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.
git clone --depth 1 https://github.com/dasein108/yt-mem-aiWrote 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/commands/dasein108/yt-mem-ai/yt-setup)<a href="https://agentmods.dev/commands/dasein108/yt-mem-ai/yt-setup"><img src="https://agentmods.dev/badge/commands/dasein108/yt-mem-ai/yt-setup/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/commands/dasein108/yt-mem-ai/yt-setup"><img src="https://agentmods.dev/badge/commands/dasein108/yt-mem-ai/yt-setup.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 | $0.00021 | $0.00519 |
| Opus 5 | $0.00010 | $0.00260 |
| Sonnet 5 | $0.00004 | $0.00104 |
| Haiku 4.5 | $0.00002 | $0.00052 |
Grade A, and why
yt-setup 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.
What it actually says
Run the yt-mem-ai first-run setup as a short interactive wizard, using the yt
skill's "Configure & maintain" flow. Ask one thing at a time; skip a step if the
user says it's already fine. Persist every choice with uvx yt-mem-ai config set KEY VALUE (global config ~/.yt-mem-ai/config.env).
- Prereqs — confirm
uv/uvxis on PATH (uvx --version). If missing, point to https://docs.astral.sh/uv/ and stop. - Show current state — run
uvx yt-mem-ai config listand summarize what's already set vs default. - Cookies browser — the fix for YouTube's "Sign in to confirm you're not a
bot" check. Ask which browser they're logged into YouTube on and set
YT_COOKIES_BROWSER(chrome/brave/firefox/edge, or blank for none). - Webshare proxy (optional) — only if they hit IP rate-limits. If yes, set
WEBSHARE_PROXY_USERNAME+WEBSHARE_PROXY_PASSWORD, then eitherYT_USE_WEBSHARE true(proxy everything) orYT_CAPTIONS_USE_WEBSHARE true(proxy only the transcript API — recommended, yt-dlp stays direct). - Embedding model (optional) — default is English
all-MiniLM-L6-v2. If they watch non-English videos, setYT_EMBEDDING_MODEL paraphrase-multilingual-MiniLM-L12-v2. Note: if they already have a library, runuvx yt-mem-ai reembedafterwards to migrate it. - Caption languages (optional) — set
YT_CAPTION_LANGS(e.g.en,es) if they want a non-default priority order. - Verify — run
uvx yt-mem-ai config listto show the final state, then offer a smoke test:/yt-summarize <a short YouTube URL>.
Keep it conversational and skippable; don't set anything the user didn't confirm.
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.
- 8d ago First seen · 32 lines · 21 tokens per session scan A 321fa15251b6
yt-setup is a command published in the GitHub repository dasein108/yt-mem-ai (7 stars, last pushed 16d ago), licensed MIT. It adds 21 tokens to every session and 519 once invoked, about $0.0001 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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handoff
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