Mps Console
JetBrains/MPS
Run or generate MPS Console code and jetbrains.mps.lang.smodel.query queries in MPS intentions, behavior, actions, generators, and BaseLanguage.
腾讯云 MPS 媒体处理服务。只要用户的请求涉及音视频或图片的处理、生成、增强、用量查询、内容理解、媒体质检,必须使用此 Skill。覆盖:转码/压缩/格式转换、画质增强/老片修复/超分、字幕提取/翻译/语音识别、去字幕/擦除水印/人脸模糊、图片超分/美颜/降噪、音频分离/人声提取/伴奏提取、AI生图/生视频(含分镜)、大模型音视频理解、媒体质检、用量统计。视频增强支持专用模板(真人/漫剧/抖动…
$ npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a claude-codeProject install by default; add -g for ~/.claude/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-mps --agent claude-codeProject scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/tencent-mps .claude/skills/tencent-mps && rm -rf skills-srcUse ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.
Claude Code skills documentation · loads skills from .claude/skills/
Install the "tencent-mps" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tencent-mps into .claude/skills/tencent-mps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-mps", then confirm the skill loads.Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$skill-installer install https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tencent-mpsType this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.
$ npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a codexProject install goes to .agents/skills/; add -g for ~/.codex/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-mps --agent codexProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/tencent-mps .agents/skills/tencent-mps && rm -rf skills-srcUse ~/.agents/skills/ instead of .agents/skills for a personal install.
Codex skills documentation · loads skills from .agents/skills/
Install the "tencent-mps" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tencent-mps into .agents/skills/tencent-mps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-mps", then confirm the skill loads.Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a cursorProject install goes to .agents/skills/; add -g for ~/.cursor/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-mps --agent cursorProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/tencent-mps .cursor/skills/tencent-mps && rm -rf skills-srcUse ~/.cursor/skills/ instead of .cursor/skills for a personal install.
Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/
Install the "tencent-mps" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tencent-mps into .cursor/skills/tencent-mps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-mps", then confirm the skill loads.Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gemini skills install https://github.com/LeoYeAI/openclaw-master-skills.git --path skills/tencent-mps--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.
$ npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a gemini-cliProject install goes to .agents/skills/; add -g for ~/.gemini/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-mps --agent gemini-cliProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/tencent-mps .gemini/skills/tencent-mps && rm -rf skills-srcUse ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.
Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/
Install the "tencent-mps" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tencent-mps into .gemini/skills/tencent-mps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-mps", then confirm the skill loads.Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-mpsInstalls for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).
$ npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a github-copilotProject install goes to .agents/skills/; add -g for ~/.copilot/skills/.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/tencent-mps .github/skills/tencent-mps && rm -rf skills-srcUse ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.
GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/
Install the "tencent-mps" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tencent-mps into .github/skills/tencent-mps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-mps", then confirm the skill loads.GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
$ npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a opencodeOpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.
$ gh skill install LeoYeAI/openclaw-master-skills tencent-mps --agent opencodeProject scope by default (.agents/skills/); add --scope user for a personal install.
$ git clone --depth 1 https://github.com/LeoYeAI/openclaw-master-skills.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/tencent-mps .opencode/skills/tencent-mps && rm -rf skills-srcUse ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.
OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/
Install the "tencent-mps" agent skill from https://github.com/LeoYeAI/openclaw-master-skills/tree/main/skills/tencent-mps into .opencode/skills/tencent-mps/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "tencent-mps", then confirm the skill loads.OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.
tencent-mps腾讯云 MPS 媒体处理服务。只要用户的请求涉及音视频或图片的处理、生成、增强、用量查询、内容理解、媒体质检,必须使用此 Skill。覆盖:转码/压缩/格式转换、画质增强/老片修复/超分、字幕提取/翻译/语音识别、去字幕/擦除水印/人脸模糊、图片超分/美颜/降噪、音频分离/人声提取/伴奏提取、AI生图/生视频(含分镜)、大模型音视频理解、媒体质检、用量统计。视频增强支持专用模板(真人/漫剧/抖动…
Tencent Mps is an agent skill from LeoYeAI/openclaw-master-skills. 腾讯云 MPS 媒体处理服务。只要用户的请求涉及音视频或图片的处理、生成、增强、用量查询、内容理解、媒体质检,必须使用此 Skill。覆盖:转码/压缩/格式转换、画质增强/老片修复/超分、字幕提取/翻译/语音识别、去字幕/擦除水印/人脸模糊、图片超分/美颜/降噪、音频分离/人声提取/伴奏提取、AI生图/生视频(含分镜)、大模型音视频理解、媒体质检、用量统计。视频增强支持专用模板(真人/漫剧/抖动优化/细节最强/人脸保真,720P至4K)。无论是视频转码、去水印、提取人声、画质修复、内容理解、质量检测,还是AI生成图片视频,都应调用此 Skill。
Its SKILL.md is about 3.6k tokens, which your agent loads only when the skill is triggered. The skill folder holds 27 other files, including scripts and reference files (for example `_meta.json`, `references/params.md` and `references/scripts-detail.md`).
The repository describes itself as: 🧠 Curated collection of 1209+ best OpenClaw skills — weekly updated by MyClaw.ai. The licence is MIT.
6 steps, taken from the first numbered list in SKILL.md.
Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Ships 13 files in scripts/ (Python, from the files we listed), which the agent can run.
Shell commands in SKILL.md call:
pythonpipFrom the folder's file list and the shell code blocks in SKILL.md.
Links to these hosts (documentation or services it may open):
cloud.tencent.comFrom URLs in SKILL.md, links to its own repository left out.
Names these keys or tokens, usually read from environment variables:
TENCENTCLOUD_SECRET_KEYFrom names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.
Tencent Mps loads about 3.6k tokens when it runs, and up to ~22k if it reads all its reference files. Until then it costs about 72 tokens; SKILL.md has 596 words of instructions outside code blocks.
Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.
The automated check found no risky patterns in SKILL.md.
Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.
The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 596 words, ~3,612 tokens.
.claude/skills/tencent-mps/SKILL.md (or your agent's skills folder). This skill also uses 25 other files; get the full folder from GitHub.💰 费用提示:本 Skill 调用腾讯云 MPS 服务会产生相应费用,包括转码费、AI 处理费、存储费等。具体计费标准请参考 腾讯云 MPS 定价。每次使用MPS的媒体处理/图片处理/生图/生视频功能,一定要给出提示。
通过腾讯云官方 Python SDK 调用 MPS API,所有脚本位于 scripts/ 目录,均支持 --help 和 --dry-run。
详细参数:见
references/params.md完整示例集:见references/scripts-detail.md
检查环境变量:
python scripts/load_env.py --check-only配置(~/.profile 或 ~/.bashrc):
# 必须(所有脚本)
export TENCENTCLOUD_SECRET_ID="your-secret-id"
export TENCENTCLOUD_SECRET_KEY="your-secret-key"
# 以下场景必须配置 COS 变量:
# 1. 输入源为 --cos-object(即 COS 对象路径,非 URL)
# 2. 使用 mps_cos_upload.py / mps_cos_download.py 上传/下载本地文件
# 3. 脚本需要将处理结果写回 COS(OutputStorage)
export TENCENTCLOUD_COS_BUCKET="your-bucket" # COS 存储桶名
export TENCENTCLOUD_COS_REGION="your-bucket-region" # 存储桶地域,如 ap-guangzhou安装依赖:
pip install tencentcloud-sdk-python cos-python-sdk-v5MPS 只接受 URL 或 COS 对象作为输入,本地文件必须先上传。
当用户请求涉及本地文件路径(如 ./video.mp4、/path/to/image.jpg)时,按以下步骤自动处理:
步骤 1:上传文件到 COS
python scripts/mps_cos_upload.py --local-file <本地文件路径> --cos-key <目标路径>--cos-key 指定合理的存储路径(默认路径 input/)步骤 2:使用 COS 路径参数执行脚本 根据脚本类型,使用各个脚本中 传递 COS 路径的方式,如下:
| 脚本 | COS 路径参数方式 | 示例 |
|---|---|---|
mps_transcode.py | --cos-object <key> | --cos-object input/video.mp4 |
mps_enhance.py | --cos-object <key> | --cos-object input/video.mp4 |
mps_erase.py | --cos-object <key> | --cos-object input/video.mp4 |
mps_subtitle.py | --cos-object <key> | --cos-object input/video.mp4 |
mps_imageprocess.py | --cos-object <key> | --cos-object input/image.jpg |
mps_qualitycontrol.py | --cos-object <key> | --cos-object input/video.mp4 |
mps_av_understand.py | --cos-object <key> | --cos-object input/video.mp4 |
mps_vremake.py | --cos-object <key> | --cos-object input/video.mp4 |
mps_narrate.py | --cos-object <key> | --cos-object input/video.mp4 |
mps_highlight.py | --cos-object <key> | --cos-object input/video.mp4 |
mps_aigc_image.py | --cos-input-bucket <b> --cos-input-region <r> --cos-input-key <k> | --cos-input-bucket xxx --cos-input-region ap-guangzhou --cos-input-key input/img.jpg |
mps_aigc_video.py | --cos-input-bucket <b> --cos-input-region <r> --cos-input-key <k> | --cos-input-bucket xxx --cos-input-region ap-guangzhou --cos-input-key input/img.jpg |
注意:使用
--cos-object的脚本依赖环境变量TENCENTCLOUD_COS_BUCKET和TENCENTCLOUD_COS_REGION;AIGC 类脚本需要显式传递完整的 COS 信息。
步骤 3:下载处理结果(如需要)
python scripts/mps_cos_download.py --cos-key <输出key> --local-file <本地保存路径>根据输入来源不同,支持两种方式:
使用 --cos-object <key> 参数(或 --cos-input-bucket/--cos-input-region/--cos-input-key)
--cos-object input/video.mp4使用 --url <url> 参数
--url https://example-bucket.cos.ap-guangzhou.myqcloud.com/video.mp4⚠️ 注意:如果 URL 来自本地上传的 COS 文件且没有公开权限,请使用方式一(COS 路径方式),脚本会自动生成带签名的 URL。
如需手动执行,完整流程如下:
# 1. 上传
python scripts/mps_cos_upload.py --local-file ./video.mp4 --cos-key input/video.mp4
# 2. 执行任务(使用 COS 路径)
python scripts/mps_transcode.py --cos-object input/video.mp4
# 3. 下载结果
python scripts/mps_cos_download.py --cos-key output/result.mp4 --local-file ./result.mp4返回结果含链接时,用 Markdown 格式返回给用户:[文件名](URL)
所有脚本默认自动轮询等待完成。
--no-wait,脚本返回 TaskIdmps_get_video_task.py,图片用 mps_get_image_task.py💰 以下操作将调用腾讯云 MPS 服务并产生费用。
选择脚本时必须严格按照映射关系,不得混用:
| 用户需求类型 | 使用脚本 | 说明 |
|---|---|---|
| 检查画面质量、检测模糊/花屏 | mps_qualitycontrol.py | 唯一质检脚本,--definition 60(默认) |
| 检测播放兼容性、卡顿、播放异常 | mps_qualitycontrol.py | 唯一质检脚本,--definition 70 |
| 音频质量检测、音频事件检测 | mps_qualitycontrol.py | 唯一质检脚本,--definition 50 |
| 去除字幕、擦除水印、人脸/车牌模糊 | mps_erase.py | 仅用于画面内容擦除/遮挡 |
| 画质增强、老片修复、超分辨率 | mps_enhance.py | 视频画质提升 |
| 转码、压缩、格式转换 | mps_transcode.py | 编码格式处理 |
| 字幕提取、翻译、字幕类语音识别 | mps_subtitle.py | 字幕相关 |
| 图片处理(超分/美颜/降噪) | mps_imageprocess.py | 图片增强 |
| AI 生图(文生图/图生图) | mps_aigc_image.py | AIGC 图片生成 |
| AI 生视频(文生视频/图生视频/分镜生成) | mps_aigc_video.py | AIGC 视频生成,Kling 模型支持分镜功能 |
| 音视频内容理解(场景/摘要/分析/语音识别) | mps_av_understand.py | 大模型理解,必须提供 --mode 和 --prompt |
| 视频去重(画中画/视频扩展/换脸/换人等) | mps_vremake.py | VideoRemake,必须提供 --mode |
| 用量统计查询 | mps_usage.py | 调用次数/时长查询 |
| AI解说二创 / 短剧解说 / 自动生成短剧解说视频 / 短剧解说混剪 | mps_narrate.py | 必须从预设 --scene 中选择;不支持输入自定义脚本;多集视频按顺序通过 --extra-urls 追加 |
| 精彩集锦 / 高光提取 / 自动剪辑精彩片段 / 足球进球集锦 / 篮球集锦 / 短剧高光 | mps_highlight.py | 必须从预设 --scene 中选择,禁止自拼 ExtendedParameter;不支持直播流 |
| 查询音视频处理任务状态 | mps_get_video_task.py | ProcessMedia 任务查询 |
| 查询图片处理任务状态 | mps_get_image_task.py | ProcessImage 任务查询 |
| 上传本地文件到 COS | mps_cos_upload.py | 本地→COS 前置步骤 |
| 从 COS 下载文件 | mps_cos_download.py | COS→本地 后置步骤 |
| 列出 COS Bucket 文件 | mps_cos_list.py | 查看 COS 文件列表,支持路径过滤和文件名搜索 |
重要:
mps_erase.py职责是擦除/遮挡画面视觉元素,不涉及质量检测。 "画质检测"、"模糊"、"花屏"、"播放兼容性"、"音频质检" → 必须用mps_qualitycontrol.py。
脚本路径前缀:所有生成的 python 命令必须包含 scripts/ 路径前缀,格式为 python scripts/mps_xxx.py ...。禁止生成 python mps_xxx.py ...(缺少 scripts/ 前缀)的命令。
禁止占位符:所有参数值必须是真实值。若用户未提供必需值,先询问,不得用 <视频URL>、YOUR_URL 等占位符。
mps_qualitycontrol.py 必须含 --definition:
--definition 50--definition 60--definition 70mps_av_understand.py 必须含 --mode 和 --prompt:
--mode video(理解视频画面)或 --mode audio(仅音频,视频自动提取音频)--prompt 控制大模型理解侧重点,缺失时结果可能为空mps_narrate.py 必须含 --scene:
short-drama | short-drama-no-eraseshort-drama)-no-erase 场景(short-drama-no-erase)--url/--cos-object,后续集用 --extra-urls 按顺序追加scriptUrls 相关参数(本次不支持输入自定义脚本)mps_highlight.py 必须含 --scene:
vlog | vlog-panorama | short-drama | football | basketball | custom--scene,无需二次询问--prompt 和 --scenario 仅在 --scene custom 时生效,但二者非必填--top-clip 仅允许在 vlog / vlog-panorama / custom 场景下使用mps_enhance.py)大模型增强模板(--template),按场景+目标分辨率选择:
| 场景 | 720P | 1080P | 2K | 4K |
|---|---|---|---|---|
| 真人(Real) | 327001 | 327003 | 327005 | 327007 |
| 漫剧(Anime) | 327002 | 327004 | 327006 | 327008 |
| 抖动优化 | 327009 | 327010 | 327011 | 327012 |
| 细节最强 | 327013 | 327014 | 327015 | 327016 |
| 人脸保真 | 327017 | 327018 | 327019 | 327020 |
mps_erase.py)预设模板:101 去字幕 | 102 去字幕+OCR | 201 去水印高级版 | 301 人脸模糊 | 302 人脸+车牌模糊
mps_av_understand.py)通过 AiAnalysisTask.Definition=33 + ExtendedParameter(mvc.mode + mvc.prompt) 控制。
# 视频内容理解
python scripts/mps_av_understand.py \
--url https://example.com/video.mp4 \
--mode video \
--prompt "请分析这个视频的主要内容、场景和关键信息"
# 音频模式(视频自动提取音频)
python scripts/mps_av_understand.py \
--url https://example.com/video.mp4 \
--mode audio \
--prompt "请进行语音识别,输出完整文字内容"
# 对比分析(两段音视频)
python scripts/mps_av_understand.py \
--url https://example.com/v1.mp4 \
--extend-url https://example.com/v2.mp4 \
--mode audio \
--prompt "对比两段音频,分析差异"
# 查询任务
python scripts/mps_av_understand.py --task-id 2600011633-WorkflowTask-xxxxx --jsonmps_qualitycontrol.py)脚本支持以下 3 种系统预设模板(--definition 参数):
预设模板:
60(默认):格式质检-Pro版,检测画面模糊、花屏、画面受损等内容问题50:Audio Detection,音频质量/音频事件检测70:内容质检-Pro版,检测播放卡顿、播放异常、播放兼容性问题# 画面质检(默认,使用预设模板 60)
python scripts/mps_qualitycontrol.py --url https://example.com/video.mp4 --definition 60
# 播放兼容性质检(预设模板 70)
python scripts/mps_qualitycontrol.py --url https://example.com/video.mp4 --definition 70
# 音频质检(预设模板 50)
python scripts/mps_qualitycontrol.py --url https://example.com/audio.mp3 --definition 50
# 异步提交
python scripts/mps_qualitycontrol.py --url https://example.com/video.mp4 --definition 60 --no-waitmps_vremake.py)# 画中画去重(等待结果)
python scripts/mps_vremake.py --url https://example.com/video.mp4 --mode PicInPic --wait
# 视频扩展去重
python scripts/mps_vremake.py --url https://example.com/video.mp4 --mode BackgroundExtend --wait
# 换脸模式
python scripts/mps_vremake.py --url https://example.com/video.mp4 --mode SwapFace \
--src-faces https://example.com/src.png --dst-faces https://example.com/dst.png --wait
# 换人模式
python scripts/mps_vremake.py --url https://example.com/video.mp4 --mode SwapCharacter \
--src-character https://example.com/src_full.png \
--dst-character https://example.com/dst_full.png --wait
# 画中画 + LLM 提示词
python scripts/mps_vremake.py --url https://example.com/video.mp4 --mode PicInPic \
--llm-prompt "生成一个唯美的自然风景背景图片" --wait
# 异步提交(默认,不加 --wait)
python scripts/mps_vremake.py --url https://example.com/video.mp4 --mode PicInPic
# 查询任务
python scripts/mps_vremake.py --task-id 2600011633-WorkflowTask-xxxxx --json去重模式:PicInPic(画中画)BackgroundExtend(视频扩展)VerticalExtend(垂直填充)HorizontalExtend(水平填充)AB(视频交错)SwapFace(换脸)SwapCharacter(换人)
主要参数:--url / --cos-object / --task-id / --mode(必填)/ --wait / --llm-prompt / --llm-video-prompt / --src-faces+--dst-faces(换脸)/ --src-character+--dst-character(换人)/ --json / --dry-run
mps_narrate.py)输入原始视频,一站式自动完成解说脚本生成、脚本匹配成片、AI 配音、去字幕等操作,输出带有解说文案、配音和字幕的新视频。
# 短剧单集解说(默认含擦除,输出1个视频)
python scripts/mps_narrate.py --url https://example.com/drama.mp4 --scene short-drama
# COS对象输入
python scripts/mps_narrate.py --cos-object /input/drama.mp4 --scene short-drama
# 原视频无字幕,关闭擦除
python scripts/mps_narrate.py --url https://example.com/drama.mp4 --scene short-drama-no-erase
# 短剧三集合并解说,输出3个不同版本
python scripts/mps_narrate.py \
--url https://example.com/ep01.mp4 \
--extra-urls https://example.com/ep02.mp4 https://example.com/ep03.mp4 \
--scene short-drama \
--output-count 3
# Dry Run(预览转义后的 ExtendedParameter)
python scripts/mps_narrate.py --url https://example.com/drama.mp4 --scene short-drama --dry-run预设场景:short-drama(短剧,含擦除) | short-drama-no-erase(短剧,无擦除)
主要参数:--url / --cos-object(第一集,必填) / --scene(必填) / --extra-urls(第2集起) / --output-count(输出数量,默认1,最大5) / --no-wait / --dry-run
mps_highlight.py)使用 MPS 智能分析功能,通过 AI 算法自动捕捉并生成视频中的精彩片段(高光集锦)。固定使用 26 号预设模板,支持 VLOG、短剧、足球赛事、篮球赛事等多种场景。
# 足球赛事精彩集锦
python scripts/mps_highlight.py --cos-object /input/football.mp4 --scene football
# 短剧影视高光
python scripts/mps_highlight.py --cos-object /input/drama.mp4 --scene short-drama
# VLOG 全景相机
python scripts/mps_highlight.py --url https://example.com/vlog.mp4 --scene vlog-panorama
# 自定义场景(大模型版)
python scripts/mps_highlight.py --url https://example.com/skiing.mp4 \
--scene custom --prompt "滑雪场景,输出人物高光" --scenario "滑雪"
# 篮球赛事
python scripts/mps_highlight.py --cos-object /input/basketball.mp4 --scene basketball
# 指定输出片段数(仅 vlog/vlog-panorama/custom 支持)
python scripts/mps_highlight.py --cos-object /input/vlog.mp4 --scene vlog --top-clip 10
# Dry Run(仅打印请求参数)
python scripts/mps_highlight.py --cos-object /input/game.mp4 --scene football --dry-run预设场景:
vlog:VLOG、风景、无人机视频(大模型版)vlog-panorama:全景相机(开启全景优化,大模型版)short-drama:短剧、影视剧,提取主角出场/BGM高光(大模型版)football:足球赛事,识别射门/进球/红黄牌/回放(高级版)basketball:篮球赛事(高级版)custom:自定义场景,可传 --prompt 和 --scenario(大模型版)主要参数:--url / --cos-object(必填) / --scene(必填) / --prompt(custom场景) / --scenario(custom场景) / --top-clip(vlog/vlog-panorama/custom场景可用) / --no-wait / --dry-run
⚠️ 重要限制:
--top-clip 仅允许在 vlog / vlog-panorama / custom 场景下使用--prompt 和 --scenario 仅在 --scene custom 时生效,但二者非必填mps_usage.py)python scripts/mps_usage.py --days 30 --all-types
python scripts/mps_usage.py --start 2026-01-01 --end 2026-01-31
python scripts/mps_usage.py --type Transcode Enhance AIGC AIAnalysis--type 支持:Transcode Enhance AIAnalysis AIRecognition AIReview Snapshot AnimatedGraphics AiQualityControl Evaluation ImageProcess AddBlindWatermark AddNagraWatermark ExtractBlindWatermark AIGC
| 脚本 | 文档 |
|---|---|
mps_transcode.py / mps_enhance.py / mps_subtitle.py / mps_erase.py | ProcessMedia |
mps_qualitycontrol.py | ProcessMedia AiQualityControlTask |
mps_imageprocess.py | ProcessImage |
mps_av_understand.py | VideoComprehension AiAnalysisTask |
mps_vremake.py | VideoRemake AiAnalysisTask |
mps_narrate.py | ProcessMedia AiAnalysisTask |
mps_highlight.py | ProcessMedia AiAnalysisTask |
mps_aigc_image.py | CreateAigcImageTask |
mps_aigc_video.py | CreateAigcVideoTask |
mps_usage.py | DescribeUsageData |
mps_get_video_task.py | DescribeTaskDetail |
mps_get_image_task.py | DescribeImageTaskDetail |
© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file
SKILL.md and 25 other files (scripts, references) in skills/tencent-mps of LeoYeAI/openclaw-master-skills.
Open the folder on GitHubat commit e5199b5
Tencent Mps next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.
| Skill | Stars | Used in | Tokens | Auto-check | Licence | Repo updated |
|---|---|---|---|---|---|---|
| Tencent Mps this skillLeoYeAI/openclaw-master-skills | 2.2k | — | ~3.6k | Automated safety check: Pass | MIT | |
| Mps ConsoleJetBrains/MPS | 1.7k | — | ~4.1k | Automated safety check: Pass | Apache-2.0 | |
| Mps BaselanguageJetBrains/MPS | 1.7k | — | ~2.4k | Automated safety check: Pass | Apache-2.0 | |
| Mps QuotationsJetBrains/MPS | 1.7k | — | ~2.5k | Automated safety check: Pass | Apache-2.0 | |
| Mps TestsJetBrains/MPS | 1.7k | — | ~3k | Automated safety check: Pass | Apache-2.0 | |
| Mps Ide PluginJetBrains/MPS | 1.7k | — | ~3.7k | Automated safety check: Pass | Apache-2.0 |
JetBrains/MPS
Run or generate MPS Console code and jetbrains.mps.lang.smodel.query queries in MPS intentions, behavior, actions, generators, and BaseLanguage.
JetBrains/MPS
Author and edit MPS jetbrains.mps.baseLanguage (Java) nodes — choose between the Java parser and JSON AST blueprints, map Java syntax to baseLanguage concepts/roles, harvest persistent member…
JetBrains/MPS
A skill your agent uses when writing or debugging MPS quotations and anti-quotations — "node literals" that create SNode trees inline in behavior, typesystem, intentions, generator, and other model…
JetBrains/MPS
A skill your agent uses when writing or modifying tests inside MPS @tests models — NodesTestCase (typesystem, constraints, scopes, dataflow, generator output), EditorTestCase (intentions, actions…
JetBrains/MPS
A skill your agent uses when authoring or modifying MPS IDE plugins — code that integrates with the MPS / IntelliJ host IDE shell.
JetBrains/MPS
Create and execute IDE run configurations for MPS root nodes via MPS MCP — Java Application for IMainClass / ClassConcept with main, JUnit Tests for ITestCase.
LeoYeAI/openclaw-master-skills
Manages pipelines on a DevOps quality and efficiency platform through its OpenAPI: list workspaces and templates, create, update, run and cancel pipelines, and read run records.
LeoYeAI/openclaw-master-skills
Patches OpenClaw's Feishu extension so an edited document triggers an isolated agent session that reads the doc and replies inline, turning it into a live chat space.
LeoYeAI/openclaw-master-skills
Multi-context memory management system for OpenClaw agents with group-isolated storage, global shared memory, workspace organization, and group-specific skills isolation.
LeoYeAI/openclaw-master-skills
Runs a brand's AI-search visibility work end to end: diagnosing how AI platforms represent it, repositioning it, producing AI-optimized content and monitoring ongoing mentions.
LeoYeAI/openclaw-master-skills
Installs and authenticates the gws CLI, then automates Gmail, Drive, Sheets, Calendar, Docs, Chat and Tasks with ready-made recipes, persona bundles and security audits.
LeoYeAI/openclaw-master-skills
Runs four advisor roles, a fitness coach, nutritionist, data analyst and TCM practitioner, to build a health profile and track workouts, diet and wellness over time.
腾讯云 MPS 媒体处理服务。只要用户的请求涉及音视频或图片的处理、生成、增强、用量查询、内容理解、媒体质检,必须使用此 Skill。覆盖:转码/压缩/格式转换、画质增强/老片修复/超分、字幕提取/翻译/语音识别、去字幕/擦除水印/人脸模糊、图片超分/美颜/降噪、音频分离/人声提取/伴奏提取、AI生图/生视频(含分镜)、大模型音视频理解、媒体质检、用量统计。视频增强支持专用模板(真人/漫剧/抖动…. Tencent Mps is an agent skill from LeoYeAI/openclaw-master-skills.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a claude-code`. Or copy the skill folder (skills/tencent-mps in LeoYeAI/openclaw-master-skills) into .claude/skills/tencent-mps in your project. Claude Code loads it when a task matches its description.
Run `npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a codex`. Or copy the skill folder (skills/tencent-mps in LeoYeAI/openclaw-master-skills) into .agents/skills/tencent-mps in your project. Codex loads it when a task matches its description.
Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/tencent-mps, .gemini/skills/tencent-mps, .github/skills/tencent-mps and .opencode/skills/tencent-mps in your project.
Going by SKILL.md and its folder, Tencent Mps needs Python for the scripts in its folder, the command-line tools its instructions call (python and pip) and credentials named TENCENTCLOUD_SECRET_KEY. Our summary lists: Python 3; A credential in TENCENTCLOUD_SECRET_KEY.
SKILL.md names 1 domain. As links in the text: cloud.tencent.com. This is read from the text; nothing was executed.
Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.
Tencent Mps is published under the MIT licence (from the LICENSE file in the skill folder). It allows redistribution, so the full SKILL.md is shown on this page.
About 3.6k tokens (SKILL.md is roughly 14k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 19k tokens, read only when the agent opens those files.
Skills that share tags, products or a category with Tencent Mps: Mps Console (JetBrains/MPS, 1.7k stars), Mps Baselanguage (JetBrains/MPS, 1.7k stars), Mps Quotations (JetBrains/MPS, 1.7k stars) and Mps Tests (JetBrains/MPS, 1.7k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.
LeoYeAI (a GitHub user) maintains it in LeoYeAI/openclaw-master-skills, which has 2,161 GitHub stars. The repository holds 1,235 skills in this directory. The repository was last updated on July 20, 2026.
Source: LeoYeAI/openclaw-master-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.