news-rough-cut

news-rough-cut is a skill for Claude Code, Codex from gabrielmoreira/agent-skills-mirror. It costs 108 tokens per session (1,870 once invoked), scanned A, original, MIT.

A workflow for making a factual short news video from press conferences, interviews,现场 footage, or surveillance footage.

In plain words
What is it for?
It helps identify the main news topic, choose key facts and images, arrange the story, and check that the final edit remains accurate and concise.
Why use it?
It removes unrelated material while preserving the main facts, complete statements, and natural story order. It does not add music, narration, or sound effects.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit It helps identify the main news topic, choose key facts and images, arrange the story, and check that the final edit remains accurate and concise.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/gabrielmoreira/agent-skills-mirror/news-rough-cut
Install

Getting it into your agent

One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.

Any agent
npx skills add gabrielmoreira/agent-skills-mirror --skill news-rough-cut
Clone the repo
git clone --depth 1 https://github.com/gabrielmoreira/agent-skills-mirror

Made for: Claude Code, Codex.

Wrote this? Show the measurements

A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.

agentmods badge for news-rough-cut

README.md
[![agentmods](https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/news-rough-cut/github.svg)](https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/news-rough-cut)
Your own site
<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/news-rough-cut"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/news-rough-cut/github.svg" alt="Measured on agentmods" height="20"></a>

Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.

agentmods 80×15 button for news-rough-cut

Your own site · 80×15
<a href="https://agentmods.dev/skills/gabrielmoreira/agent-skills-mirror/news-rough-cut"><img src="https://agentmods.dev/badge/skills/gabrielmoreira/agent-skills-mirror/news-rough-cut.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 108 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,870 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
Origin original No closer match found in the catalogue.
Token cost

What it costs to keep this loaded

Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.

ModelPer sessionOnce invoked
Fable 5.1 $0.00108 $0.01870
Opus 5 $0.00054 $0.00935
Sonnet 5 $0.00022 $0.00374
Haiku 4.5 $0.00011 $0.00187

Measured 12d ago against content hash 5e2310e111ff, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-12, from the pricing page.

Security

Grade A, and why

news-rough-cut scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 12d ago.

A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.

Nothing flagged

None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.

mirrors/repos/0xsline@OpenChatCut/src/agent/skills/news-rough-cut/SKILL.md · 120 lines

How it starts

The opening of the file, as written. The whole thing — 120 lines — stays where its author put it; the contents beside it link to each section on GitHub.

News Rough Cut(新闻智能粗剪)

把新闻素材粗剪为一条内容完整、逻辑清晰、节奏紧凑的新闻短视频。忠实于原始素材,不加任何外部声音,保持客观、正式、紧凑、清晰的信息型新闻风格。

This is an OpenChatCut-native workflow. Use the current project's assets, transcript, word-level editing, timeline, and editing tools. Do not depend on external download or transcode pipelines.

工作流总览

  1. 完整分析素材(剪辑前必做):识别素材中的新闻事件、核心话题、关键人物、重要结论及有效画面,再确定剪辑主线和成片时长。使用 read_projecttranscribe_trackview_timeline_frames 逐段核对素材内容。
  2. 话题分析与时长确定:判断素材包含多少个话题,区分核心话题与次要内容。
  3. 内容组织:开头直接呈现最重要的新闻结果/核心结论/最新进展/关键现场画面,不铺垫。
  4. 剪辑执行:按保留/删除规则筛选,讲话按语义完整切割。
  5. 音频只保留目标新闻素材原声:开始编辑前只把用户明确指定/选中的新闻素材及其原始现场声列入允许来源;未明确指定时只采用活动时间线上已存在的新闻画面与现场声。媒体池里的 BGM、音效、配音、旁白和其他未选素材即使早已存在,也不得进入允许来源。
  6. 终检:逐段回放核对事实忠实、讲话语义完整、剪切点衔接自然。

话题分析与时长确定

  • 原则上一条成片只围绕一条核心新闻主线展开。
  • 若素材中存在多个相互独立的话题,优先选择新闻价值最高、信息最完整、画面最充分的话题进行剪辑;不要将无关话题强行拼接在同一条视频中。
  • 成片时长不做固定限制,根据以下因素自动确定:
    • 核心新闻的信息量;
    • 有效人物讲话的长度;
    • 事件发展阶段和最新进展;
    • 关键现场画面的数量;
    • 保证新闻语义完整所需要的时长。
  • 信息较少时应缩短成片,避免为了延长时长加入无关内容;信息较多时可以适当延长,不能为了压缩时长而剪断人物讲话、遗漏关键事实或破坏新闻逻辑

内容组织逻辑

成片开头直接呈现最重要的新闻结果、核心结论、最新进展或关键现场画面,不使用冗长铺垫。整体按照以下逻辑组织:

  1. 发生了什么;
  2. 目前有哪些最新进展;
  3. 最终结果、后续影响或相关回应。

若新闻事件尚未结束,应以当前已经确认的最新进展收尾,不得自行推测结果。

内容保留规则

优先保留以下内容:

  • 新闻事件的核心事实;
  • 时间、地点、人物和事件结果;
  • 最新进展及权威回应;
  • 重要人物具有实际信息量的讲话;
  • 新闻现场、采访、发布会、监控画面及相关有效素材;
  • 能够直接说明事件经过、结果或影响的关键画面。

所有保留内容必须服务于核心新闻主线。

内容删除规则

删除以下内容:

  • 广告和商业推广;
  • 节目宣传、频道包装及片头片尾;
  • 主持人寒暄和无信息量的串场;
  • 重复表述和重复画面;
  • 无效停顿、口头语及明显空白;
  • 与核心事件无关的冗长背景;
  • 不影响新闻理解的次要内容;
  • 无法验证、表意模糊或容易造成误解的片段。

人物讲话剪辑规则

  • 人物讲话必须保持语义完整
  • 优先在以下位置切割:
    • 一个完整句子结束后;
    • 人物自然停顿处;
    • 讲话内容发生明显转折处;
    • 镜头自然转场处。
  • 不得从一句话中间强行切断,不得只保留部分表述导致原意改变,不得将不同时间、不同语境下的讲话错误拼接。
  • 若一段讲话较长,可删除其中重复、空泛或无关的句子,但保留下来的内容必须能够独立表达完整意思
  • 使用词级编辑工具(文字稿)按词删改,保证落点落在完整句子边界。

事实与逻辑要求

剪辑必须忠于原始新闻素材,不得:

  • 改变人物讲话原意;
  • 夸大或弱化事实;
  • 将不同事件错误关联;
  • 通过镜头拼接制造虚假因果关系;
  • 将推测性内容表达为确定事实;
  • 使用与新闻事件不对应的画面误导观众;
  • 为追求节奏而删除必要的前因后果。

音频要求

  • 不得新增任何背景音乐、配音、旁白、音效、转场音效或其他外部声音。
  • 只保留原始素材中与新闻内容直接相关的人声和必要的现场声音。
  • 删除广告音乐、节目包装音乐以及与核心新闻无关的声音。
  • 处理剪切点时应保证原始人声衔接自然,避免突然截断、重叠、爆音或明显音量跳变(用 edit_item 的 fadeInSeconds/fadeOutSeconds 微调剪切点即可,不用加音乐)。

Read the full file on GitHub · 120 lines

Changes

What this file has done since we first saw it

Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.

  1. 12d ago First seen · 120 lines · 108 tokens per session scan A 5e2310e111ff

Subscribe to this mod's changes

news-rough-cut is a skill published in the GitHub repository gabrielmoreira/agent-skills-mirror (17 stars, last pushed yesterday), licensed MIT. It adds 108 tokens to every session and 1,870 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.

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