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.
npx skills add redfox-data/redfox-community-dsh --skill youtube-commentgit clone --depth 1 https://github.com/redfox-data/redfox-community-dshWrote 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.
[](https://agentmods.dev/skills/redfox-data/redfox-community-dsh/youtube-comment)<a href="https://agentmods.dev/skills/redfox-data/redfox-community-dsh/youtube-comment"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/youtube-comment/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.
<a href="https://agentmods.dev/skills/redfox-data/redfox-community-dsh/youtube-comment"><img src="https://agentmods.dev/badge/skills/redfox-data/redfox-community-dsh/youtube-comment.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00108 | $0.02696 |
| Opus 5 | $0.00054 | $0.01348 |
| Sonnet 5 | $0.00022 | $0.00539 |
| Haiku 4.5 | $0.00011 | $0.00270 |
Grade A, and why
youtube-comment scanned grade A with 1 finding 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 9d 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.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
A: 不需要。脚本使用 Python 标准库 `urllib`，Python 3.6+ 环境即可直接运行。 How it starts
The opening of the file, as written. The whole thing — 245 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube视频评论分析
输入视频链接，一键获取评论数据与四维情感洞察，用数据看清 YouTube 平台的用户真实声音
简介
YouTube视频评论分析 是一款专为社交媒体运营、品牌方、市场研究人员和内容创作者设计的智能评论洞察工具。通过红狐 API 获取 YouTube 视频的真实评论数据，结合 AI 四维情感分析（积极/负面/需求/竞品），快速掌握任意视频下的用户反馈全貌。
- 核心价值：告别逐条翻评论，一次查询即可获得视频信息、评论全量列表与情感占比分析，快速定位舆情风向与用户需求
- 适用对象：品牌运营、社媒运营、市场策划、产品经理、内容创作者、MCN机构
- 技术基础：基于红狐数据平台的实时分析能力与智能情感分析
功能特性
核心能力
| 功能 | 说明 |
|---|---|
| 💬 评论获取 | 粘贴视频链接或视频ID即可拉取一级评论数据，支持多链接批量查询 |
| 📄 翻页续查 | 单页若干条一级评论，翻页令牌继续获取下一页（每页消耗一次积分） |
| 🤖 四维 AI 分析 | 逐条打标，四个维度（积极/负面/需求/竞品）各附真实占比与代表评论证据引用；竞品维度不明显时如实标注「不适用」 |
| 📊 评论排序 | 支持按热门（top）或最新（newest）排序，可按语言和地区偏好筛选 |
| 🌐 多语言支持 | 支持各语种视频评论，AI 分析基于原文语境（hashtag、@提及、emoji） |
| 🛡️ 积分保护 | 多链接查询、翻页前主动提示积分消耗，确认后才执行 |
特色亮点
- ⚡ 一句话查询：粘贴视频链接即可获取完整分析，无需记忆命令
- 🔒 零缓存设计：结果仅在对话中展示，不落盘缓存，数据安全可控
- 📋 标准分析报告：固定模板输出（视频信息→查询范围→评论列表→四维情感分析）
一键安装
前置条件
- 已安装 Python 3.6+
安装步骤
- 将技能文件夹放入你的 Skills 目录
- 配置数据服务接入凭证（详见 核心工作流）
使用指南
触发方式
当用户提到以下任意关键词时自动激活：
- "YouTube评论"、"油管评论"、"视频评论"、"YouTube作品评论分析"
- "评论分析"、"评论舆情"、"看评论"、"评论查询"
- 直接粘贴 YouTube 视频链接 + "评论/分析"
视频ID获取方式
视频ID可从视频链接中直接提取。例如：
- 视频链接：
https://www.youtube.com/watch?v=sa8AzBK4dao - Shorts链接：
https://www.youtube.com/shorts/sa8AzBK4dao - 短链接：
https://youtu.be/sa8AzBK4dao - 视频ID：
sa8AzBK4dao（即链接中v=或/shorts/或youtu.be/后面的部分）
支持 youtube.com 和 youtu.be 两种域名格式，带播放列表等参数的分享链接也可自动识别。
常用命令速查
| 意图 | 示例话术 | 效果 |
|---|---|---|
| 查看视频评论 | 「查询 https://www.youtube.com/watch?v=xxx」 | 获取视频信息 + 本页评论 + 四维分析 |
| 通过视频ID查询 | 「查看视频 sa8AzBK4dao 的评论」 | 自动识别ID并拉取评论 |
| 继续翻页 | 「下一页」 | 用上一页返回的 continuationToken 获取下一页评论（消耗一次积分，会先提示确认） |
| 批量查询 | 一次粘贴多条链接 | 提示积分消耗确认后，逐一拉取并独立分析 |
使用示例
示例1：标准查询
用户：查询 https://www.youtube.com/watch?v=sa8AzBK4dao AI：输出完整分析（视频信息→查询范围→评论列表→四维情感分析）
示例2：继续翻页
用户：下一页 AI：提示翻页将消耗一次积分，确认后携带 continuationToken 获取下一页评论并输出
示例4：视频无评论
用户：查询一条无评论的视频 AI：该视频暂无评论，请检查视频是否存在或已设为私密。（不主动替换查询其他视频）
What ships with it
6 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 9d ago First seen · 245 lines · 108 tokens per session scan A 103bfbf3afc1
youtube-comment is a skill published in the GitHub repository redfox-data/redfox-community-dsh (6 stars, last pushed yesterday), licensed MIT. It adds 108 tokens to every session and 2,696 once invoked, about $0.0005 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
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