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 aliildan/ytb-tools --skill yt-researchgit clone --depth 1 https://github.com/aliildan/ytb-toolsWrote 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/aliildan/ytb-tools/yt-research)<a href="https://agentmods.dev/skills/aliildan/ytb-tools/yt-research"><img src="https://agentmods.dev/badge/skills/aliildan/ytb-tools/yt-research.svg" alt="Measured on agentmods" 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 | $0.00078 | $0.00969 |
| Opus 5 | $0.00039 | $0.00485 |
| Sonnet 5 | $0.00016 | $0.00194 |
| Haiku 4.5 | $0.00008 | $0.00097 |
Grade A, and why
yt-research 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 7d 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.
How it starts
The opening of the file, as written. The whole thing — 77 lines — stays where its author put it; the contents beside it link to each section on GitHub.
YouTube topic research (search → transcripts → summaries → digest)
This skill runs the full pipeline over many videos using the ytb-tools MCP tools
(youtube_search, youtube_get_transcript, youtube_save_summary).
Inputs (parse from the user's request)
- keyword (required) — the search query.
- count (default 10) — how many videos to process (the "N").
- depth (default
quick) —quick|standard|detailed. - language (optional) — override the summary language (default = each video's language).
Steps
1. Search
Call youtube_search with query = keyword and limit = count. Report how many
results actually came back (it may be fewer than requested — YouTube limits search
depth).
2. Confirm before large runs
If the result count is greater than 20, STOP and confirm with the user before continuing — tell them exactly how many videos will be fetched and summarized and that it will take time and tokens. Wait for a yes. Skip this confirmation only if the user already explicitly approved a large run in their request (e.g. "yes, summarize all 150").
3. Fetch + summarize in batches
Process the videos in batches of 10. For each batch:
- For each video, call
youtube_get_transcriptwith the videoId.- If a video has no transcript (error), skip it and record it in a "skipped" list — do not abort the whole run.
- Summarize each fetched transcript at the chosen depth, in the transcript's
language (or the
languageoverride). Pick the model by depth and dispatch a subagent (Task tool) per summary — run the batch's summaries in parallel:quick→ modelhaiku(claude-haiku-4-5): one-line TL;DR + 3–5 bullets.standard→ modelsonnet(claude-sonnet-4-6): key points + takeaways.detailed→ modelopus(claude-opus-4-8): chapters, themes, quotes. Each subagent receives the transcriptfullTextand returns only the summary.
- For each summary, call
youtube_save_summarywithvideoId, the summary text, thestyle(= depth),title, videourl, the model id, andlanguage. - After each batch, post a short progress line:
Batch k/N done — M summarized, S skipped.
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.
- 7d ago First seen · 77 lines · 78 tokens per session scan A 1a4398163498
yt-research is a skill published in the GitHub repository aliildan/ytb-tools (0 stars, last pushed 2mo ago), licensed MIT. It adds 78 tokens to every session and 969 once invoked, about $0.0004 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.
Other skills, from other repositories
systematic-debugging
Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.
local-ai-agents
Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…
next-cache-components-adoption
Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…
next-cache-components-optimizer
Drive a Next.js route to instant navigation by setting up an agentic loop, under Cache Components / PPR, on initial load (hard navigation) and client-side navigation (soft navigation). Encode the goal as a failing @next/playwright instant() e2e and work it to green, one verified route at a time; the shipped test then…
next-partial-prefetching-adoption
Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…
chronicle
Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…