media-transcript

A tool that turns the spoken words in online videos into clean text, using captions or subtitles. It supports YouTube and other sites handled by yt-dlp, a program for downloading video information.

In plain words
What is it for?
Use it for talks, tutorials, interviews, or any online video where the spoken content matters. It can include timestamps when you need to find when something was said, or return structured JSON for another program.
Why use it?
It lets coding tasks use a video's contents as text instead of ignoring the video. You can search, summarize, or answer questions about what was said.

Skill for Claude CodeCodex

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.

agentmods
npx agentmods add skills/sonichi/sutando/media-transcript
Any agent
npx skills add sonichi/sutando --skill media-transcript
Clone the repo
git clone --depth 1 https://github.com/sonichi/sutando

Made for: Claude Code, Codex.

Per session 0 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 525 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
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 $0.00000 $0.00525
Opus 5 $0.00000 $0.00262
Sonnet 5 $0.00000 $0.00105
Haiku 4.5 $0.00000 $0.00052

Measured 2d ago against content hash 73971d86292b, method: parsed. Prices are Anthropic first-party input rates as of 2026-08-30, from the pricing page.

Security

Grade A, and why

media-transcript 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 2d ago.

The scan reads SKILL.md. This mod also ships 1 executable file (scripts/transcript.py), listed below but not scanned — reading those needs a real analyzer, not pattern matching.

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.

skills/media-transcript/SKILL.md · 30 lines

How it starts

The opening of the file, as written. The whole thing — 30 lines — stays where its author put it; the contents beside it link to each section on GitHub.

media-transcript

Pull a video's transcript (captions/subtitles) as clean text — the doc-ingest sibling for video. Any task that references a YouTube (or other yt-dlp-supported) URL can consume the spoken content as text instead of being blind to it.

Usage:

python3 skills/media-transcript/scripts/transcript.py <url> [--lang en] [--timestamps] [--json]

Prints the transcript to stdout. --timestamps prefixes blocks with [mm:ss] cue starts (use when the question asks when/after what something was said). --json wraps the result as {"url", "ok", "kind", "text"|"error"} for programmatic callers.

When to use

  • A task references a video URL whose content matters ("what did they say about X", "what number is mentioned after Y", summarizing a talk).
  • The agent-eval harness hits video-based benchmark tasks (4 of 10 GAIA L3 fails on 2026-07-30 were video-content questions this skill unblocks).
  • Anything needing spoken-word content where captions exist.

Not for:

  • Local audio/video files — use skills/audio-transcribe (whisper on the audio track); the script points there and exits 3.
  • Videos with no captions at all — v1 is captions-only (uploader subs preferred, auto-captions fallback). The script says so honestly (exit 1) rather than guessing; a whisper-on-downloaded-audio fallback is a possible v2, deliberately out of scope (media downloads are heavyweight and often unnecessary).

Behavior

  • Prefers uploader subtitles over auto-generated captions; --lang preference (default en) with graceful fallback to available English variants.
  • Downloads ONLY the subtitle track — never the media stream — into a private temp dir, removed afterwards. No API keys.
  • Auto-caption VTTs repeat rolling caption windows; the parser dedupes them, strips inline tags/entities, and drops cue numbers, producing readable prose.
  • yt-dlp is probed at runtime (PATH binary, else the importable module) — a host without it gets one actionable error naming the install, never a crash (same design language as doc-ingest's extractor probing).

Read the full file on GitHub · 30 lines

Files

What ships with it

2 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.

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. 2d ago First seen · 30 lines · 0 tokens per session scan A 73971d86292b

Subscribe to this mod's changes

media-transcript is a skill published in the GitHub repository sonichi/sutando (389 stars, last pushed 2d ago), licensed MIT. It costs nothing until one of its globs matches a file; then it loads 525 tokens. 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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