media-ingest

media-ingest is a skill for Claude Code, Codex from timurgaleev/memex. It costs 52 tokens per session (1,017 once invoked), scanned A, original, MIT.

A workflow for bringing videos, audio, PDFs, books, screenshots, and GitHub repositories into a connected knowledge base.

In plain words
What is it for?
Use it to transcribe recordings, extract text from documents or images, identify mentioned people and companies, and link them to related pages.
Why use it?
It turns information spread across different formats into searchable pages while keeping transcripts, extracted text, and original sources available.

Skill for Claude CodeCodex

Written for no agent in particular: nothing here depends on one.

Good fit Use it to transcribe recordings, extract text from documents or images, identify mentioned people and companies, and link them to related pages.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/timurgaleev/memex/media-ingest
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 timurgaleev/memex --skill media-ingest
Clone the repo
git clone --depth 1 https://github.com/timurgaleev/memex

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 media-ingest

README.md
[![agentmods](https://agentmods.dev/badge/skills/timurgaleev/memex/media-ingest/github.svg)](https://agentmods.dev/skills/timurgaleev/memex/media-ingest)
Your own site
<a href="https://agentmods.dev/skills/timurgaleev/memex/media-ingest"><img src="https://agentmods.dev/badge/skills/timurgaleev/memex/media-ingest/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 media-ingest

Your own site · 80×15
<a href="https://agentmods.dev/skills/timurgaleev/memex/media-ingest"><img src="https://agentmods.dev/badge/skills/timurgaleev/memex/media-ingest.svg" alt="Reviewed on agentmods" width="80" height="20"></a>
Per session 52 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 1,017 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. Third-party audits
  • NVIDIA SkillSpector pass 7 Sept 2026
How audits are shown
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 $0.00052 $0.01017
Opus 5 $0.00026 $0.00508
Sonnet 5 $0.00010 $0.00203
Haiku 4.5 $0.00005 $0.00102

Measured 8d ago against content hash fc5cbf28ead3, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-08, from the pricing page.

Security

Grade A, and why

media-ingest 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 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.

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.

deploy/skills/media-ingest/SKILL.md · 126 lines

How it starts

The opening of the file, as written. The whole thing — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.

Media Ingest Skill

Ingest video, audio, PDF, book, screenshot, and GitHub repo content into the brain.

Filing rule: Read skills/_brain-filing-rules.md (via get_skill _brain-filing-rules) before creating any new page.

Contract

This skill guarantees:

  • Every ingested media item has a brain page with analysis (not just a transcript dump)
  • Transcripts (video/audio) saved in raw and human-readable formats
  • Entity extraction: every person and company mentioned gets back-linked
  • Raw sources preserved via the put_raw_data tool
  • Filing by primary subject, not by media format

Convention: See conventions/quality.md (via get_skill conventions/quality) for Iron Law back-linking.

Every mention of a person or company with a brain page MUST create a back-link.

Phases

Phase 1: Identify format and fetch

Format Action
YouTube/video URL Fetch transcript (Whisper, transcription service, or captions)
Audio file Transcribe with available STT service
PDF Extract text (OCR if needed)
Book PDF Extract text, identify chapters/sections
Screenshot/image OCR via vision model, extract text and entities
GitHub repo Clone, read README + key files, summarize architecture (optionally memex index the checkout for code-graph queries)

Phase 2: Preserve raw source

Store the extracted text or transcript for provenance with put_raw_data, keyed to the page slug. Binaries themselves are not stored in the brain — record the original URL or file path on the page's **Source:** line.

Phase 3: Create brain page

File by primary subject (not format). Use this template:

# {Title}

**Source:** {URL or file path}
**Format:** {video/audio/PDF/book/screenshot/repo}
**Created:** {date}

## Summary
{Key points, not a transcript dump}

## Key Segments / Highlights
{For video/audio: timestamped highlights. For books: chapter summaries.}

## People Mentioned
{List with links to brain pages}

## Companies Mentioned
{List with links to brain pages}

Read the full file on GitHub · 126 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 · 126 lines · 52 tokens per session scan A fc5cbf28ead3

Subscribe to this mod's changes

media-ingest is a skill published in the GitHub repository timurgaleev/memex (8 stars, last pushed yesterday), licensed MIT. It adds 52 tokens to every session and 1,017 once invoked, about $0.0003 per session on Opus 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 2026-08-31.

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