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editing-decision-engine编辑决策引擎

Agent Skill

editing-decision-engine 用于处理 GitHub 仓库、Issue、Pull Request 和代码协作信息,适合在 Codex、Claude、Cursor、Gemini CLI 中需要围绕仓库状态、代码变更或协作事项进行整理时使用。可结合来源仓库、安装命令和原始 README 继续核验具体用法。安装前建议确认权限范围、维护状态,以及是否会触发联网、命令执行或文件读写。

总安装

451

周安装

19

GitHub Stars

公开资料未说明

下载量

158
CodexClaudeCursorGemini CLI

安装说明

本站只整理中文说明和来源信息,不托管安装包,也不代用户安装。

GitHub

来源数

2

许可证

unknown

最后核验

2026-05-01

来源状态

来源可访问

安装方式

通过对话安装

复制提示词发给支持本地命令或 Skills 的 AI 助手,先确认命令和权限,再让它执行。

请帮我安装这个 Agent Skill:editing-decision-engine(编辑决策引擎)
来源仓库:https://github.com/postplusai/postplus-skills
仓库路径:skills/editing-decision-engine
安装命令:
npx skills add https://github.com/postplusai/postplus-skills --skill editing-decision-engine
安装前请先检查当前环境是否支持对应 CLI,并向我确认将要执行的命令、安装目录、联网范围和文件读写权限;确认后再执行。

命令行安装

复制命令到本机终端执行。该命令会通过 npx skills 从第三方来源获取 Skill;本站只展示命令,不托管安装包,也不自动执行。

skills.shnpx skills
npx skills add https://github.com/postplusai/postplus-skills --skill editing-decision-engine

简介

用于短视频剪辑决策规划,整合 A-roll、B-roll 与脚本节奏。

  • 适合在 Codex、Claude、Cursor、Gemini CLI 中制定短形式编辑策略。
  • 输出高质量编辑决策包,不直接生成 NLE 时间线,保留人工干预空间。
  • 需明确主题与参考视频,避免过度自动化导致创意损失。
  • editing-decision-engine 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

Editing Decision Engine

Follow shared release-shell rules in:

  • postplus-shared release-shell rules

Use this skill when the user wants a strong short-form edit plan, not just a script rewrite or a generic video breakdown.

This skill is for post-edit decision making across:

  • A-roll performance
  • B-roll proof footage
  • script meaning
  • beat timing
  • reference-video editing patterns
  • final edit packaging

Do not treat this as a video renderer.

First-version goal:

  • output a high-quality edit decision package
  • not fully automate the final NLE timeline

Use For

  • planning how to cut a talking-head short
  • deciding where B-roll should appear
  • mapping script beats to visual proof
  • deciding when to stay on A-roll vs cut away
  • translating a reference video into reusable edit patterns
  • packaging a cut plan for Premiere, Final Cut, CapCut, or a human editor

Trigger Signals

Use this skill when the user asks for things like:

  • 这条怎么剪
  • 根据 A-roll 和 B-roll 设计剪法
  • 参考某条视频的剪辑逻辑
  • 按脚本和素材做 post-edit plan
  • 逐句决定哪里贴屏幕、哪里留脸
  • 给我一个时间轴级别的剪辑方案

Do not use this skill when the user only needs:

  • raw video analysis without edit decisions
  • frame extraction without timeline reasoning
  • render generation from image and audio

Route those to:

  • a dedicated visual analysis workflow
  • skills/40-creative/frame-extraction
  • skills/40-creative/video-batch-runner

Core Principle

Do not describe footage only by what appears on screen.

For edit planning, the important question is:

  • what does this shot prove
  • what beat does it support
  • how much attention should it take
  • whether it should lead, support, bridge, or punctuate

The same B-roll clip can be:

  • primary proof
  • support proof
  • transition cover
  • pace reset
  • visual filler

depending on the spoken beat around it.

Read These References

  • workflow and decision rules: references/workflow.md
  • core objects and output shapes: references/schemas.md

Required Inputs

The skill works best when at least these exist:

  • script text or spoken transcript
  • local A-roll file or a reliable description of the A-roll performance
  • local B-roll files or a usable B-roll shot inventory
  • intended output length or target platform

Optional but high-value inputs:

  • one or more reference videos
  • subtitle draft or transcript with timestamps
  • previous edit notes
  • campaign or persona context

If assets are missing, do not pretend the plan is precise.

Instead:

  1. state which decisions are grounded
  2. state which decisions are provisional
  3. produce the strongest plan possible from available evidence

Workflow

1. Lock the edit thesis

Before building a timeline, identify:

  • what the video is trying to prove
  • whether it is tutorial-led, viewpoint-led, comparison-led, or proof-led
  • what visual contrast drives the piece

Examples:

  • old fragmented workflow vs in-context workflow
  • tool overload vs cleaner setup
  • annoying to start vs easy to start

2. Break the spoken content into beats

Do not plan edits sentence by sentence only.

Break into edit beats based on:

  • meaning shift
  • emotional shift
  • proof need
  • pace change

Each beat should capture:

  • the spoken line or paraphrase
  • timing if known
  • beat role
  • proof requirement
  • visual demand

3. Understand assets semantically

For A-roll:

  • delivery energy
  • pauses
  • emphasis words
  • facial or body moments worth preserving

For B-roll:

  • what it literally shows
  • what it proves
  • where it is strongest
  • how long it can stay on screen before feeling repetitive

For references:

  • what structural pattern is reusable
  • what is surface style only

4. Decide the cut logic

For each beat, decide:

  • stay on A-roll or cut away
  • which B-roll asset to use
  • whether the B-roll is primary or supporting proof
  • overlay length
  • subtitle density
  • whether to use punch-in, hold, montage, J-cut, or L-cut

5. Package the output

Default output should include:

  • edit thesis
  • beat map
  • B-roll assignment table
  • time-ordered edit decisions
  • risks and missing assets

Release-Shell Execution Contract

  • keep edit theses, beat maps, asset notes, and intermediate decision packages under <work-folder>/.postplus/editing-decision-engine/
  • keep only final user-facing edit plans outside .postplus/
  • start with a bounded first pass on one sequence or one short video before broader edit planning
  • if required inputs such as transcript, A-roll context, or B-roll inventory are missing, stop immediately instead of switching to ad hoc shell glue

First-Version Boundary

Keep the first version pragmatic.

Prefer:

  • markdown edit plans
  • JSON beat maps
  • B-roll proof tables
  • simple timeline-ready CSV if useful

Do not require in v1:

  • direct XML generation for NLEs
  • automatic cut rendering
  • perfect shot detection
  • automatic motion-design systems

Output Standard

A strong result from this skill should let a human editor start cutting immediately.

Minimum bar:

  • they can tell what the first 3 seconds should do
  • they know where the proof moments land
  • they know which B-roll is essential vs optional
  • they know where the edit should breathe instead of over-cutting

If the output cannot guide a real editor, it is not specific enough.

适合场景

01

用户想查找某类 Agent Skill 时

02

需要根据任务场景推荐可安装能力包时

03

需要对比不同来源的安装命令和来源信息时

能力概览

能力 1

按任务关键词查找相关 Skills

能力 2

展示可复制的安装命令

能力 3

保留来源站点、仓库和原始说明,方便继续核验

能力 4

展示第三方安全扫描或审计结果

安装后应在对应宿主中按原始 README 的触发条件使用;具体调用方式请以来源页面和 README 为准。

平台分布

Codex

34.55%
按下载量换算55

Claude

30.9%
按下载量换算49

Cursor

19.11%
按下载量换算30

Gemini CLI

10.33%
按下载量换算16

安全审计

Gen Agent Trust Hub

通过

Socket

可疑

Snyk

通过

权限和风险

执行命令

安装流程涉及命令执行,可能通过 npx skills add https://github.com/postplusai/postplus-skills --skill editing-decision-engine 联网下载 Skill 或依赖。用户安装前应确认命令来源、仓库内容和执行环境。

安装前确认

本站仅展示第三方公开信息,不托管安装包,不提供自动安装或运行环境。安装前应自行审查源码、依赖和命令行为。来源安全扫描存在 warning/failed 结果,不能写成本站确认安全。当前只有一个来源,正式发布前建议补源仓库或其他目录站核验。

来源信息

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