AAS Core is a local control plane for coding agents that lets them search a large catalogue of skills, choose a stack, validate it, and create a reproducible plan. It is used to assemble and review agent workflows through its CLI, local MCP server, catalogue, plugins, and Workbench. The catalogue add-ons provide the skills, plugins, bundles, and workflows that AAS Core helps agents select and validate.
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 sickn33/agentic-awesome-skills --skill apify-youtube-transcript-scrapergit clone --depth 1 https://github.com/sickn33/agentic-awesome-skillsWrote 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/sickn33/agentic-awesome-skills/apify-youtube-transcript-scraper)<a href="https://agentmods.dev/skills/sickn33/agentic-awesome-skills/apify-youtube-transcript-scraper"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/apify-youtube-transcript-scraper/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/sickn33/agentic-awesome-skills/apify-youtube-transcript-scraper"><img src="https://agentmods.dev/badge/skills/sickn33/agentic-awesome-skills/apify-youtube-transcript-scraper.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 | $0.00048 | $0.02304 |
| Opus 5.5 | $0.00019 | $0.00922 |
| Sonnet 5.5 | $0.00010 | $0.00461 |
| Haiku 4.5 | $0.00005 | $0.00230 |
Grade A, and why
apify-youtube-transcript-scraper 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 today.
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.
Copies of this mod
1 near-identical copy found in the catalogue:
- apify-youtube-transcript-scraper — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 186 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube Transcript Scraper
Turn a YouTube link, a channel or a playlist into text with one run of harshmaur/youtube-transcript-scraper. Each video gives one row with the transcript and the video facts. The agent picks the input list, sets how many videos to read per channel, and chooses the transcript shape.
Disclosure: the Actor is paid per result and is built by the skill author. Links carry no affiliate parameters.
When to Use
Use to summarize public YouTube videos, find timestamped quotations, export captions, or research transcripts from channels and playlists.
Example prompts
Prompts this skill handles:
- "Summarize https://youtu.be/jNQXAC9IVRw in five bullet points."
- "Give me SRT subtitles for these three videos."
- "Pull the transcripts of the last 20 videos from @mkbhd and list every product he reviewed."
- "Transcripts of this playlist, in Spanish, with timestamps so I can link to the exact second."
Out of scope (the boundary):
- "Download the MP4" or "get the audio" — this Actor returns text and metadata only.
- "Find videos about X" — it does not search YouTube. Get the video, channel or playlist links first.
- "Read the comments" — use a YouTube comments Actor.
Prerequisites
- Apify account (sign up). The free plan's monthly credit pays for about 1,000 transcripts.
- Authentication via one of:
apify login(OAuth, if you use the Apify CLI)APIFY_TOKENenvironment variable- Token from Apify Console → Settings → Integrations
- A previously installed and reviewed Apify CLI, or the Apify MCP server (see "Calling the Actor").
Workflow
Step 1 — Pick the input list
| The user gives you | Field | Notes |
|---|---|---|
Video links: watch?v=, youtu.be/, /shorts/, /live/ |
videoUrls |
One row per link. maxVideos does not apply. |
A channel: @handle, youtube.com/@handle, /channel/UC…, /c/Name |
channelUrls |
The newest uploads, up to maxVideos per channel. |
A playlist: youtube.com/playlist?list=… |
playlistUrls |
Playlist order, up to maxVideos; about 100 at most. |
What ships with it
1 file 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.
- today First seen · 186 lines · 48 tokens per session scan A 85cb19c1eb3f
apify-youtube-transcript-scraper is a skill published in the GitHub repository sickn33/agentic-awesome-skills (48,269 stars, last pushed today), licensed MIT. It adds 48 tokens to every session and 2,304 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 2026-10-22.
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