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ugc-content-graderUGC 内容分级器

Agent Skill

用于辅助文档、README、Markdown、说明文和内容稿件的整理与改写。它适合让 Agent 提炼结构、补齐章节、统一术语、检查链接或把零散材料整理成可读文档。使用时应保留项目已有事实、命令和路径,不要把未确认的信息写成确定结论;涉及对外文案时,还需要控制语气,避免过度营销或夸大能力。

总安装

250

周安装

10

GitHub Stars

4

下载量

81
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:ugc-content-grader(UGC 内容分级器)
来源仓库:https://github.com/tfcbot/rawugc-skills
仓库路径:skills/ugc-content-grader
安装命令:
npx skills add https://github.com/tfcbot/rawugc-skills --skill ugc-content-grader
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/tfcbot/rawugc-skills --skill ugc-content-grader

简介

辅助文档、README、Markdown 和内容稿件的整理与改写,提升内容可读性。

  • 可提炼结构、补齐章节、统一术语或检查链接,适用于内容生产场景。
  • 使用时保留项目已有事实与路径,避免将未确认信息写成确定结论。
  • 涉及对外文案时需控制语气,防止过度营销或夸大能力描述。
  • ugc-content-grader 属于待分类类 Skill,可作为该场景下的辅助能力补充。

SKILL.md

UGC Content Grader

Procedural knowledge for auditing and scoring short-form UGC video ideas destined for AI generation (RawUGC / Sora / Veo). Apply these rubrics to every card in a kanban board or any batch of UGC scripts.

When to Use

  • User asks to "score", "grade", "audit", or "review" UGC ideas
  • User asks to "improve" low-scoring content
  • User adds new ideas and wants them evaluated
  • User wants to check if content "sounds like an ad"

Scores

Every idea receives three scores. All three must be present.

1. Quality Score (1–10)

Does the script make sense for the target audience and short-form platform?

RangeLabelMeaning
8–10HighHook stops the scroll, overlay is tight, shot list is filmable, angle lands for the persona
5–7MidDecent but something is off — weak hook, overlay too long, angle mismatch
1–4LowDoesn't work — confusing, wrong audience, wouldn't hold attention past 1 second

See reference.md for the full quality rubric.

2. Complexity Score (low / medium / high)

How likely is AI video generation to fail or produce artifacts?

LevelMeaning
lowStatic location, one person, no props requiring precision, no on-screen text/numbers, no walking
mediumOne location change OR one precise prop interaction OR brief text on screen
highScreen content, multiple simultaneous props, walking while talking, specific readable text/numbers, two-phone setups

Target: low. If an idea scores medium or high, rewrite the shot list to remove the offending elements. Common fixes in reference.md.

3. Native Score (1–10)

Does this feel like organic creator content or does it read like an ad?

High = native/casual. Low = reads like an ad.

RangeLabelColorMeaning
7–10NativeGreenFeels like a real person posting organically — storytime, pov, rant, hot take, meme format
4–6MidOrangeMixed — decent hook but some ad structure leaking through
1–3AdsyRedReads like a marketing department wrote it — jargon, checklists, "link in bio", feature lists

See reference.md for the full native scoring rubric with red flags and green flags.

CTA Rules

  • Ratio: 1/3 of ideas should have a CTA. 2/3 should have NO CTA.
  • No "link in bio" — ever. It screams ad.
  • Acceptable CTA format: Comment-keyword style only (e.g. "comment SUNDAY and I'll send you the process")
  • No CTAs that sound like landing pages: "try it free today", "see what it costs", "start your free trial" are all banned.
  • When distributing CTAs across a batch, spread them evenly — don't cluster all CTAs in one funnel phase.

Improvement Workflow

When content scores below threshold, rewrite it following these principles:

  1. Hook: Rewrite as storytime, pov, hot take, or rant. First person. Emotional. Specific.
  2. Overlay: Conversational, not formatted. No bullet points or checklists. Short — max 4 lines.
  3. Shot List: Keep it to 3–4 simple shots. One static location. No complex choreography.
  4. Tone: Gen-Z native — self-deprecating, unhinged, chaotic, conspiratorial, smug, confused. NOT: professional, motivational, coach-y, LinkedIn energy.

Data Format

Scores are saved directly on each card object:

{
  "qualityScore": 9,
  "complexityScore": "low",
  "nativeScore": 8
}

For the full rubric details, scoring examples, red/green flags, and rewrite patterns see reference.md.

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

37.17%
按下载量换算30

Claude

28.93%
按下载量换算23

Cursor

18.41%
按下载量换算15

Gemini CLI

10.47%
按下载量换算8

安全审计

Gen Agent Trust Hub

通过

Socket

通过

Snyk

通过

权限和风险

只读

该 Skill 主要提供规则、说明或参考内容,本身偏只读;真正读写文件、联网或执行命令仍取决于宿主 Agent 的任务。

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。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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