_root, source="local")
+        music_dir = status.music_dir
+
+    music_root = str(music_dir) if music_dir is not None else None
+    if music_dir is None or not music_dir.is_dir():
+        return {
+            "music_root": music_root,
+            "mp3_count": 0,
+            "usable_count": 0,
+            "sample_path": None,
+            "issue": "music_dir_missing",
+        }
+
+    mp3_files = [path for path in music_dir.rglob("*.mp3") if path.is_file()]
+    usable = [path for path in music_dir.rglob("*") if is_usable_audio_file(path)]
+    issue = _music_content_issue(music_dir)
+    sample = str(sorted(usable, key=lambda p: str(p).lower())[0]) if usable else None
+    return {
+        "music_root": music_root,
+        "mp3_count": len(mp3_files),
+        "usable_count": len(usable),
+        "sample_path": sample,
+        "issue": issue,
+    }
+
+
 def background_music_issue(
     data_root: str | Path | None = None,
     env: dict[str, str] | None = None,

src/jiangchang_skill_core/rpa/video_session.py

@@ -1,9 +1,14 @@
-"""RPA 运行录屏会话：ffmpeg 桌面录制 → 字幕 + 背景音乐 → 最终 MP4。"""
+"""RPA 运行录屏会话：ffmpeg 桌面录制 → 字幕 + 旁白 + 背景音乐 → 最终 MP4。
+
+背景音乐默认循环铺满录屏时长并在结尾淡出；旁白使用 Windows 本地 SAPI 合成，
+失败时静默降级，不影响视频生成。Skill 无需额外配置。
+"""
 
 from __future__ import annotations
 
 import asyncio
 import os
+import re
 import subprocess
 import sys
 import time
@@ -18,6 +23,7 @@ from ..media_assets import (
     ensure_media_assets,
     pick_background_music,
     resolve_ffmpeg,
+    resolve_ffprobe,
 )
 
 _JIANGCHANG_SUBTITLE_STYLE = (
@@ -28,6 +34,54 @@ _JIANGCHANG_SUBTITLE_STYLE = (
 
 _CAPTURE_FRAMERATE = 15
 
+# 背景音乐循环 + 结尾淡出（默认策略，非 env 配置）
+_MUSIC_VOLUME = 0.12
+_VOICE_VOLUME = 1.0
+_MUSIC_FADE_OUT_SECONDS = 3.0
+_MIN_MUSIC_FADE_OUT_SECONDS = 1.0
+_SHORT_VIDEO_FADE_RATIO = 0.25
+
+_VOICEOVER_MAX_CHARS = 60
+_VOICEOVER_DEDUP_SECONDS = 10.0
+_VOICEOVER_MIN_GAP_SECONDS = 2.0
+
+_INTRO_BUFFER_SECONDS = 5.0
+_INTRO_STABILIZE_SECONDS = 1.0
+_OUTRO_BUFFER_SECONDS = 5.0
+
+_VOICEOVER_SKIP_SUBSTRINGS = (
+    "等待 1-5s",
+    "跳过重复",
+    "写入联系人库",
+    "探针模式",
+    "异常",
+    "失败",
+)
+
+_VOICEOVER_IMPORTANT_SUBSTRINGS = (
+    "开始",
+    "打开",
+    "启动",
+    "定位",
+    "输入",
+    "点击",
+    "搜索",
+    "等待搜索结果",
+    "检查登录状态",
+    "处理验证码",
+    "等待人工验证",
+    "解析",
+    "提取",
+    "采集完成",
+    "部分完成",
+    "完成",
+)
+
+# 明显技术日志：时间戳前缀、纯数字进度等
+_TECH_LOG_RE = re.compile(
+    r"^\d{4}-\d{2}-\d{2}|^\[\w+\]|^DEBUG:|^INFO:|^WARN:|^ERROR:"
+)
+
 
 def _record_video_enabled() -> bool:
     return config.get_bool("OPENCLAW_RECORD_VIDEO", default=False)
@@ -41,6 +95,68 @@ def _resolve_ffmpeg_exe() -> Optional[Path]:
     return path if path.is_file() else None
 
 
+def _resolve_ffprobe_exe() -> Optional[Path]:
+    """定位 ffprobe；优先 media_assets bundle，否则尝试 ffmpeg 同目录。"""
+    ffprobe = resolve_ffprobe()
+    if ffprobe is not None:
+        path = Path(ffprobe)
+        if path.is_file():
+            return path
+    ffmpeg = _resolve_ffmpeg_exe()
+    if ffmpeg is not None:
+        sibling = ffmpeg.parent / ("ffprobe.exe" if sys.platform == "win32" else "ffprobe")
+        if sibling.is_file():
+            return sibling
+    return None
+
+
+def _probe_media_duration_seconds(
+    ffprobe_exe: Optional[Path], media_path: Path
+) -> Optional[float]:
+    if ffprobe_exe is None or not media_path.is_file():
+        return None
+    try:
+        result = subprocess.run(
+            [
+                str(ffprobe_exe),
+                "-v",
+                "error",
+                "-show_entries",
+                "format=duration",
+                "-of",
+                "default=nk=1:nw=1",
+                str(media_path),
+            ],
+            capture_output=True,
+            text=True,
+            encoding="utf-8",
+            errors="replace",
+            timeout=30,
+        )
+        if result.returncode != 0:
+            return None
+        raw = (result.stdout or "").strip()
+        if not raw:
+            return None
+        value = float(raw)
+        return value if value > 0 else None
+    except Exception:
+        return None
+
+
+def _music_fade_params(
+    duration_seconds: Optional[float],
+) -> tuple[Optional[float], Optional[float]]:
+    if duration_seconds is None or duration_seconds <= 0:
+        return (None, None)
+    fade = min(
+        _MUSIC_FADE_OUT_SECONDS,
+        max(_MIN_MUSIC_FADE_OUT_SECONDS, duration_seconds * _SHORT_VIDEO_FADE_RATIO),
+    )
+    fade_start = max(0.0, duration_seconds - fade)
+    return (fade_start, fade)
+
+
 def _resolve_music_file(warnings: List[str]) -> Optional[Path]:
     music = pick_background_music()
     if music is not None:
@@ -59,6 +175,183 @@ class _StepEntry:
     duration: float = 4.0
 
 
+@dataclass
+class _VoiceClip:
+    path: Path
+    delay_ms: int
+
+
+def _voiceover_text_for_step(text: str) -> Optional[str]:
+    """过滤适合朗读的步骤文本；噪音/技术日志返回 None。"""
+    cleaned = (text or "").strip()
+    if not cleaned:
+        return None
+    if _TECH_LOG_RE.search(cleaned):
+        return None
+    for skip in _VOICEOVER_SKIP_SUBSTRINGS:
+        if skip in cleaned:
+            return None
+    if len(cleaned) > _VOICEOVER_MAX_CHARS:
+        cleaned = cleaned[:_VOICEOVER_MAX_CHARS]
+    return cleaned
+
+
+def _is_important_voiceover(text: str) -> bool:
+    for important in _VOICEOVER_IMPORTANT_SUBSTRINGS:
+        if important in text:
+            return True
+    return False
+
+
+def _select_voiceover_clips(
+    entries: List[_StepEntry],
+) -> List[tuple[_StepEntry, str]]:
+    """按时间排序，去重并保证旁白间隔；关键动作可绕过最小间隔。"""
+    result: List[tuple[_StepEntry, str]] = []
+    last_text_at: Dict[str, float] = {}
+    last_spoken_at = -_VOICEOVER_MIN_GAP_SECONDS
+
+    for entry in sorted(entries, key=lambda e: e.start):
+        spoken = _voiceover_text_for_step(entry.text)
+        if not spoken:
+            continue
+        prev = last_text_at.get(spoken)
+        if prev is not None and entry.start - prev < _VOICEOVER_DEDUP_SECONDS:
+            continue
+        if (
+            not _is_important_voiceover(spoken)
+            and entry.start - last_spoken_at < _VOICEOVER_MIN_GAP_SECONDS
+        ):
+            continue
+        last_text_at[spoken] = entry.start
+        last_spoken_at = entry.start
+        result.append((entry, spoken))
+    return result
+
+
+def _tts_available() -> bool:
+    return sys.platform == "win32"
+
+
+def _sapi_synthesize_wav(text: str, output_wav: Path) -> bool:
+    if not _tts_available():
+        return False
+    output_wav.parent.mkdir(parents=True, exist_ok=True)
+    out_str = str(output_wav.resolve()).replace("'", "''")
+    text_esc = text.replace("'", "''")
+    ps_script = (
+        "Add-Type -AssemblyName System.Speech; "
+        "$s = New-Object System.Speech.Synthesis.SpeechSynthesizer; "
+        f"$s.SetOutputToWaveFile('{out_str}'); "
+        f"$s.Speak('{text_esc}'); "
+        "$s.Dispose()"
+    )
+    try:
+        result = subprocess.run(
+            ["powershell", "-NoProfile", "-NonInteractive", "-Command", ps_script],
+            capture_output=True,
+            text=True,
+            encoding="utf-8",
+            errors="replace",
+            timeout=120,
+        )
+        return (
+            result.returncode == 0
+            and output_wav.is_file()
+            and output_wav.stat().st_size > 0
+        )
+    except Exception:
+        return False
+
+
+def _mix_voice_clips(
+    ffmpeg_exe: Path, clips: List[_VoiceClip], output_wav: Path
+) -> bool:
+    if not clips:
+        return False
+    output_wav.parent.mkdir(parents=True, exist_ok=True)
+
+    filter_parts: List[str] = []
+    mix_labels: List[str] = []
+    cmd_inputs: List[str] = []
+
+    for i, clip in enumerate(clips):
+        cmd_inputs.extend(["-i", str(clip.path)])
+        label = f"v{i}"
+        filter_parts.append(
+            f"[{i}:a]adelay={clip.delay_ms}|{clip.delay_ms},"
+            f"volume={_VOICE_VOLUME}[{label}]"
+        )
+        mix_labels.append(f"[{label}]")
+
+    if len(clips) == 1:
+        filter_complex = filter_parts[0].replace(f"[v0]", "[out]")
+        # single clip: relabel output
+        filter_complex = (
+            f"[0:a]adelay={clips[0].delay_ms}|{clips[0].delay_ms},"
+            f"volume={_VOICE_VOLUME}[out]"
+        )
+    else:
+        filter_complex = (
+            ";".join(filter_parts)
+            + ";"
+            + "".join(mix_labels)
+            + f"amix=inputs={len(clips)}:duration=longest:dropout_transition=0:normalize=0[out]"
+        )
+
+    cmd_tail = [
+        "-y",
+        *cmd_inputs,
+        "-filter_complex",
+        filter_complex,
+        "-map",
+        "[out]",
+        str(output_wav),
+    ]
+    ok, _ = _run_ffmpeg(ffmpeg_exe, cmd_tail)
+    return ok and output_wav.is_file()
+
+
+def _synthesize_step_voiceover(
+    entries: List[_StepEntry],
+    output_wav: Path,
+    warnings: List[str],
+    *,
+    ffmpeg_exe: Optional[Path] = None,
+) -> Optional[Path]:
+    """本地 Windows SAPI 逐条合成旁白并按步骤 start 时间对齐；失败返回 None。"""
+    if not _tts_available():
+        warnings.append("tts_unsupported_platform")
+        return None
+
+    clips_to_speak = _select_voiceover_clips(entries)
+    if not clips_to_speak:
+        return None
+
+    voice_dir = output_wav.parent
+    voice_dir.mkdir(parents=True, exist_ok=True)
+    temp_clips: List[_VoiceClip] = []
+
+    for i, (entry, spoken) in enumerate(clips_to_speak):
+        clip_path = voice_dir / f"voice_{i:03d}.wav"
+        if not _sapi_synthesize_wav(spoken, clip_path):
+            warnings.append("tts_synthesis_failed")
+            return None
+        delay_ms = max(0, int(entry.start * 1000))
+        temp_clips.append(_VoiceClip(path=clip_path, delay_ms=delay_ms))
+
+    if ffmpeg_exe is None:
+        ffmpeg_exe = _resolve_ffmpeg_exe()
+    if ffmpeg_exe is None:
+        warnings.append("tts_mix_ffmpeg_missing")
+        return None
+
+    if not _mix_voice_clips(ffmpeg_exe, temp_clips, output_wav):
+        warnings.append("tts_mix_failed")
+        return None
+    return output_wav
+
+
 def _generate_srt(entries: List[_StepEntry], output_path: str) -> None:
     MIN_DURATION = 1.0
     GAP = 0.1
@@ -117,27 +410,16 @@ def _run_ffmpeg(ffmpeg_exe: Path, cmd_tail: List[str]) -> tuple[bool, str]:
     return True, ""
 
 
-def _build_desktop_record_cmd(ffmpeg_exe: Path, capture_path: str) -> Optional[List[str]]:
+def _build_music_filter(
-    """Windows gdigrab 全桌面录制；非 Windows 返回 None。"""
+    audio_input_idx: int,
-    if sys.platform != "win32":
+    fade_start: Optional[float],
-        return None
+    fade_duration: Optional[float],
-    return _ffmpeg_cmd(
+    output_label: str = "music",
-        ffmpeg_exe,
+) -> str:
-        "-y",
+    filt = f"[{audio_input_idx}:a]volume={_MUSIC_VOLUME}"
-        "-f",
+    if fade_start is not None and fade_duration is not None:
-        "gdigrab",
+        filt += f",afade=t=out:st={fade_start}:d={fade_duration}"
-        "-framerate",
+    return filt + f"[{output_label}]"
-        str(_CAPTURE_FRAMERATE),
-        "-i",
-        "desktop",
-        "-c:v",
-        "libx264",
-        "-preset",
-        "ultrafast",
-        "-pix_fmt",
-        "yuv420p",
-        capture_path,
-    )
 
 
 def _compose_capture_mp4(
@@ -147,7 +429,8 @@ def _compose_capture_mp4(
     output_path: Path,
     *,
     music_file: Optional[Path] = None,
-    music_volume: float = 0.15,
+    voiceover_file: Optional[Path] = None,
+    warnings: Optional[List[str]] = None,
 ) -> tuple[bool, str]:
     output_path.parent.mkdir(parents=True, exist_ok=True)
     srt_esc = _escape_srt_path(str(srt_path.resolve()))
@@ -156,38 +439,77 @@ def _compose_capture_mp4(
         f":force_style='{_JIANGCHANG_SUBTITLE_STYLE}'"
     )
 
-    if music_file and music_file.is_file():
+    has_music = music_file is not None and music_file.is_file()
-        filter_complex = (
+    has_voice = voiceover_file is not None and voiceover_file.is_file()
-            f"[0:v]{subtitle_filter}[vout];"
+
-            f"[1:a]volume={music_volume},apad[aout]"
+    fade_start: Optional[float] = None
+    fade_duration: Optional[float] = None
+    if has_music:
+        ffprobe = _resolve_ffprobe_exe()
+        duration = _probe_media_duration_seconds(ffprobe, capture_path)
+        fade_start, fade_duration = _music_fade_params(duration)
+        if fade_start is None and warnings is not None:
+            warnings.append("video_duration_probe_failed_for_music_fade")
+
+    if has_music or has_voice:
+        cmd_tail: List[str] = ["-y", "-i", str(capture_path)]
+        input_idx = 1
+        filter_parts: List[str] = [f"[0:v]{subtitle_filter}[vout]"]
+        audio_labels: List[str] = []
+
+        if has_music:
+            cmd_tail.extend(["-stream_loop", "-1", "-i", str(music_file)])
+            music_label = "aout" if not has_voice else "music"
+            filter_parts.append(
+                _build_music_filter(input_idx, fade_start, fade_duration, music_label)
+            )
+            if has_voice:
+                audio_labels.append(f"[{music_label}]")
+            input_idx += 1
+
+        if has_voice:
+            cmd_tail.extend(["-i", str(voiceover_file)])
+            if has_music:
+                filter_parts.append(
+                    f"[{input_idx}:a]volume={_VOICE_VOLUME}[voice]"
+                )
+                audio_labels.append("[voice]")
+            else:
+                # voice-only：apad 补静音，避免 -shortest 按旁白长度截短视频
+                filter_parts.append(
+                    f"[{input_idx}:a]volume={_VOICE_VOLUME},apad[aout]"
+                )
+            input_idx += 1
+
+        if len(audio_labels) == 2:
+            filter_parts.append(
+                "".join(audio_labels) + "amix=inputs=2:normalize=0[aout]"
+            )
+
+        cmd_tail.extend(
+            [
+                "-filter_complex",
+                ";".join(filter_parts),
+                "-map",
+                "[vout]",
+                "-map",
+                "[aout]",
+                "-c:v",
+                "libx264",
+                "-preset",
+                "fast",
+                "-crf",
+                "23",
+                "-c:a",
+                "aac",
+                "-b:a",
+                "128k",
+                "-shortest",
+                "-pix_fmt",
+                "yuv420p",
+                str(output_path),
+            ]
         )
-        cmd_tail = [
-            "-y",
-            "-i",
-            str(capture_path),
-            "-i",
-            str(music_file),
-            "-filter_complex",
-            filter_complex,
-            "-map",
-            "[vout]",
-            "-map",
-            "[aout]",
-            "-c:v",
-            "libx264",
-            "-preset",
-            "fast",
-            "-crf",
-            "23",
-            "-c:a",
-            "aac",
-            "-b:a",
-            "128k",
-            "-shortest",
-            "-pix_fmt",
-            "yuv420p",
-            str(output_path),
-        ]
     else:
         cmd_tail = [
             "-y",
@@ -212,6 +534,29 @@ def _compose_capture_mp4(
     return _run_ffmpeg(ffmpeg_exe, cmd_tail)
 
 
+def _build_desktop_record_cmd(ffmpeg_exe: Path, capture_path: str) -> Optional[List[str]]:
+    """Windows gdigrab 全桌面录制；非 Windows 返回 None。"""
+    if sys.platform != "win32":
+        return None
+    return _ffmpeg_cmd(
+        ffmpeg_exe,
+        "-y",
+        "-f",
+        "gdigrab",
+        "-framerate",
+        str(_CAPTURE_FRAMERATE),
+        "-i",
+        "desktop",
+        "-c:v",
+        "libx264",
+        "-preset",
+        "ultrafast",
+        "-pix_fmt",
+        "yuv420p",
+        capture_path,
+    )
+
+
 class RpaVideoSession:
     """Service/RPA 层统一 ffmpeg 桌面录屏；OPENCLAW_RECORD_VIDEO=1 时启用成片流程。"""
 
@@ -222,11 +567,13 @@ class RpaVideoSession:
         skill_data_dir: str,
         batch_id: str,
         title: str = "",
+        closing_title: str = "",
     ) -> None:
         self.skill_slug = skill_slug
         self.skill_data_dir = os.path.abspath(skill_data_dir)
         self.batch_id = batch_id
         self.title = title
+        self.closing_title = closing_title
         self.enabled = _record_video_enabled()
         self.warnings: List[str] = []
         self.output_video_path: Optional[str] = None
@@ -242,12 +589,17 @@ class RpaVideoSession:
             self.skill_data_dir, "rpa-artifacts", batch_id
         )
         self._subtitles_dir = os.path.join(self._artifact_root, "subtitles")
+        self._voiceover_dir = os.path.join(self._artifact_root, "voiceover")
         self._logs_dir = os.path.join(self._artifact_root, "logs")
         self._ffmpeg_record_log_path = os.path.join(self._logs_dir, "ffmpeg-record.log")
         self._capture_path = os.path.join(self._artifact_root, "capture.mp4")
         self._srt_path = os.path.join(self._subtitles_dir, f"{self._video_stem}.srt")
+        self._voiceover_path = os.path.join(self._voiceover_dir, "voiceover.wav")
         self._planned_output = os.path.join(self._videos_dir, f"{self._video_stem}.mp4")
 
+        self._music_path: Optional[str] = None
+        self._voiceover_output: Optional[str] = None
+
         self._steps: List[_StepEntry] = []
         self._t0: Optional[float] = None
         self._ffmpeg_proc: Optional[subprocess.Popen] = None
@@ -256,6 +608,7 @@ class RpaVideoSession:
         if self.enabled:
             os.makedirs(self._videos_dir, exist_ok=True)
             os.makedirs(self._subtitles_dir, exist_ok=True)
+            os.makedirs(self._voiceover_dir, exist_ok=True)
             os.makedirs(self._logs_dir, exist_ok=True)
             os.makedirs(self._artifact_root, exist_ok=True)
 
@@ -366,19 +719,80 @@ class RpaVideoSession:
         self._close_ffmpeg_record_log()
         time.sleep(0.3)
 
+    async def _safe_add_step(self, text: str, *, duration: float = 4.0) -> None:
+        try:
+            self.add_step(text, duration=duration)
+        except Exception:
+            pass
+
     async def __aenter__(self) -> "RpaVideoSession":
         if self.enabled:
             self._t0 = time.monotonic()
-            if self.title:
-                self.add_step(self.title, duration=3.0)
             self._start_ffmpeg_capture()
+            await asyncio.sleep(_INTRO_STABILIZE_SECONDS)
+            if self.title:
+                await self._safe_add_step(self.title, duration=4.0)
+            intro_wait = _INTRO_BUFFER_SECONDS - _INTRO_STABILIZE_SECONDS
+            if intro_wait > 0:
+                await asyncio.sleep(intro_wait)
         return self
 
     async def __aexit__(self, exc_type, exc, tb) -> None:
         if self.enabled:
+            if self.closing_title:
+                await self._safe_add_step(self.closing_title, duration=4.0)
+            await asyncio.sleep(_OUTRO_BUFFER_SECONDS)
             self._stop_ffmpeg_capture()
             await self.finalize()
 
+    def _try_compose_variants(
+        self,
+        ffmpeg_exe: Path,
+        capture: Path,
+        srt_file: Path,
+        output: Path,
+        *,
+        music: Optional[Path],
+        voiceover: Optional[Path],
+        use_srt: bool,
+    ) -> tuple[bool, str]:
+        """按 music/voice 组合尝试合成，失败时逐级降级。"""
+        srt = srt_file if use_srt else Path(self._srt_path)
+        variants: List[tuple[Optional[Path], Optional[Path]]] = [
+            (music, voiceover),
+        ]
+        if music and voiceover:
+            variants.append((None, voiceover))
+        if music:
+            variants.append((music, None))
+        variants.append((None, None))
+
+        seen: set[tuple[Optional[str], Optional[str]]] = set()
+        last_err = ""
+        for m, v in variants:
+            key = (str(m) if m else None, str(v) if v else None)
+            if key in seen:
+                continue
+            seen.add(key)
+            ok, err = _compose_capture_mp4(
+                ffmpeg_exe,
+                capture,
+                srt,
+                output,
+                music_file=m,
+                voiceover_file=v,
+                warnings=self.warnings,
+            )
+            if ok:
+                return True, ""
+            last_err = err
+            if m is not None and v is not None:
+                self.warnings.append(f"ffmpeg_with_music_and_voice_failed: {err}")
+            elif m is not None:
+                self.warnings.append(f"ffmpeg_with_music_failed: {err}")
+
+        return False, last_err
+
     async def finalize(self) -> None:
         """停止录制后合成最终 MP4；失败只记 warning，不抛异常。"""
         if not self.enabled:
@@ -406,7 +820,12 @@ class RpaVideoSession:
                 self.warnings.append(f"subtitle_write_failed: {exc}")
 
             music = _resolve_music_file(self.warnings)
-            if music is None and "background_music_lfs_pointer_only" not in self.warnings and "background_music_invalid" not in self.warnings:
+            if music is not None:
+                self._music_path = str(music.resolve())
+            elif (
+                "background_music_lfs_pointer_only" not in self.warnings
+                and "background_music_invalid" not in self.warnings
+            ):
                 self.warnings.append("background_music_missing")
 
             ffmpeg_exe = _resolve_ffmpeg_exe()
@@ -415,25 +834,32 @@ class RpaVideoSession:
                 self.artifacts = self.summary()
                 return
 
+            voiceover: Optional[Path] = None
+            try:
+                vo = _synthesize_step_voiceover(
+                    entries,
+                    Path(self._voiceover_path),
+                    self.warnings,
+                    ffmpeg_exe=ffmpeg_exe,
+                )
+                if vo is not None:
+                    voiceover = vo
+                    self._voiceover_output = str(vo.resolve())
+            except Exception as exc:
+                self.warnings.append(f"tts_unexpected_error: {exc}")
+
             srt_file = Path(self._srt_path)
             use_srt = srt_file.is_file() and srt_file.stat().st_size > 0
 
-            ok, err = _compose_capture_mp4(
+            ok, err = self._try_compose_variants(
                 ffmpeg_exe,
                 capture,
-                srt_file if use_srt else Path(self._srt_path),
+                srt_file,
                 Path(self._planned_output),
-                music_file=music,
+                music=music,
+                voiceover=voiceover,
+                use_srt=use_srt,
             )
-            if not ok and music is not None:
-                self.warnings.append(f"ffmpeg_with_music_failed: {err}")
-                ok, err = _compose_capture_mp4(
-                    ffmpeg_exe,
-                    capture,
-                    srt_file if use_srt else Path(self._srt_path),
-                    Path(self._planned_output),
-                    music_file=None,
-                )
             if not ok and not use_srt:
                 ok, err = _run_ffmpeg(
                     ffmpeg_exe,
@@ -469,12 +895,28 @@ class RpaVideoSession:
             if self.enabled and self._ffmpeg_record_log_path
             else None
         )
+        audio_warnings = [
+            w
+            for w in self.warnings
+            if w.startswith(
+                (
+                    "tts_",
+                    "video_duration_probe_failed",
+                    "ffmpeg_with_music",
+                    "background_music_",
+                )
+            )
+            or w == "background_music_missing"
+        ]
         return {
             "enabled": self.enabled,
             "path": self.output_video_path,
             "capture_path": self.capture_path,
             "record_log_path": record_log,
             "warnings": list(self.warnings),
+            "voiceover_path": self._voiceover_output,
+            "music_path": self._music_path,
+            "audio_warnings": audio_warnings,
         }
 
     def to_artifact_dict(self) -> Dict[str, Any]:

src/jiangchang_skill_core/runtime_diagnostics.py

@@ -0,0 +1,339 @@
+"""共享 Runtime 诊断：health 输出与 media-assets / ffmpeg 探测。"""
+
+from __future__ import annotations
+
+import importlib.metadata
+import logging
+import os
+import sys
+from dataclasses import dataclass
+from pathlib import Path
+from typing import Any, Mapping
+
+import jiangchang_skill_core
+from .media_assets import probe_background_music, probe_media_assets, resolve_media_assets_root
+from .runtime_env import platform_default_data_root
+
+_SHARED_CORE_HINT = (
+    "jiangchang_skill_core is loaded from the skill tree; expected the shared "
+    "jiangchang-platform-kit installed in the host Python runtime."
+)
+
+
+@dataclass(frozen=True)
+class RuntimeIssue:
+    code: str
+    message: str
+    severity: str = "warning"
+
+
+@dataclass(frozen=True)
+class RuntimeDiagnostics:
+    skill_slug: str
+    python_executable: str
+    platform_kit_version: str | None
+    platform_kit_min_version: str | None
+    platform_kit_version_ok: bool | None
+    jiangchang_skill_core_file: str | None
+
+    claw_data_root: str | None
+    jiangchang_data_root: str | None
+    resolved_data_root: str | None
+
+    media_assets_root: str | None
+    ffmpeg_available: bool
+    ffmpeg_path: str | None
+
+    background_music_mp3_count: int
+    background_music_usable_count: int
+    background_music_issue: str | None
+    background_music_sample_path: str | None
+
+    record_video_enabled: bool
+    issues: tuple[RuntimeIssue, ...]
+
+    @property
+    def has_fatal_issues(self) -> bool:
+        return any(issue.severity == "error" for issue in self.issues)
+
+    def issue_codes(self) -> list[str]:
+        return [issue.code for issue in self.issues]
+
+
+def _env_dict(env: Mapping[str, str] | None) -> dict[str, str]:
+    return dict(env) if env is not None else dict(os.environ)
+
+
+def _resolve_data_root(env: Mapping[str, str]) -> str:
+    root = (env.get("CLAW_DATA_ROOT") or env.get("JIANGCHANG_DATA_ROOT") or "").strip()
+    if root:
+        return root
+    return platform_default_data_root()
+
+
+def _parse_version(version: str) -> tuple[int, int, int, int]:
+    """Parse major.minor.patch[.postN] into (major, minor, patch, post)."""
+    text = version.strip()
+    post = 0
+    if ".post" in text:
+        base, _, post_part = text.partition(".post")
+        post_digits = ""
+        for ch in post_part:
+            if ch.isdigit():
+                post_digits += ch
+            else:
+                break
+        post = int(post_digits) if post_digits else 0
+        text = base
+
+    parts: list[int] = []
+    for piece in text.split("."):
+        digits = ""
+        for ch in piece:
+            if ch.isdigit():
+                digits += ch
+            else:
+                break
+        if digits:
+            parts.append(int(digits))
+
+    while len(parts) < 3:
+        parts.append(0)
+
+    return parts[0], parts[1], parts[2], post
+
+
+def version_ge(installed: str, required: str) -> bool:
+    """Compare semver-like versions without external deps (supports legacy .postN)."""
+    return _parse_version(installed) >= _parse_version(required)
+
+
+def _path_under(parent: str | Path, child: str | Path) -> bool:
+    try:
+        parent_path = Path(parent).resolve()
+        child_path = Path(child).resolve()
+        if sys.platform == "win32":
+            parent_norm = os.path.normcase(str(parent_path))
+            child_norm = os.path.normcase(str(child_path))
+            common = os.path.commonpath([parent_norm, child_norm])
+            return common == parent_norm
+        return os.path.commonpath([str(parent_path), str(child_path)]) == str(parent_path)
+    except (OSError, ValueError):
+        return False
+
+
+def is_jiangchang_skill_core_from_skill_tree(
+    *,
+    skill_root: str | Path,
+    core_file: str | Path | None = None,
+) -> bool:
+    """Return True when jiangchang_skill_core is loaded from inside skill_root."""
+    try:
+        root = Path(skill_root)
+        if not str(root).strip():
+            return False
+        core = Path(core_file) if core_file is not None else Path(jiangchang_skill_core.__file__)
+        return _path_under(root, core)
+    except (OSError, TypeError, ValueError):
+        return False
+
+
+def _platform_kit_version() -> str | None:
+    try:
+        return importlib.metadata.version("jiangchang-platform-kit")
+    except importlib.metadata.PackageNotFoundError:
+        return None
+
+
+def _bool_from_env(env: Mapping[str, str], key: str, default: bool = False) -> bool:
+    val = env.get(key)
+    if val is None or val == "":
+        return default
+    return str(val).strip().lower() in ("1", "true", "yes", "on")
+
+
+def collect_runtime_diagnostics(
+    *,
+    skill_slug: str,
+    platform_kit_min_version: str | None = None,
+    skill_root: str | Path | None = None,
+    record_video: bool | None = None,
+    env: Mapping[str, str] | None = None,
+) -> RuntimeDiagnostics:
+    env_map = _env_dict(env)
+    issues: list[RuntimeIssue] = []
+
+    claw_data_root = env_map.get("CLAW_DATA_ROOT")
+    jiangchang_data_root = env_map.get("JIANGCHANG_DATA_ROOT")
+    resolved_data_root = _resolve_data_root(env_map)
+
+    media_root_path = resolve_media_assets_root(resolved_data_root, env_map)
+    media_status = probe_media_assets(resolved_data_root, env_map)
+    ffmpeg_path_obj = media_status.ffmpeg_path
+    ffmpeg_ok = ffmpeg_path_obj is not None and ffmpeg_path_obj.is_file()
+
+    music_probe = probe_background_music(media_root_path, env=env_map)
+    mp3_count = int(music_probe["mp3_count"])
+    usable_count = int(music_probe["usable_count"])
+    music_issue = music_probe.get("issue")
+    music_sample = music_probe.get("sample_path")
+
+    if music_issue is None and not media_status.music_ready and media_status.warnings:
+        for warning in media_status.warnings:
+            if warning.startswith("background_music") or warning == "music_dir_missing":
+                music_issue = warning
+                break
+
+    platform_version = _platform_kit_version()
+    platform_ok: bool | None
+    if platform_kit_min_version is None:
+        platform_ok = None
+    elif platform_version is None:
+        platform_ok = False
+    else:
+        platform_ok = version_ge(platform_version, platform_kit_min_version)
+
+    if platform_version is None:
+        issues.append(
+            RuntimeIssue(
+                code="platform_kit_not_installed",
+                message="jiangchang-platform-kit package metadata not found",
+                severity="error",
+            )
+        )
+    elif platform_kit_min_version is not None and not platform_ok:
+        issues.append(
+            RuntimeIssue(
+                code="platform_kit_version_low",
+                message=(
+                    f"jiangchang-platform-kit version {platform_version} "
+                    f"is below required {platform_kit_min_version}"
+                ),
+                severity="error",
+            )
+        )
+
+    core_file: str | None
+    try:
+        core_file = os.path.abspath(jiangchang_skill_core.__file__)
+    except (OSError, TypeError, ValueError):
+        core_file = None
+
+    if skill_root is not None and core_file is not None:
+        if is_jiangchang_skill_core_from_skill_tree(skill_root=skill_root, core_file=core_file):
+            issues.append(
+                RuntimeIssue(
+                    code="jiangchang_skill_core_loaded_from_skill_tree",
+                    message=_SHARED_CORE_HINT,
+                    severity="warning",
+                )
+            )
+
+    if record_video is None:
+        record_video_enabled = _bool_from_env(env_map, "OPENCLAW_RECORD_VIDEO", False)
+    else:
+        record_video_enabled = record_video
+
+    if not ffmpeg_ok:
+        severity = "warning"
+        message = "ffmpeg not available"
+        if record_video_enabled:
+            message = "OPENCLAW_RECORD_VIDEO enabled but ffmpeg is not available"
+        issues.append(
+            RuntimeIssue(
+                code="ffmpeg_unavailable",
+                message=message,
+                severity=severity,
+            )
+        )
+
+    if record_video_enabled and music_issue:
+        issues.append(
+            RuntimeIssue(
+                code="background_music_unavailable",
+                message=f"background music unavailable: {music_issue}",
+                severity="warning",
+            )
+        )
+
+    return RuntimeDiagnostics(
+        skill_slug=skill_slug,
+        python_executable=sys.executable,
+        platform_kit_version=platform_version,
+        platform_kit_min_version=platform_kit_min_version,
+        platform_kit_version_ok=platform_ok,
+        jiangchang_skill_core_file=core_file,
+        claw_data_root=claw_data_root,
+        jiangchang_data_root=jiangchang_data_root,
+        resolved_data_root=resolved_data_root,
+        media_assets_root=str(media_root_path),
+        ffmpeg_available=ffmpeg_ok,
+        ffmpeg_path=str(ffmpeg_path_obj) if ffmpeg_path_obj else None,
+        background_music_mp3_count=mp3_count,
+        background_music_usable_count=usable_count,
+        background_music_issue=str(music_issue) if music_issue else None,
+        background_music_sample_path=str(music_sample) if music_sample else None,
+        record_video_enabled=record_video_enabled,
+        issues=tuple(issues),
+    )
+
+
+def format_runtime_health_lines(diagnostics: RuntimeDiagnostics) -> list[str]:
+    lines = [
+        f"skill_slug: {diagnostics.skill_slug}",
+        f"python_executable: {diagnostics.python_executable}",
+        f"platform_kit_version: {diagnostics.platform_kit_version or ''}",
+        f"platform_kit_min_version: {diagnostics.platform_kit_min_version or ''}",
+        f"platform_kit_version_ok: {diagnostics.platform_kit_version_ok}",
+        f"jiangchang_skill_core_file: {diagnostics.jiangchang_skill_core_file or ''}",
+        f"CLAW_DATA_ROOT: {diagnostics.claw_data_root or ''}",
+        f"JIANGCHANG_DATA_ROOT: {diagnostics.jiangchang_data_root or ''}",
+        f"resolved_data_root: {diagnostics.resolved_data_root or ''}",
+        f"media_assets_root: {diagnostics.media_assets_root or ''}",
+        f"ffmpeg_available: {diagnostics.ffmpeg_available}",
+        f"ffmpeg_path: {diagnostics.ffmpeg_path or ''}",
+        f"background_music_mp3_count: {diagnostics.background_music_mp3_count}",
+        f"background_music_usable_count: {diagnostics.background_music_usable_count}",
+        f"background_music_issue: {diagnostics.background_music_issue or ''}",
+        f"background_music_sample_path: {diagnostics.background_music_sample_path or ''}",
+        f"record_video_enabled: {diagnostics.record_video_enabled}",
+    ]
+    for issue in diagnostics.issues:
+        lines.append(f"runtime_issue[{issue.severity}]: {issue.code} - {issue.message}")
+    return lines
+
+
+def runtime_diagnostics_dict(diagnostics: RuntimeDiagnostics) -> dict[str, Any]:
+    return {
+        "skill_slug": diagnostics.skill_slug,
+        "python_executable": diagnostics.python_executable,
+        "platform_kit_version": diagnostics.platform_kit_version,
+        "platform_kit_min_version": diagnostics.platform_kit_min_version,
+        "platform_kit_version_ok": diagnostics.platform_kit_version_ok,
+        "jiangchang_skill_core_file": diagnostics.jiangchang_skill_core_file,
+        "CLAW_DATA_ROOT": diagnostics.claw_data_root,
+        "JIANGCHANG_DATA_ROOT": diagnostics.jiangchang_data_root,
+        "resolved_data_root": diagnostics.resolved_data_root,
+        "media_assets_root": diagnostics.media_assets_root,
+        "ffmpeg_available": diagnostics.ffmpeg_available,
+        "ffmpeg_path": diagnostics.ffmpeg_path,
+        "background_music_mp3_count": diagnostics.background_music_mp3_count,
+        "background_music_usable_count": diagnostics.background_music_usable_count,
+        "background_music_issue": diagnostics.background_music_issue,
+        "background_music_sample_path": diagnostics.background_music_sample_path,
+        "record_video_enabled": diagnostics.record_video_enabled,
+        "runtime_issues": [
+            {"code": issue.code, "message": issue.message, "severity": issue.severity}
+            for issue in diagnostics.issues
+        ],
+    }
+
+
+def log_runtime_diagnostics(
+    diagnostics: RuntimeDiagnostics,
+    logger: logging.Logger | None = None,
+    level: int = logging.INFO,
+) -> None:
+    log = logger or logging.getLogger("jiangchang_skill_core.runtime_diagnostics")
+    for line in format_runtime_health_lines(diagnostics):
+        log.log(level, line)

tests/test_media_assets.py

@@ -15,7 +15,7 @@ from jiangchang_skill_core import media_assets as ma
 
 def _make_complete_assets(root: Path, *, with_ffmpeg: bool = True, with_ffprobe: bool = True) -> None:
     (root / "music" / "calm").mkdir(parents=True)
-    (root / "music" / "calm" / "track.mp3").write_bytes(b"x" * 256)
+    (root / "music" / "calm" / "track.mp3").write_bytes(b"x" * 1024)
     (root / "fonts").mkdir(parents=True)
     (root / "watermark").mkdir(parents=True)
     bin_key = ma._platform_bin_key()
@@ -58,6 +58,56 @@ def _install_tools_from_manifest(root: Path, warnings: list[str]) -> bool:
     return True
 
 
+def _build_archive_zip(dest: Path, inner_name: str) -> None:
+    manifest = _sample_manifest()
+    with zipfile.ZipFile(dest, "w") as zf:
+        zf.writestr(f"{inner_name}/README.md", "# media-assets\n")
+        zf.writestr(f"{inner_name}/manifest.json", json.dumps(manifest, ensure_ascii=False))
+        zf.writestr(f"{inner_name}/music/calm/track.mp3", b"x" * 1024)
+        zf.writestr(f"{inner_name}/fonts/.keep", "")
+        zf.writestr(f"{inner_name}/watermark/.keep", "")
+
+
+def test_default_bundle_url_is_release() -> None:
+    url = ma._media_assets_bundle_url()
+    assert url == ma.MEDIA_ASSETS_BUNDLE_URL
+    assert url.endswith("/releases/download/vlatest/media-assets.zip")
+    assert "/archive/main.zip" not in url
+
+
+def test_bundle_url_env_override() -> None:
+    override = "https://example.com/media-assets.zip"
+    assert ma._media_assets_bundle_url(env={"MEDIA_ASSETS_BUNDLE_URL": override}) == override
+
+
+def test_zip_download_uses_bundle_url_override(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
+    data_root = tmp_path / "data"
+    shared = data_root / "shared"
+    target = shared / "media-assets"
+    archive = tmp_path / "media-assets.zip"
+    override = "https://example.com/media-assets.zip"
+
+    _build_archive_zip(archive, "media-assets")
+    captured_urls: list[str] = []
+
+    def _fake_download(url: str, dest: Path) -> None:
+        captured_urls.append(url)
+        dest.write_bytes(archive.read_bytes())
+
+    monkeypatch.setattr(ma, "_download_zip", _fake_download)
+    monkeypatch.setattr(ma, "_find_git_executable", lambda: None)
+    monkeypatch.setattr(ma, "_try_download_ffmpeg_tools", _install_tools_from_manifest)
+
+    env = {
+        "JIANGCHANG_DATA_ROOT": str(data_root),
+        "MEDIA_ASSETS_BUNDLE_URL": override,
+    }
+    status = ma.ensure_media_assets(env=env)
+    assert captured_urls == [override]
+    assert target.is_dir()
+    assert status.ready is True
+
+
 def test_media_assets_root_env_priority(tmp_path: Path) -> None:
     custom = tmp_path / "custom-media"
     custom.mkdir()
@@ -118,9 +168,9 @@ def test_pick_background_music_stable_first(tmp_path: Path, monkeypatch: pytest.
     root = tmp_path / "data" / "shared" / "media-assets"
     _make_complete_assets(root)
     music = root / "music"
-    (music / "b-upbeat.mp3").write_bytes(b"x" * 256)
+    (music / "b-upbeat.mp3").write_bytes(b"x" * 1024)
-    (music / "calm" / "a-calm.mp3").write_bytes(b"x" * 256)
+    (music / "calm" / "a-calm.mp3").write_bytes(b"x" * 1024)
-    (music / "z-last.wav").write_bytes(b"x" * 256)
+    (music / "z-last.wav").write_bytes(b"x" * 1024)
 
     monkeypatch.setattr(
         ma,
@@ -132,23 +182,18 @@ def test_pick_background_music_stable_first(tmp_path: Path, monkeypatch: pytest.
     assert picked == music / "b-upbeat.mp3"
 
 
-def _build_archive_zip(dest: Path, inner_name: str) -> None:
+@pytest.mark.parametrize("inner_name", ["media-assets", "media-assets-main"])
-    manifest = _sample_manifest()
+def test_zip_wrapper_layout_detected(
-    with zipfile.ZipFile(dest, "w") as zf:
+    tmp_path: Path,
-        zf.writestr(f"{inner_name}/README.md", "# media-assets\n")
+    monkeypatch: pytest.MonkeyPatch,
-        zf.writestr(f"{inner_name}/manifest.json", json.dumps(manifest, ensure_ascii=False))
+    inner_name: str,
-        zf.writestr(f"{inner_name}/music/calm/track.mp3", b"x" * 256)
+) -> None:
-        zf.writestr(f"{inner_name}/fonts/.keep", "")
-        zf.writestr(f"{inner_name}/watermark/.keep", "")
-
-
-def test_zip_wrapper_layout_detected(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
     data_root = tmp_path / "data"
     shared = data_root / "shared"
     target = shared / "media-assets"
     archive = tmp_path / "media-assets.zip"
 
-    _build_archive_zip(archive, "media-assets-main")
+    _build_archive_zip(archive, inner_name)
 
     def _fake_download(url: str, dest: Path) -> None:
         dest.write_bytes(archive.read_bytes())
@@ -226,12 +271,33 @@ def test_probe_media_assets_does_not_download(tmp_path: Path, monkeypatch: pytes
     assert status.ffmpeg_path is None
 
 
+def test_lfs_pointer_warning_in_probe_and_ensure(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
+    root = tmp_path / "data" / "shared" / "media-assets"
+    _make_complete_assets(root)
+    music = root / "music"
+    (music / "calm" / "track.mp3").unlink()
+    (music / "lfs-only.mp3").write_text(
+        "version https://git-lfs.github.com/spec/v1\noid sha256:abc\nsize 123\n"
+    )
+
+    monkeypatch.setattr(ma, "_try_download_via_zip", lambda *a, **k: False)
+    monkeypatch.setattr(ma, "_try_download_via_git", lambda *a, **k: False)
+
+    probed = ma.probe_media_assets(env={"JIANGCHANG_DATA_ROOT": str(tmp_path / "data")})
+    assert "background_music_lfs_pointer_only" in probed.warnings
+    assert probed.music_ready is False
+
+    ensured = ma.ensure_media_assets(env={"JIANGCHANG_DATA_ROOT": str(tmp_path / "data")})
+    assert "background_music_lfs_pointer_only" in ensured.warnings
+    assert ensured.ready is False
+
+
 def test_pick_background_music_skips_lfs_pointer(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
     root = tmp_path / "data" / "shared" / "media-assets"
     _make_complete_assets(root, with_ffmpeg=True, with_ffprobe=True)
     music = root / "music"
     (music / "calm" / "track.mp3").unlink()
-    (music / "real.mp3").write_bytes(b"x" * 256)
+    (music / "real.mp3").write_bytes(b"x" * 1024)
     lfs = music / "lfs-only.mp3"
     lfs.write_text("version https://git-lfs.github.com/spec/v1\noid sha256:abc\nsize 123\n")
 
@@ -324,7 +390,7 @@ def test_video_finalize_without_music_fallback(tmp_path: Path, monkeypatch: pyte
 def test_manifest_ffmpeg_download(tmp_path: Path, monkeypatch: pytest.MonkeyPatch) -> None:
     root = tmp_path / "data" / "shared" / "media-assets"
     (root / "music" / "calm").mkdir(parents=True)
-    (root / "music" / "calm" / "track.mp3").write_bytes(b"x" * 256)
+    (root / "music" / "calm" / "track.mp3").write_bytes(b"x" * 1024)
     (root / "fonts").mkdir(parents=True)
     (root / "watermark").mkdir(parents=True)
     (root / "manifest.json").write_text(
@@ -340,3 +406,32 @@ def test_manifest_ffmpeg_download(tmp_path: Path, monkeypatch: pytest.MonkeyPatc
     assert status.ready is True
     assert status.ffmpeg_path is not None
     assert status.ffprobe_path is not None
+
+
+def test_is_usable_audio_file_rejects_small_and_lfs(tmp_path: Path) -> None:
+    small = tmp_path / "small.mp3"
+    small.write_bytes(b"x" * 512)
+    assert ma.is_usable_audio_file(small) is False
+
+    ok = tmp_path / "ok.mp3"
+    ok.write_bytes(b"x" * 1024)
+    assert ma.is_usable_audio_file(ok) is True
+
+    lfs = tmp_path / "lfs.mp3"
+    lfs.write_text("version https://git-lfs.github.com/spec/v1\noid sha256:abc\nsize 123\n")
+    assert ma.is_usable_audio_file(lfs) is False
+    assert ma.is_git_lfs_pointer(lfs) is True
+
+
+def test_probe_background_music_structure(tmp_path: Path) -> None:
+    root = tmp_path / "media-assets"
+    music = root / "music" / "calm"
+    music.mkdir(parents=True)
+    (music / "track.mp3").write_bytes(b"x" * 1024)
+
+    probe = ma.probe_background_music(root)
+    assert probe["music_root"] == str(root / "music")
+    assert probe["mp3_count"] == 1
+    assert probe["usable_count"] == 1
+    assert probe["issue"] is None
+    assert probe["sample_path"] == str(music / "track.mp3")

tests/test_release_workflow.py

@@ -1,4 +1,4 @@
-"""Text-level checks that reusable-release-skill packages .env.example at package root."""
+"""Text-level checks for release-related GitHub Actions workflows."""
 
 from __future__ import annotations
 
@@ -8,17 +8,52 @@ import re
 import pytest
 
 _REPO_ROOT = os.path.abspath(os.path.join(os.path.dirname(__file__), ".."))
-_WORKFLOW_PATH = os.path.join(
+_SKILL_WORKFLOW_PATH = os.path.join(
     _REPO_ROOT, ".github", "workflows", "reusable-release-skill.yaml"
 )
+_PUBLISH_WORKFLOW_PATH = os.path.join(
+    _REPO_ROOT, ".github", "workflows", "publish.yml"
+)
 
 
 @pytest.fixture(scope="module")
 def workflow_text() -> str:
-    with open(_WORKFLOW_PATH, encoding="utf-8") as f:
+    with open(_SKILL_WORKFLOW_PATH, encoding="utf-8") as f:
         return f.read()
 
 
+@pytest.fixture(scope="module")
+def publish_workflow_text() -> str:
+    with open(_PUBLISH_WORKFLOW_PATH, encoding="utf-8") as f:
+        return f.read()
+
+
+def test_workflow_packages_readme_at_root(workflow_text: str) -> None:
+    assert "readme_src = os.path.abspath('README.md')" in workflow_text
+    assert "readme_dst = os.path.join(PACKAGE, 'README.md')" in workflow_text
+    assert "Copied README.md" in workflow_text
+    assert (
+        "raise RuntimeError('README.md exists in skill root but was not packaged')"
+        in workflow_text
+    )
+
+
+def test_workflow_metadata_reads_root_readme(workflow_text: str) -> None:
+    assert "readme_path = 'README.md'" in workflow_text
+    assert "frontmatter.load(readme_path)" in workflow_text
+    assert "metadata['readme_md'] = body" in workflow_text
+
+
+def test_workflow_does_not_use_references_readme_for_marketplace(
+    workflow_text: str,
+) -> None:
+    assert "os.path.join('references', 'README.md')" not in workflow_text
+    assert not re.search(
+        r"frontmatter\.load\([^)]*references[^)]*README",
+        workflow_text,
+    )
+
+
 def test_workflow_packages_env_example_at_root(workflow_text: str) -> None:
     assert ".env.example" in workflow_text
     assert "Copied .env.example" in workflow_text
@@ -40,3 +75,18 @@ def test_workflow_does_not_package_dot_env(workflow_text: str) -> None:
         r"os\.path\.join\(PACKAGE,\s*['\"]\.env['\"]\)",
         workflow_text,
     )
+
+
+def test_publish_workflow_triggers_on_main_only(publish_workflow_text: str) -> None:
+    assert "branches:" in publish_workflow_text
+    assert "- main" in publish_workflow_text
+    assert "tags:" not in publish_workflow_text
+
+
+def test_publish_workflow_uses_pyproject_version_only(publish_workflow_text: str) -> None:
+    assert "ci_set_package_version" not in publish_workflow_text
+    assert "GITHUB_RUN_NUMBER" not in publish_workflow_text
+    assert "GITHUB_RUN_ID" not in publish_workflow_text
+    assert ".post" not in publish_workflow_text
+    assert "python3.12 -m build" in publish_workflow_text
+    assert "twine upload" in publish_workflow_text

tests/test_runtime_diagnostics.py

@@ -0,0 +1,347 @@
+# -*- coding: utf-8 -*-
+"""runtime_diagnostics 公共 Runtime / media-assets 诊断测试。"""
+from __future__ import annotations
+
+import json
+from pathlib import Path
+from unittest.mock import patch
+
+import pytest
+
+import jiangchang_skill_core
+from jiangchang_skill_core import media_assets as ma
+from jiangchang_skill_core.runtime_diagnostics import (
+    RuntimeDiagnostics,
+    RuntimeIssue,
+    collect_runtime_diagnostics,
+    format_runtime_health_lines,
+    is_jiangchang_skill_core_from_skill_tree,
+    runtime_diagnostics_dict,
+    version_ge,
+)
+
+
+def test_version_ge_post_release() -> None:
+    assert version_ge("1.0.10.post23", "1.0.10") is True
+    assert version_ge("1.0.10", "1.0.10") is True
+    assert version_ge("1.0.9.post19", "1.0.10") is False
+    assert version_ge("1.0.10.post23", "1.0.10.post21") is True
+    assert version_ge("1.0.10.post21", "1.0.10.post23") is False
+    assert version_ge("1.0.10", "1.0.10.post1") is False
+    assert version_ge("1.0.11", "1.0.10.post99") is True
+    assert version_ge("1.0.11", "1.0.10") is True
+
+
+def test_is_jiangchang_skill_core_from_skill_tree(tmp_path: Path) -> None:
+    skill_root = tmp_path / "my-skill"
+    inside = skill_root / "scripts" / "jiangchang_skill_core" / "__init__.py"
+    inside.parent.mkdir(parents=True)
+    inside.write_text("# vendored\n", encoding="utf-8")
+    outside = tmp_path / "site-packages" / "jiangchang_skill_core" / "__init__.py"
+    outside.parent.mkdir(parents=True)
+    outside.write_text("# shared\n", encoding="utf-8")
+
+    assert is_jiangchang_skill_core_from_skill_tree(
+        skill_root=skill_root,
+        core_file=inside,
+    ) is True
+    assert is_jiangchang_skill_core_from_skill_tree(
+        skill_root=skill_root,
+        core_file=outside,
+    ) is False
+
+
+def test_collect_runtime_diagnostics_json_serializable(
+    tmp_path: Path,
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    data_root = tmp_path / "data"
+    env = {
+        "CLAW_DATA_ROOT": str(data_root),
+        "OPENCLAW_RECORD_VIDEO": "0",
+    }
+    media_root = data_root / "shared" / "media-assets"
+    (media_root / "music").mkdir(parents=True)
+
+    def _fake_probe_media_assets(data_root_arg=None, env_arg=None):
+        return ma.MediaAssetsStatus(
+            root=media_root,
+            exists=True,
+            ready=False,
+            source="local",
+            warnings=["ffmpeg_missing"],
+            ffmpeg_path=None,
+            music_dir=media_root / "music",
+            music_ready=False,
+        )
+
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
+        _fake_probe_media_assets,
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_background_music",
+        lambda *a, **k: {
+            "music_root": str(media_root / "music"),
+            "mp3_count": 0,
+            "usable_count": 0,
+            "sample_path": None,
+            "issue": "background_music_dir_empty",
+        },
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
+        lambda: "1.0.10",
+    )
+
+    diag = collect_runtime_diagnostics(
+        skill_slug="my-skill",
+        platform_kit_min_version="1.0.9",
+        env=env,
+    )
+    payload = runtime_diagnostics_dict(diag)
+    json.dumps(payload)
+    assert payload["skill_slug"] == "my-skill"
+    assert payload["resolved_data_root"] == str(data_root)
+    assert payload["platform_kit_version_ok"] is True
+
+
+def test_platform_kit_min_version_none_skips_version_issue(
+    tmp_path: Path,
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    env = {"CLAW_DATA_ROOT": str(tmp_path / "data")}
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
+        lambda *a, **k: ma.MediaAssetsStatus(
+            root=tmp_path,
+            exists=False,
+            ready=False,
+            source="local",
+        ),
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_background_music",
+        lambda *a, **k: {
+            "music_root": None,
+            "mp3_count": 0,
+            "usable_count": 0,
+            "sample_path": None,
+            "issue": "music_dir_missing",
+        },
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
+        lambda: "1.0.8",
+    )
+
+    diag = collect_runtime_diagnostics(skill_slug="my-skill", env=env)
+    assert diag.platform_kit_version_ok is None
+    assert "platform_kit_version_low" not in diag.issue_codes()
+
+
+def test_platform_kit_missing_records_issue(
+    tmp_path: Path,
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    env = {"CLAW_DATA_ROOT": str(tmp_path / "data")}
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
+        lambda *a, **k: ma.MediaAssetsStatus(
+            root=tmp_path,
+            exists=False,
+            ready=False,
+            source="local",
+        ),
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_background_music",
+        lambda *a, **k: {
+            "music_root": None,
+            "mp3_count": 0,
+            "usable_count": 0,
+            "sample_path": None,
+            "issue": None,
+        },
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
+        lambda: None,
+    )
+
+    diag = collect_runtime_diagnostics(
+        skill_slug="my-skill",
+        platform_kit_min_version="1.0.10",
+        env=env,
+    )
+    assert "platform_kit_not_installed" in diag.issue_codes()
+
+
+def test_record_video_ffmpeg_and_music_warnings_not_fatal(
+    tmp_path: Path,
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    media_root = tmp_path / "shared" / "media-assets"
+    env = {"CLAW_DATA_ROOT": str(tmp_path), "OPENCLAW_RECORD_VIDEO": "1"}
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
+        lambda *a, **k: ma.MediaAssetsStatus(
+            root=media_root,
+            exists=True,
+            ready=False,
+            source="local",
+            warnings=["ffmpeg_missing", "music_dir_missing"],
+            ffmpeg_path=None,
+            music_dir=None,
+        ),
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_background_music",
+        lambda *a, **k: {
+            "music_root": None,
+            "mp3_count": 0,
+            "usable_count": 0,
+            "sample_path": None,
+            "issue": "music_dir_missing",
+        },
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
+        lambda: "1.0.10",
+    )
+
+    diag = collect_runtime_diagnostics(skill_slug="my-skill", env=env)
+    codes = diag.issue_codes()
+    assert "ffmpeg_unavailable" in codes
+    assert "background_music_unavailable" in codes
+    assert diag.has_fatal_issues is False
+    ffmpeg_issue = next(i for i in diag.issues if i.code == "ffmpeg_unavailable")
+    assert ffmpeg_issue.severity == "warning"
+
+
+def test_skill_tree_core_issue_when_skill_root_given(tmp_path: Path) -> None:
+    skill_root = tmp_path / "my-skill"
+    fake_core = skill_root / "scripts" / "jiangchang_skill_core" / "__init__.py"
+    fake_core.parent.mkdir(parents=True)
+    fake_core.write_text("# vendored\n", encoding="utf-8")
+
+    env = {"CLAW_DATA_ROOT": str(tmp_path / "data")}
+    with patch.object(jiangchang_skill_core, "__file__", str(fake_core)):
+        diag = collect_runtime_diagnostics(
+            skill_slug="my-skill",
+            skill_root=skill_root,
+            record_video=False,
+            env=env,
+        )
+    assert "jiangchang_skill_core_loaded_from_skill_tree" in diag.issue_codes()
+
+
+def test_format_runtime_health_lines_core_fields(
+    tmp_path: Path,
+    monkeypatch: pytest.MonkeyPatch,
+) -> None:
+    env = {"CLAW_DATA_ROOT": str(tmp_path / "data")}
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_media_assets",
+        lambda *a, **k: ma.MediaAssetsStatus(
+            root=tmp_path,
+            exists=False,
+            ready=False,
+            source="local",
+        ),
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics.probe_background_music",
+        lambda *a, **k: {
+            "music_root": None,
+            "mp3_count": 0,
+            "usable_count": 0,
+            "sample_path": None,
+            "issue": None,
+        },
+    )
+    monkeypatch.setattr(
+        "jiangchang_skill_core.runtime_diagnostics._platform_kit_version",
+        lambda: "1.0.10",
+    )
+
+    diag = collect_runtime_diagnostics(skill_slug="my-skill", env=env)
+    text = "\n".join(format_runtime_health_lines(diag))
+    for marker in (
+        "python_executable:",
+        "platform_kit_version:",
+        "resolved_data_root:",
+        "media_assets_root:",
+        "ffmpeg_available:",
+        "background_music_mp3_count:",
+    ):
+        assert marker in text
+
+
+def test_background_music_lfs_and_size_rules(tmp_path: Path) -> None:
+    music = tmp_path / "music"
+    music.mkdir()
+    (music / "tiny.mp3").write_bytes(b"x" * 512)
+    (music / "lfs.mp3").write_text(
+        "version https://git-lfs.github.com/spec/v1\noid sha256:abc\nsize 123\n"
+    )
+    (music / "ok.mp3").write_bytes(b"x" * 1024)
+
+    probe = ma.probe_background_music(tmp_path)
+    assert probe["mp3_count"] == 3
+    assert probe["usable_count"] == 1
+    assert probe["sample_path"] == str(music / "ok.mp3")
+
+
+def test_runtime_diagnostics_frozen_dataclass() -> None:
+    diag = RuntimeDiagnostics(
+        skill_slug="x",
+        python_executable="python",
+        platform_kit_version="1.0.10",
+        platform_kit_min_version=None,
+        platform_kit_version_ok=None,
+        jiangchang_skill_core_file=None,
+        claw_data_root=None,
+        jiangchang_data_root=None,
+        resolved_data_root="/tmp",
+        media_assets_root="/tmp/media",
+        ffmpeg_available=False,
+        ffmpeg_path=None,
+        background_music_mp3_count=0,
+        background_music_usable_count=0,
+        background_music_issue=None,
+        background_music_sample_path=None,
+        record_video_enabled=False,
+        issues=(RuntimeIssue(code="ffmpeg_unavailable", message="no ffmpeg"),),
+    )
+    assert diag.has_fatal_issues is False
+    assert diag.issue_codes() == ["ffmpeg_unavailable"]
+
+
+def test_format_runtime_health_lines_issue_separator_ascii() -> None:
+    diag = RuntimeDiagnostics(
+        skill_slug="x",
+        python_executable="python",
+        platform_kit_version="1.0.11",
+        platform_kit_min_version=None,
+        platform_kit_version_ok=None,
+        jiangchang_skill_core_file=None,
+        claw_data_root=None,
+        jiangchang_data_root=None,
+        resolved_data_root="/tmp",
+        media_assets_root="/tmp/media",
+        ffmpeg_available=False,
+        ffmpeg_path=None,
+        background_music_mp3_count=0,
+        background_music_usable_count=0,
+        background_music_issue=None,
+        background_music_sample_path=None,
+        record_video_enabled=False,
+        issues=(RuntimeIssue(code="ffmpeg_unavailable", message="no ffmpeg"),),
+    )
+    lines = format_runtime_health_lines(diag)
+    issue_lines = [line for line in lines if line.startswith("runtime_issue[")]
+    assert len(issue_lines) == 1
+    assert " - " in issue_lines[0]
+    assert "\u2014" not in issue_lines[0]
+    assert "\u2013" not in issue_lines[0]

tests/test_video_session.py

@@ -1,5 +1,5 @@
 # -*- coding: utf-8 -*-
-"""RpaVideoSession：ffmpeg 桌面录屏。"""
+"""RpaVideoSession：ffmpeg 桌面录屏、背景音乐循环淡出、旁白混音。"""
 from __future__ import annotations
 
 import asyncio
@@ -8,9 +8,21 @@ import sys
 import tempfile
 import unittest
 from pathlib import Path
-from unittest.mock import MagicMock, patch
+from unittest.mock import AsyncMock, MagicMock, patch
+
 from jiangchang_skill_core import config
-from jiangchang_skill_core.rpa.video_session import RpaVideoSession
+from jiangchang_skill_core.rpa import video_session as vs
+from jiangchang_skill_core.rpa.video_session import (
+    RpaVideoSession,
+    _StepEntry,
+    _INTRO_BUFFER_SECONDS,
+    _INTRO_STABILIZE_SECONDS,
+    _OUTRO_BUFFER_SECONDS,
+    _compose_capture_mp4,
+    _music_fade_params,
+    _select_voiceover_clips,
+    _voiceover_text_for_step,
+)
 
 
 class TestRpaVideoSession(unittest.TestCase):
@@ -33,6 +45,8 @@ class TestRpaVideoSession(unittest.TestCase):
                 self.assertIsNone(summ["path"])
                 self.assertIsNone(summ["capture_path"])
                 self.assertIsNone(summ["record_log_path"])
+                self.assertIsNone(summ["voiceover_path"])
+                self.assertIsNone(summ["music_path"])
         finally:
             if old is not None:
                 os.environ["OPENCLAW_RECORD_VIDEO"] = old
@@ -60,6 +74,11 @@ class TestRpaVideoSession(unittest.TestCase):
                         "/rpa-artifacts/exmail_20260602_120000/logs/ffmpeg-record.log"
                     )
                 )
+                self.assertTrue(
+                    session._voiceover_path.replace("\\", "/").endswith(
+                        "/rpa-artifacts/exmail_20260602_120000/voiceover/voiceover.wav"
+                    )
+                )
                 self.assertTrue(
                     session._planned_output.replace("\\", "/").startswith(
                         tmp.replace("\\", "/") + "/videos/"
@@ -144,5 +163,413 @@ class TestRpaVideoSession(unittest.TestCase):
             config.reset_cache()
 
 
+class TestMusicFadeParams(unittest.TestCase):
+    def test_normal_duration(self) -> None:
+        start, dur = _music_fade_params(20.0)
+        self.assertAlmostEqual(start, 17.0)
+        self.assertAlmostEqual(dur, 3.0)
+
+    def test_short_video(self) -> None:
+        start, dur = _music_fade_params(4.0)
+        self.assertAlmostEqual(dur, 1.0)
+        self.assertAlmostEqual(start, 3.0)
+
+    def test_invalid_duration(self) -> None:
+        self.assertEqual(_music_fade_params(None), (None, None))
+        self.assertEqual(_music_fade_params(0), (None, None))
+        self.assertEqual(_music_fade_params(-1), (None, None))
+
+
+class TestVoiceoverTextFilter(unittest.TestCase):
+    def test_keeps_meaningful_steps(self) -> None:
+        for text in (
+            "开始采集",
+            "获取1688账号",
+            "启动浏览器",
+            "检查登录状态",
+            "搜索关键词：螺丝",
+            "解析第 1 页店铺列表",
+            "打开店铺联系方式页",
+            "提取联系人信息",
+            "采集完成",
+        ):
+            self.assertIsNotNone(_voiceover_text_for_step(text), msg=text)
+
+    def test_skips_noise(self) -> None:
+        for text in (
+            "等待 1-5s",
+            "跳过重复店铺",
+            "写入联系人库",
+            "探针模式",
+            "操作异常",
+            "登录失败",
+            "2024-01-01 12:00:00 INFO: debug",
+            "",
+            "   ",
+        ):
+            self.assertIsNone(_voiceover_text_for_step(text), msg=text)
+
+    def test_truncates_long_text(self) -> None:
+        long_text = "开" * 80
+        result = _voiceover_text_for_step(long_text)
+        self.assertIsNotNone(result)
+        assert result is not None
+        self.assertEqual(len(result), 60)
+
+    def test_dedup_within_ten_seconds(self) -> None:
+        entries = [
+            _StepEntry(0.0, "启动浏览器"),
+            _StepEntry(5.0, "启动浏览器"),
+            _StepEntry(12.0, "启动浏览器"),
+        ]
+        clips = _select_voiceover_clips(entries)
+        texts = [t for _, t in clips]
+        self.assertEqual(texts.count("启动浏览器"), 2)
+
+    def test_min_gap_two_seconds(self) -> None:
+        entries = [
+            _StepEntry(0.0, "获取1688账号"),
+            _StepEntry(1.0, "连接CDP"),
+            _StepEntry(3.0, "检查登录状态"),
+        ]
+        clips = _select_voiceover_clips(entries)
+        self.assertEqual(len(clips), 2)
+        self.assertEqual(clips[0][1], "获取1688账号")
+        self.assertEqual(clips[1][1], "检查登录状态")
+
+    def test_important_bypasses_min_gap(self) -> None:
+        entries = [
+            _StepEntry(0.0, "定位搜索框"),
+            _StepEntry(0.5, "输入关键词：宁德电池"),
+            _StepEntry(1.0, "点击搜索"),
+            _StepEntry(1.5, "等待搜索结果"),
+        ]
+        clips = _select_voiceover_clips(entries)
+        texts = [t for _, t in clips]
+        self.assertEqual(len(clips), 4)
+        self.assertIn("输入关键词：宁德电池", texts)
+        self.assertIn("点击搜索", texts)
+
+    def test_noise_still_skipped_with_important_nearby(self) -> None:
+        entries = [
+            _StepEntry(0.0, "点击搜索"),
+            _StepEntry(0.5, "跳过重复店铺"),
+            _StepEntry(1.0, "写入联系人库"),
+        ]
+        clips = _select_voiceover_clips(entries)
+        texts = [t for _, t in clips]
+        self.assertEqual(texts, ["点击搜索"])
+
+
+class TestComposeCaptureMp4(unittest.TestCase):
+    def setUp(self) -> None:
+        self.ffmpeg = Path(r"C:\ffmpeg\ffmpeg.exe")
+        self.capture = Path(r"C:\tmp\capture.mp4")
+        self.srt = Path(r"C:\tmp\sub.srt")
+        self.output = Path(r"C:\tmp\out.mp4")
+        self.music = Path(r"C:\tmp\music.mp3")
+        self.voice = Path(r"C:\tmp\voiceover.wav")
+
+    def _run_compose(self, **kwargs) -> list[str]:
+        captured: list[str] = []
+
+        def fake_run(_exe: Path, cmd_tail: list[str]) -> tuple[bool, str]:
+            captured.extend(cmd_tail)
+            return True, ""
+
+        with (
+            patch.object(vs, "_run_ffmpeg", side_effect=fake_run),
+            patch.object(vs, "_resolve_ffprobe_exe", return_value=Path(r"C:\ffmpeg\ffprobe.exe")),
+            patch.object(vs, "_probe_media_duration_seconds", return_value=kwargs.pop("duration", 20.0)),
+            patch.object(Path, "is_file", return_value=True),
+        ):
+            _compose_capture_mp4(
+                self.ffmpeg,
+                self.capture,
+                self.srt,
+                self.output,
+                music_file=kwargs.get("music_file"),
+                voiceover_file=kwargs.get("voiceover_file"),
+                warnings=kwargs.get("warnings"),
+            )
+        return captured
+
+    def test_music_loop_params(self) -> None:
+        cmd = self._run_compose(music_file=self.music)
+        cmd_str = " ".join(cmd)
+        loop_idx = cmd.index("-stream_loop")
+        minus_one_idx = cmd.index("-1", loop_idx)
+        music_i_idx = cmd.index("-i", minus_one_idx)
+        self.assertEqual(cmd[music_i_idx + 1], str(self.music))
+        self.assertIn("-shortest", cmd)
+        filter_idx = cmd.index("-filter_complex")
+        filt = cmd[filter_idx + 1]
+        self.assertNotIn("apad", filt)
+
+    def test_music_fade_filter_long_video(self) -> None:
+        cmd = self._run_compose(music_file=self.music, duration=20.0)
+        filt = cmd[cmd.index("-filter_complex") + 1]
+        self.assertIn("afade=t=out:st=17", filt)
+        self.assertIn("d=3", filt)
+        self.assertIn(f"volume={vs._MUSIC_VOLUME}", filt)
+
+    def test_music_fade_filter_short_video(self) -> None:
+        cmd = self._run_compose(music_file=self.music, duration=4.0)
+        filt = cmd[cmd.index("-filter_complex") + 1]
+        self.assertIn("afade=t=out:st=3", filt)
+        self.assertIn("d=1", filt)
+
+    def test_duration_probe_failed_no_afade(self) -> None:
+        warnings: list[str] = []
+        captured: list[str] = []
+
+        def fake_run(_exe: Path, cmd_tail: list[str]) -> tuple[bool, str]:
+            captured.extend(cmd_tail)
+            return True, ""
+
+        with (
+            patch.object(vs, "_run_ffmpeg", side_effect=fake_run),
+            patch.object(vs, "_resolve_ffprobe_exe", return_value=None),
+            patch.object(vs, "_probe_media_duration_seconds", return_value=None),
+            patch.object(Path, "is_file", return_value=True),
+        ):
+            ok, _ = _compose_capture_mp4(
+                self.ffmpeg,
+                self.capture,
+                self.srt,
+                self.output,
+                music_file=self.music,
+                warnings=warnings,
+            )
+        self.assertTrue(ok)
+        self.assertIn("video_duration_probe_failed_for_music_fade", warnings)
+        filt = captured[captured.index("-filter_complex") + 1]
+        self.assertNotIn("afade", filt)
+        self.assertIn("-stream_loop", captured)
+
+    def test_music_and_voice_amix(self) -> None:
+        cmd = self._run_compose(music_file=self.music, voiceover_file=self.voice)
+        filt = cmd[cmd.index("-filter_complex") + 1]
+        self.assertIn("amix", filt)
+        self.assertIn(f"volume={vs._MUSIC_VOLUME}", filt)
+        self.assertIn(f"volume={vs._VOICE_VOLUME}", filt)
+        self.assertLess(vs._MUSIC_VOLUME, vs._VOICE_VOLUME)
+        self.assertIn("afade", filt)
+        self.assertNotIn("apad", filt)
+        self.assertIn("-stream_loop", cmd)
+        self.assertIn("-shortest", cmd)
+
+    def test_voice_only_no_amix(self) -> None:
+        cmd = self._run_compose(voiceover_file=self.voice)
+        filt = cmd[cmd.index("-filter_complex") + 1]
+        self.assertNotIn("amix", filt)
+        self.assertIn(f"volume={vs._VOICE_VOLUME}", filt)
+        self.assertIn("apad", filt)
+        self.assertIn("-shortest", cmd)
+        self.assertNotIn("-stream_loop", cmd)
+
+
+class TestVideoSessionLifecycle(unittest.TestCase):
+    def setUp(self) -> None:
+        config.reset_cache()
+
+    def tearDown(self) -> None:
+        os.environ.pop("OPENCLAW_RECORD_VIDEO", None)
+        config.reset_cache()
+
+    @patch("jiangchang_skill_core.rpa.video_session.asyncio.sleep", new_callable=AsyncMock)
+    @patch.object(RpaVideoSession, "_start_ffmpeg_capture")
+    @patch.object(RpaVideoSession, "_stop_ffmpeg_capture")
+    @patch.object(RpaVideoSession, "finalize", new_callable=AsyncMock)
+    def test_enter_starts_capture_before_title(
+        self,
+        mock_finalize: AsyncMock,
+        mock_stop: MagicMock,
+        mock_start: MagicMock,
+        mock_sleep: AsyncMock,
+    ) -> None:
+        os.environ["OPENCLAW_RECORD_VIDEO"] = "1"
+        call_order: list[str] = []
+        mock_start.side_effect = lambda: call_order.append("start_capture")
+
+        with tempfile.TemporaryDirectory() as tmp:
+            config.reset_cache()
+            session = RpaVideoSession(
+                skill_slug="test",
+                skill_data_dir=tmp,
+                batch_id="batch_intro",
+                title="开始执行测试",
+            )
+            original_add = session.add_step
+
+            def _track_add(text: str, *, duration: float = 4.0) -> None:
+                call_order.append(f"add_step:{text}")
+                original_add(text, duration=duration)
+
+            with patch.object(session, "add_step", side_effect=_track_add):
+                asyncio.run(session.__aenter__())
+
+        self.assertEqual(call_order[0], "start_capture")
+        self.assertIn("add_step:开始执行测试", call_order)
+        mock_sleep.assert_awaited()
+        total_sleep = sum(c.args[0] for c in mock_sleep.await_args_list if c.args)
+        self.assertAlmostEqual(total_sleep, _INTRO_BUFFER_SECONDS)
+
+    @patch("jiangchang_skill_core.rpa.video_session.asyncio.sleep", new_callable=AsyncMock)
+    @patch.object(RpaVideoSession, "_start_ffmpeg_capture")
+    def test_enter_no_title_still_buffers(
+        self,
+        mock_start: MagicMock,
+        mock_sleep: AsyncMock,
+    ) -> None:
+        os.environ["OPENCLAW_RECORD_VIDEO"] = "1"
+        with tempfile.TemporaryDirectory() as tmp:
+            config.reset_cache()
+            session = RpaVideoSession(
+                skill_slug="test",
+                skill_data_dir=tmp,
+                batch_id="batch_no_title",
+            )
+            with patch.object(session, "add_step") as mock_add:
+                asyncio.run(session.__aenter__())
+            mock_start.assert_called_once()
+            mock_add.assert_not_called()
+            total_sleep = sum(c.args[0] for c in mock_sleep.await_args_list if c.args)
+            self.assertAlmostEqual(total_sleep, _INTRO_BUFFER_SECONDS)
+
+    @patch("jiangchang_skill_core.rpa.video_session.asyncio.sleep", new_callable=AsyncMock)
+    @patch.object(RpaVideoSession, "_stop_ffmpeg_capture")
+    @patch.object(RpaVideoSession, "finalize", new_callable=AsyncMock)
+    def test_exit_closing_title_before_stop(
+        self,
+        mock_finalize: AsyncMock,
+        mock_stop: MagicMock,
+        mock_sleep: AsyncMock,
+    ) -> None:
+        os.environ["OPENCLAW_RECORD_VIDEO"] = "1"
+        call_order: list[str] = []
+        mock_stop.side_effect = lambda: call_order.append("stop_capture")
+
+        with tempfile.TemporaryDirectory() as tmp:
+            config.reset_cache()
+            session = RpaVideoSession(
+                skill_slug="test",
+                skill_data_dir=tmp,
+                batch_id="batch_outro",
+                closing_title="任务已完成",
+            )
+            original_add = session.add_step
+
+            def _track_add(text: str, *, duration: float = 4.0) -> None:
+                call_order.append(f"add_step:{text}")
+                original_add(text, duration=duration)
+
+            with patch.object(session, "add_step", side_effect=_track_add):
+                asyncio.run(session.__aexit__(None, None, None))
+
+        self.assertIn("add_step:任务已完成", call_order)
+        self.assertEqual(call_order[-1], "stop_capture")
+        total_sleep = sum(c.args[0] for c in mock_sleep.await_args_list if c.args)
+        self.assertAlmostEqual(total_sleep, _OUTRO_BUFFER_SECONDS)
+
+    @patch("jiangchang_skill_core.rpa.video_session.asyncio.sleep", new_callable=AsyncMock)
+    @patch.object(RpaVideoSession, "_stop_ffmpeg_capture")
+    @patch.object(RpaVideoSession, "finalize", new_callable=AsyncMock)
+    def test_exit_no_closing_title_still_outro_buffer(
+        self,
+        mock_finalize: AsyncMock,
+        mock_stop: MagicMock,
+        mock_sleep: AsyncMock,
+    ) -> None:
+        os.environ["OPENCLAW_RECORD_VIDEO"] = "1"
+        with tempfile.TemporaryDirectory() as tmp:
+            config.reset_cache()
+            session = RpaVideoSession(
+                skill_slug="test",
+                skill_data_dir=tmp,
+                batch_id="batch_outro_empty",
+            )
+            with patch.object(session, "add_step") as mock_add:
+                asyncio.run(session.__aexit__(None, None, None))
+            mock_add.assert_not_called()
+            mock_stop.assert_called_once()
+            total_sleep = sum(c.args[0] for c in mock_sleep.await_args_list if c.args)
+            self.assertAlmostEqual(total_sleep, _OUTRO_BUFFER_SECONDS)
+
+
+class TestFinalizeDegradation(unittest.TestCase):
+    def setUp(self) -> None:
+        config.reset_cache()
+
+    def tearDown(self) -> None:
+        os.environ.pop("OPENCLAW_RECORD_VIDEO", None)
+        config.reset_cache()
+
+    @patch("jiangchang_skill_core.rpa.video_session._resolve_ffmpeg_exe")
+    @patch("jiangchang_skill_core.rpa.video_session._resolve_music_file")
+    @patch("jiangchang_skill_core.rpa.video_session._synthesize_step_voiceover")
+    @patch("jiangchang_skill_core.rpa.video_session._compose_capture_mp4")
+    def test_tts_failure_still_composes(
+        self,
+        mock_compose: MagicMock,
+        mock_tts: MagicMock,
+        mock_music: MagicMock,
+        mock_ffmpeg: MagicMock,
+    ) -> None:
+        os.environ["OPENCLAW_RECORD_VIDEO"] = "1"
+        mock_ffmpeg.return_value = Path(r"C:\ffmpeg\ffmpeg.exe")
+        mock_music.return_value = Path(r"C:\tmp\music.mp3")
+        mock_tts.return_value = None
+        mock_compose.return_value = (True, "")
+
+        with tempfile.TemporaryDirectory() as tmp:
+            capture = Path(tmp) / "rpa-artifacts" / "batch" / "capture.mp4"
+            capture.parent.mkdir(parents=True)
+            capture.write_bytes(b"fake")
+
+            session = RpaVideoSession(
+                skill_slug="test",
+                skill_data_dir=tmp,
+                batch_id="batch",
+            )
+            session.add_step("启动浏览器")
+            asyncio.run(session.finalize())
+
+        self.assertTrue(mock_compose.called)
+        self.assertIsNotNone(session.output_video_path)
+
+    @patch("jiangchang_skill_core.rpa.video_session._resolve_ffmpeg_exe")
+    @patch("jiangchang_skill_core.rpa.video_session._resolve_music_file")
+    @patch("jiangchang_skill_core.rpa.video_session._synthesize_step_voiceover")
+    @patch("jiangchang_skill_core.rpa.video_session._compose_capture_mp4")
+    def test_compose_fallback_without_music(
+        self,
+        mock_compose: MagicMock,
+        mock_tts: MagicMock,
+        mock_music: MagicMock,
+        mock_ffmpeg: MagicMock,
+    ) -> None:
+        os.environ["OPENCLAW_RECORD_VIDEO"] = "1"
+        mock_ffmpeg.return_value = Path(r"C:\ffmpeg\ffmpeg.exe")
+        mock_music.return_value = Path(r"C:\tmp\music.mp3")
+        mock_tts.return_value = None
+        mock_compose.side_effect = [(False, "music err"), (True, "")]
+
+        with tempfile.TemporaryDirectory() as tmp:
+            capture = Path(tmp) / "rpa-artifacts" / "batch" / "capture.mp4"
+            capture.parent.mkdir(parents=True)
+            capture.write_bytes(b"fake")
+
+            session = RpaVideoSession(
+                skill_slug="test",
+                skill_data_dir=tmp,
+                batch_id="batch",
+            )
+            asyncio.run(session.finalize())
+
+        self.assertEqual(mock_compose.call_count, 2)
+        self.assertTrue(any("ffmpeg_with_music_failed" in w for w in session.warnings))
+
+
 if __name__ == "__main__":
     unittest.main()

tools/ci_set_package_version.py

@@ -1,79 +0,0 @@
-"""Patch pyproject.toml and __init__.py version for CI builds (not committed)."""
-from __future__ import annotations
-
-import os
-import re
-import sys
-from pathlib import Path
-
-ROOT = Path(__file__).resolve().parent.parent
-
-
-def _read_base_version() -> str:
-    text = (ROOT / "pyproject.toml").read_text(encoding="utf-8")
-    match = re.search(r'^version\s*=\s*"([^"]+)"', text, re.MULTILINE)
-    if not match:
-        raise SystemExit("ERROR: version not found in pyproject.toml")
-    base = match.group(1)
-    return re.sub(r"\.post\d+$", "", base)
-
-
-def resolve_version() -> str:
-    ref = os.environ.get("GITHUB_REF", "")
-    if ref.startswith("refs/tags/v"):
-        return ref.removeprefix("refs/tags/v")
-    if ref.startswith("refs/tags/"):
-        return ref.removeprefix("refs/tags/")
-
-    run_number = (
-        os.environ.get("GITHUB_RUN_NUMBER")
-        or os.environ.get("GITHUB_RUN_ID")
-        or "0"
-    )
-    base = _read_base_version()
-    return f"{base}.post{run_number}"
-
-
-def patch_version(version: str) -> None:
-    pyproject = ROOT / "pyproject.toml"
-    py_text = pyproject.read_text(encoding="utf-8")
-    py_text, n = re.subn(
-        r'^version\s*=\s*"[^"]*"',
-        f'version = "{version}"',
-        py_text,
-        count=1,
-        flags=re.MULTILINE,
-    )
-    if n != 1:
-        raise SystemExit("ERROR: failed to patch version in pyproject.toml")
-    pyproject.write_text(py_text, encoding="utf-8")
-
-    init_py = ROOT / "src" / "jiangchang_desktop_sdk" / "__init__.py"
-    init_text = init_py.read_text(encoding="utf-8")
-    init_text, n = re.subn(
-        r'^__version__\s*=\s*"[^"]*"',
-        f'__version__ = "{version}"',
-        init_text,
-        count=1,
-        flags=re.MULTILINE,
-    )
-    if n != 1:
-        raise SystemExit("ERROR: failed to patch __version__ in __init__.py")
-    init_py.write_text(init_text, encoding="utf-8")
-
-
-def main() -> None:
-    version = resolve_version()
-    print(f"Resolved package version: {version}")
-    patch_version(version)
-    if os.environ.get("GITHUB_OUTPUT"):
-        with open(os.environ["GITHUB_OUTPUT"], "a", encoding="utf-8") as fh:
-            fh.write(f"package_version={version}\n")
-
-
-if __name__ == "__main__":
-    try:
-        main()
-    except SystemExit as exc:
-        print(exc, file=sys.stderr)
-        raise

tools/release.ps1

@@ -28,6 +28,7 @@
   加密与 ZIP 内容由 CI 工作流 reusable-release-skill.yaml 的「Encrypt Source Code」步骤执行。CI 会：
   - 加密 scripts/（递归 PyArmor -r，输出到包内 scripts/，与源码目录树一致）
   - 复制 SKILL.md
+  - 若根目录存在 README.md，则复制到包根（明文，用于技能市场用户说明）
   - 复制 references/（排除 REQUIREMENTS.md）
   - 复制 assets/
   - 复制 tests/