Agent skill

Tencent Mps

by LeoYeAI in 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…

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Install Tencent Mps

skills CLI
$ npx skills add LeoYeAI/openclaw-master-skills --skill tencent-mps -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install LeoYeAI/openclaw-master-skills tencent-mps --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ 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-src

Use ~/.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/

Facts

Skill name
tencent-mps
GitHub stars
2.2k
Token cost
~3.6k tokens
SKILL.md length
596 words
Files
26 (incl. scripts, references)
Skills in repo
1,235
Repo updated
First seen
Licence
MIT

At a glance

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…

  • Works in 6 steps: 脚本路径前缀:所有生成的 python 命令必须包含 scripts/… → 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… → mps_qualitycontrol.py 必须含 --definition → …
  • SKILL.md covers 环境配置, 本地文件处理流程, 异步任务说明 and 脚本功能映射(职责边界), plus 3 more sections
  • Runs Python scripts from its folder; calls python and pip; needs TENCENTCLOUD_SECRET_KEY

What it does

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.

Example prompts

  • “/tencent-mps”

Requirements

  • Python 3
  • A credential in TENCENTCLOUD_SECRET_KEY

Workflow steps

6 steps, taken from the first numbered list in SKILL.md.

  1. 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。
  2. 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。
  3. mps_qualitycontrol.py 必须含 --definition
  4. mps_av_understand.py 必须含 --mode 和 --prompt
  5. mps_narrate.py 必须含 --scene
  6. mps_highlight.py 必须含 --scene

What it can do on your machine

Read from SKILL.md and the folder at commit e5199b5. It shows what the files ask for, not the result of running them.

  • Tool permissions

    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.

  • Runs code

    Ships 13 files in scripts/ (Python, from the files we listed), which the agent can run.

    Shell commands in SKILL.md call:

    • python
    • pip

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    Links to these hosts (documentation or services it may open):

    • cloud.tencent.com

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names these keys or tokens, usually read from environment variables:

    • TENCENTCLOUD_SECRET_KEY

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

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.

Always · name and description, kept in context so the agent knows when to use it
~72
When it runs · the whole SKILL.md, loaded when a task matches
~3.6k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~22k

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.

Safety

Auto-check passed

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.

SKILL.md

The full file from LeoYeAI/openclaw-master-skills at commit e5199b5, republished under its MIT licence (© LeoYeAI). 596 words, ~3,612 tokens.

Download SKILL.mdSave it as .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.
name
tencent-mps
description
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。
metadata.version
1.1.2

腾讯云媒体处理服务(MPS)

💰 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

环境配置

检查环境变量:

bash
python scripts/load_env.py --check-only

配置(~/.profile 或 ~/.bashrc):

bash
# 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:

bash
pip install tencentcloud-sdk-python cos-python-sdk-v5

本地文件处理流程

MPS 只接受 URL 或 COS 对象作为输入,本地文件必须先上传。

用户输入本地文件时的自动处理流程

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

bash
python scripts/mps_cos_upload.py --local-file <本地文件路径> --cos-key <目标路径>
  • 使用 --cos-key 指定合理的存储路径(默认路径 input/)
  • 记录上传返回的 COS 信息:bucket、region、key

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)

bash
python scripts/mps_cos_download.py --cos-key <输出key> --local-file <本地保存路径>
输入方式说明

根据输入来源不同,支持两种方式:

方式一:COS 路径方式(推荐用于本地上传文件)

使用 --cos-object <key> 参数(或 --cos-input-bucket/--cos-input-region/--cos-input-key)

  • 适用场景:用户上传本地文件到 COS 后处理
  • 原因:本地上传的文件可能没有公开读取权限,直接使用 URL 可能会失败
  • 示例:--cos-object input/video.mp4
方式二:URL 方式(适用于已有 URL)

使用 --url <url> 参数

  • 适用场景:用户直接提供文件 URL(包括其他账号/来源的 COS URL、外部链接等)
  • 要求:URL 必须可公开访问或已携带有效签名
  • 示例:--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。

手动处理示例

如需手动执行,完整流程如下:

bash
# 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)

异步任务说明

所有脚本默认自动轮询等待完成。

  • 只提交不等待:加 --no-wait,脚本返回 TaskId
  • 手动查询:音视频用 mps_get_video_task.py,图片用 mps_get_image_task.py

脚本功能映射(职责边界)

💰 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.pyAIGC 图片生成
AI 生视频(文生视频/图生视频/分镜生成)mps_aigc_video.pyAIGC 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.pyVideoRemake,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.pyProcessMedia 任务查询
查询图片处理任务状态mps_get_image_task.pyProcessImage 任务查询
上传本地文件到 COSmps_cos_upload.py本地→COS 前置步骤
从 COS 下载文件mps_cos_download.pyCOS→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。

Show full SKILL.md (282 more words)Show less

生成命令的强制规则

  1. 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。

  2. 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。

  3. mps_qualitycontrol.py 必须含 --definition:

    • 音频质检:--definition 50
    • 画面质检(默认):--definition 60
    • 播放兼容性:--definition 70
  4. mps_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
  5. mps_narrate.py 必须含 --scene:

    • 值必须是预设枚举之一:short-drama | short-drama-no-erase
    • 用户说"有字幕"/"带硬字幕"时默认选含擦除场景(short-drama)
    • 用户说"没有字幕"/"原片无字幕"/"不擦除"时选 -no-erase 场景(short-drama-no-erase)
    • 多集视频时,第一集用 --url/--cos-object,后续集用 --extra-urls 按顺序追加
    • 禁止传入 scriptUrls 相关参数(本次不支持输入自定义脚本)
  6. mps_highlight.py 必须含 --scene:

    • 值必须是预设枚举之一:vlog | vlog-panorama | short-drama | football | basketball | custom
    • 用户提到"篮球"/"足球"/"短剧"/"VLOG"等关键词时直接映射到对应 --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
    • 禁止生成预设表以外的 ExtendedParameter 字段或值
    • 用户请求处理直播流集锦时,告知当前 skill 不支持直播流,需使用 MPS API 直接调用

关键脚本说明

视频增强 (mps_enhance.py)

大模型增强模板(--template),按场景+目标分辨率选择:

场景720P1080P2K4K
真人(Real)327001327003327005327007
漫剧(Anime)327002327004327006327008
抖动优化327009327010327011327012
细节最强327013327014327015327016
人脸保真327017327018327019327020
去字幕擦除 (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

大模型音视频理解 (mps_av_understand.py)

通过 AiAnalysisTask.Definition=33 + ExtendedParameter(mvc.mode + mvc.prompt) 控制。

bash
# 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 --json
媒体质检 (mps_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
bash
# 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-wait
视频去重 (mps_vremake.py)
bash
# 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

AI 解说二创 (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。

bash
# 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

精彩集锦 (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。

bash
# 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:

  • 本脚本仅支持处理离线文件,不支持直播流
  • --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
  • ExtendedParameter 必须从预设场景参数中选择,禁止自行拼装
用量统计 (mps_usage.py)
bash
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

API 参考

脚本文档
mps_transcode.py / mps_enhance.py / mps_subtitle.py / mps_erase.pyProcessMedia
mps_qualitycontrol.pyProcessMedia AiQualityControlTask
mps_imageprocess.pyProcessImage
mps_av_understand.pyVideoComprehension AiAnalysisTask
mps_vremake.pyVideoRemake AiAnalysisTask
mps_narrate.pyProcessMedia AiAnalysisTask
mps_highlight.pyProcessMedia AiAnalysisTask
mps_aigc_image.pyCreateAigcImageTask
mps_aigc_video.pyCreateAigcVideoTask
mps_usage.pyDescribeUsageData
mps_get_video_task.pyDescribeTaskDetail
mps_get_image_task.pyDescribeImageTaskDetail

© LeoYeAI, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 25 other files (scripts, references) in skills/tencent-mps of LeoYeAI/openclaw-master-skills.

  • SKILL.md
  • LICENSE.txt
  • _meta.json
  • desc.txt
  • references/params.md
  • references/scripts-detail.md
  • scripts/load_env.py
  • scripts/mps_aigc_image.py
  • scripts/mps_aigc_video.py
  • scripts/mps_av_understand.py
  • scripts/mps_cos_download.py
  • scripts/mps_cos_list.py
  • scripts/mps_cos_upload.py
  • scripts/mps_enhance.py
  • scripts/mps_erase.py
  • scripts/mps_get_image_task.py
  • scripts/mps_get_video_task.py
  • scripts/mps_highlight.py
  • scripts/mps_imageprocess.py
  • … and 7 more

Open the folder on GitHubat commit e5199b5

Compare with similar skills

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.

Tencent Mps compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Tencent Mps this skillLeoYeAI/openclaw-master-skills2.2k—~3.6kAutomated safety check: PassMIT
Mps ConsoleJetBrains/MPS1.7k—~4.1kAutomated safety check: PassApache-2.0
Mps BaselanguageJetBrains/MPS1.7k—~2.4kAutomated safety check: PassApache-2.0
Mps QuotationsJetBrains/MPS1.7k—~2.5kAutomated safety check: PassApache-2.0
Mps TestsJetBrains/MPS1.7k—~3kAutomated safety check: PassApache-2.0
Mps Ide PluginJetBrains/MPS1.7k—~3.7kAutomated safety check: PassApache-2.0

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Questions about Tencent Mps

What does Tencent Mps do?

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.

How do I install Tencent Mps in Claude Code?

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.

How do I install Tencent Mps in Codex?

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.

Can I use Tencent Mps in Cursor, Gemini CLI or GitHub Copilot?

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.

What does Tencent Mps need to run?

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.

Does Tencent Mps access the network?

SKILL.md names 1 domain. As links in the text: cloud.tencent.com. This is read from the text; nothing was executed.

Is Tencent Mps safe to install?

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.

What licence does Tencent Mps use?

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.

How many tokens does Tencent Mps use?

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.

What are the alternatives to Tencent Mps?

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.

Who maintains Tencent Mps?

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.