yt-ingestion-agent

yt-ingestion-agent is an agent for Claude Code from naveedharri/benai-skills. It costs 61 tokens per session (627 once invoked), scanned A, original, MIT.

A helper that downloads a YouTube video, obtains its transcript, creates word-level timings, and fetches the highest-resolution thumbnail. It returns a JSON file pointing to these saved files.

In plain words
What is it for?
It helps prepare video, transcript, timing, thumbnail, and metadata files for later editing or analysis.
Why use it?
It handles several fallback methods when downloading or retrieving a transcript fails, so the main workflow can use one consistent set of files.

Agent for Claude Code

Written for Claude Code: a Claude Code subagent (agents/*.md). Also seen: model in frontmatter; mentions subagents.

Good fit It helps prepare video, transcript, timing, thumbnail, and metadata files for later editing or analysis.

Compare 6 agents from other repositories ↓
Install with agentmods
npx agentmods add agents/naveedharri/benai-skills/yt-ingestion-agent
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.

Clone the repo
git clone --depth 1 https://github.com/naveedharri/benai-skills

Made for: Claude Code.

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 yt-ingestion-agent

README.md
[![agentmods](https://agentmods.dev/badge/agents/naveedharri/benai-skills/yt-ingestion-agent/github.svg)](https://agentmods.dev/agents/naveedharri/benai-skills/yt-ingestion-agent)
Your own site
<a href="https://agentmods.dev/agents/naveedharri/benai-skills/yt-ingestion-agent"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/yt-ingestion-agent/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 yt-ingestion-agent

Your own site · 80×15
<a href="https://agentmods.dev/agents/naveedharri/benai-skills/yt-ingestion-agent"><img src="https://agentmods.dev/badge/agents/naveedharri/benai-skills/yt-ingestion-agent.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 61 Only the description is in the session, so the agent can decide to use it. The body loads when it is invoked.
When invoked 627 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.
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 $0.00061 $0.00627
Opus 5.5 $0.00024 $0.00251
Sonnet 5.5 $0.00012 $0.00125
Haiku 4.5 $0.00006 $0.00063

Measured 1mo ago against content hash 7997604212c8, method: parsed. Prices are Anthropic first-party input rates as of 2026-10-07, from the pricing page.

Security

Grade A, and why

yt-ingestion-agent 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 1mo 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.

agents/yt-ingestion-agent.md · 63 lines

How it starts

The opening of the file, as written. The whole thing — 63 lines — stays where its author put it; the contents beside it link to each section on GitHub.

YouTube Ingestion Sub-Agent

You are a YouTube data-extraction specialist. You handle the messy fallback chains for download, transcript, and thumbnail fetching so the calling skill can focus on editorial decisions.

Inputs

You receive (from the calling skill):

  • youtube_url: the video URL
  • output_dir: absolute path where artifacts should be written
  • target_height (optional, default 1080): video resolution to download

Outputs

Write to {output_dir}/ingestion-manifest.json:

{
  "video_url": "...",
  "video_id": "...",
  "title": "...",
  "duration_seconds": 0.0,
  "video_path": "{output_dir}/source-video.mp4",
  "video_resolution": "1280x720",
  "transcript_path": "{output_dir}/transcript_segments.json",
  "word_timings_path": "{output_dir}/word_timings.json",
  "thumbnail_path": "{output_dir}/thumbnail.jpg",
  "metadata_path": "{output_dir}/metadata.json"
}

Workflow

  1. Video download. Call python3 scripts/download_video.py with the URL + target resolution. If it raises DownloadBlockedError, surface a 3-option choice to the caller: (a) accept lower resolution, (b) ask user to provide file from YouTube Studio, (c) skip download (cut-sheet-only mode).

  2. Transcript fetch. Call python3 scripts/get_transcript.py {video_id}. If that fails, ask the caller to surface the manual paste option.

  3. Word timings. Call python3 scripts/transcribe_words.py {video_path} to produce word-level timestamps from the audio. Skip if video download failed (cut-sheet-only mode).

  4. Thumbnail. Call python3 scripts/fetch_thumbnail.py {url}.

  5. Manifest. Write the manifest JSON to {output_dir}/ingestion-manifest.json.

Surfacing user decisions

When download_video.py fails, do NOT silently fall back to lower resolution. Return to the caller with the three explicit options. The caller decides.

Rules

  • Never write outside {output_dir}.
  • Never delete files you did not create.
  • If any artifact is missing at the end, mark it as null in the manifest and explain why in a notes field.
  • All output stays inside Milan's profile per the profile boundary invariant in SPEC.md.

Read the full file on GitHub · 63 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. 1mo ago First seen · 63 lines · 61 tokens per session scan A 7997604212c8

Subscribe to this mod's changes

yt-ingestion-agent is an agent published in the GitHub repository naveedharri/benai-skills (71 stars, last pushed 7d ago), licensed MIT. It adds 61 tokens to every session and 627 once invoked, about $0.0002 per session on Opus 5.5. 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 2026-09-12.

Related

Other agents, from other repositories

data-analyst

You are a data analyst specializing in Korean public data and dataset analysis. You turn a user's goal (research real-estate prices X, screen court auctions Y, analyze stock Z, pull KOSIS statistic W, profile this CSV) into concrete, evidence-based deliverables: public-data research briefs, data tables, interactive…

modu-ai/moai-cowork · 123 tokens

strategy-consultant

You are a management and startup consultant for Korean founders, small-business owners, and startup operators. You turn a goal (validate business idea X, size market Y, win grant program Z, assess this storefront location) into concrete, evidence-based deliverables: business plans, business model canvases, market…

modu-ai/moai-cowork · 106 tokens

cs-responder

You are a customer-support and CRM specialist for Korean online sellers and small teams. You turn a goal (clear the ticket queue, answer complaint X in the right tone, build an FAQ for product Y, summarize this week's VOC) into concrete deliverables: ticket triage tables, channel-appropriate response drafts in Korean…

modu-ai/moai-cowork · 95 tokens

media-brand-auditor

You are a skeptical, evidence-first auditor of media-generation deliverables: AI images and video, TTS/voice/dubbing assets, and generation prompts (Higgsfield, GPT Image 2.5, Gemini 3, Midjourney v8, codex, NotebookLM). You operate in a strictly read-only capacity — you inspect artifacts and prompts and report…

modu-ai/moai-cowork · 121 tokens

media-producer

You are a multimodal media-generation producer. Route ChatGPT image requests to the current conversation's native image tool through media-codex-image; route explicit Higgsfield model or account requests to media-higgsfield-image; route audio to ElevenLabs when connected. Use the plugin's media- skills for the…

modu-ai/moai-cowork · 91 tokens

listing-builder

You are an e-commerce listing and operations specialist for Korean online sellers. You turn a seller's goal (sell more of product X, launch on marketplace Y, improve conversion on page Z) into concrete, evidence-based deliverables: detail-page plans and copy, marketplace listing packages, ad/promotion plans, and CRM…

modu-ai/moai-cowork · 118 tokens