C31-cvideo

C31-cvideo is a skill for Claude Code, Codex from ChianW/C31. It costs 29 tokens per session (1,064 once invoked), scanned A, original, MIT.

A skill that takes a YouTube link, extracts its full transcript, saves it to a knowledge base and produces a structured analysis.

In plain words
What is it for?
Use it to ingest and summarise YouTube videos from standard links, Shorts links, youtu.be links or a video ID.
Why use it?
It turns a video into searchable written notes, including a fallback transcription path when captions are unavailable.

Skill for Claude CodeCodex

Which agent this was written for is unclear — built for openclaw. Also seen: positional $N argument; built for openclaw.

Good fit Use it to ingest and summarise YouTube videos from standard links, Shorts links, youtu.be links or a video ID.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/chianw/c31/c31-cvideo
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 ChianW/C31 --skill c31-cvideo
Clone the repo
git clone --depth 1 https://github.com/ChianW/C31

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 C31-cvideo

README.md
[![agentmods](https://agentmods.dev/badge/skills/chianw/c31/c31-cvideo/github.svg)](https://agentmods.dev/skills/chianw/c31/c31-cvideo)
Your own site
<a href="https://agentmods.dev/skills/chianw/c31/c31-cvideo"><img src="https://agentmods.dev/badge/skills/chianw/c31/c31-cvideo/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 C31-cvideo

Your own site · 80×15
<a href="https://agentmods.dev/skills/chianw/c31/c31-cvideo"><img src="https://agentmods.dev/badge/skills/chianw/c31/c31-cvideo.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 29 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,064 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 1 finding. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00029 $0.01064
Opus 5 $0.00015 $0.00532
Sonnet 5 $0.00006 $0.00213
Haiku 4.5 $0.00003 $0.00106

Measured 8d ago against content hash 40cd768f74a9, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

C31-cvideo 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 8d 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.

curl -X POST https://youtube-transcript.ai/mcp \
skills/personal/C31-cvideo/SKILL.md · 111 lines

How it starts

The opening of the file, as written. The whole thing — 111 lines — stays where its author put it; the contents beside it link to each section on GitHub.

C31-Video-Ingest Skill

触发词

帮我看, 帮我总结, 看一下, 帮我总结这个视频, 看一下这个视频, 看这个视频

功能

接收任意 YouTube 链接 → 自动提取完整文字稿 → 保存到知识库 → 生成结构化分析

执行流程

Step 1: 接收链接

用户发送 YouTube 链接(支持多种格式):

  • https://www.youtube.com/watch?v=XXXX
  • https://youtu.be/XXXX
  • https://www.youtube.com/shorts/XXXX
  • 裸 video ID: XXXX

Step 2: 提取 Video ID

用正则表达式从各种 URL 格式中提取 11 位 video ID。

Step 3: 获取文字稿(主路径)

调用 youtube-transcript.ai MCP 服务器:

curl -X POST https://youtube-transcript.ai/mcp \
  -H "Content-Type: application/json" \
  -d '{
    "jsonrpc": "2.0",
    "method": "tools/call",
    "params": {
      "name": "get_youtube_transcript",
      "arguments": {"video": "VIDEO_ID", "lang": "en"}
    },
    "id": 1
  }'

特点:

  • 免费,无需 API key
  • 秒级返回
  • 支持多语言字幕选择(lang 参数)
  • 返回带时间戳的完整文字稿

Step 4: 兜底路径(无字幕视频)

如果 MCP 返回 TranscriptsDisabledNoTranscriptFound:

  1. 检查环境变量 OPENAI_API_KEY
  2. yt-dlp 提取音频(需 ffmpeg
  3. 调用 OpenAI Whisper API 转录($0.006/分钟)

Step 5: 保存与归档

保存到: memory/moc/video_{video_id}_{timestamp}_{source}.md

Frontmatter 包含:

  • video_id
  • source (mcp / whisper)
  • fetched_at
  • url
  • duration
  • word_count

Step 6: 分析输出

自动分析并输出:

  • 核心信息: 主角、产品、成绩
  • 具体背景: 起点、早期失败、关键转折
  • 方法论: 步骤拆解、工具使用
  • 引爆案例: 具体帖子/内容、数据结果
  • 可应用方式: 映射到用户当前项目

依赖

工具 必需 安装命令
youtube-transcript.ai MCP 无需安装,直调 API
python3 系统自带
yt-dlp ⚠️ 仅兜底 pip install yt-dlp
ffmpeg ⚠️ 仅兜底 apt-get install ffmpeg
OPENAI_API_KEY ⚠️ 仅兜底 环境变量

脚本位置

~/.openclaw/scripts/c31-video-ingest.py

用法示例

# 直接给 video ID
python3 ~/.openclaw/scripts/c31-video-ingest.py 96jN2OCOfLs

# 给完整 URL
python3 ~/.openclaw/scripts/c31-video-ingest.py "https://www.youtube.com/watch?v=XXXX"

# 指定语言
python3 ~/.openclaw/scripts/c31-video-ingest.py XXXX --lang zh-CN

已知限制

  1. YouTube 直接访问在中国大陆环境可能超时(MCP 服务器在海外,通常可访问)
  2. MCP 返回的文字稿可能含重复行(YouTube 自动字幕的重复片段问题)
  3. 视频若无字幕且未配置 OPENAI_API_KEY,会失败

Read the full file on GitHub · 111 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. 8d ago First seen · 111 lines · 29 tokens per session scan A 40cd768f74a9

Subscribe to this mod's changes

C31-cvideo is a skill published in the GitHub repository ChianW/C31 (1 stars, last pushed 13d ago), licensed MIT. It adds 29 tokens to every session and 1,064 once invoked, about $0.0001 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 2026-08-31.

Related

Other skills, from other repositories

compare-harnesses

Diff two scaffolded harnesses (ADR-031). Reports manifest meta drift + host list + per-file fingerprint changes (added/removed/changed). Exits 0 IDENTICAL, 1 DRIFT, 2 missing manifest. Use --bundle for the ADR-031 schema-1 JSON envelope.

ruvnet/metaharness · 66 tokens

oia-manifest

Emit .harness/oia-manifest.json declaring layer alignment with the OIA v0.1 9-layer reference architecture. Self-describes the harness's MCP wiring, witness signing, audit log, identity posture (always 'none' at v0.1). --check verifies an existing manifest, --dry-run prints without writing, --json emits to stdout.

ruvnet/metaharness · 79 tokens

create-harness

Scaffold your own focused AI agent harness — pick host (Claude Code, Codex, pi.dev, Hermes), template, agents, skills, and ship a npm-publishable harness with its own npx CLI. Use when a user asks to "create my own agent harness", "scaffold a harness", "make a custom Claude Code plugin like ruflo", or "build a…

ruvnet/metaharness · 89 tokens

diag-harness

Kernel-version skew check (ADR-027). Reports manifest surface + manifest kernel + installed kernel + verdict (match/patch-diff/minor-diff/major-diff). Exits 1 on minor/major skew with a copy-pasteable npm install @metaharness/[email protected] next step. Exits 2 if no .harness/manifest.json at path.

ruvnet/metaharness · 85 tokens

example-harness

Scaffold a ready-made AI agent harness in one command from the 19 published @metaharness/ example packages — 9 host integrations (Claude Code, Codex, Hermes, pi.dev, OpenClaw, RVM, Copilot, OpenCode, GitHub Actions) + 10 vertical pods (devops, research, trading, support, legal, coding, education, sales, gaming…

ruvnet/metaharness · 90 tokens

repo-genome

7-section readiness scorecard for a LOCAL repo. Reports repo type + agent topology + MCP risk + test confidence + release readiness + recommended harness plan + scorecard. Exit 0 ready, 1 needs-work, 2 blocked. --json for the 6-field scorecard, --bundle for the ADR-031 schema-1 envelope.

ruvnet/metaharness · 73 tokens