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 SamurAIGPT/open-ai-youtube-agent --skill keyword-tag-researchgit clone --depth 1 https://github.com/SamurAIGPT/open-ai-youtube-agentWrote 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/samuraigpt/open-ai-youtube-agent/keyword-tag-research)<a href="https://agentmods.dev/skills/samuraigpt/open-ai-youtube-agent/keyword-tag-research"><img src="https://agentmods.dev/badge/skills/samuraigpt/open-ai-youtube-agent/keyword-tag-research/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/samuraigpt/open-ai-youtube-agent/keyword-tag-research"><img src="https://agentmods.dev/badge/skills/samuraigpt/open-ai-youtube-agent/keyword-tag-research.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 | $0.00026 | $0.00814 |
| Opus 5 | $0.00013 | $0.00407 |
| Sonnet 5 | $0.00005 | $0.00163 |
| Haiku 4.5 | $0.00003 | $0.00081 |
Grade A, and why
Keyword & Tag Research 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 3d 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 — 72 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Keyword & Tag Research Agent
Mission
Turn a video topic into a ranked list of YouTube-specific keywords and tags, sized by real search demand and competition on YouTube itself — not a generic web-search proxy.
Use this agent when
- A user is planning a video and wants to know what people actually search for on YouTube around the topic.
- A user wants tag suggestions beyond what they'd think of manually.
- A user wants to compare keyword difficulty across a few topic candidates before committing to one.
Required inputs
- A seed topic or a few candidate topics.
- Optional: target audience/niche to narrow suggestions.
Required connections
- A Muapi API key (
muapi).
Available Muapi capabilities
youtube.search_volume— YouTube search rankings by keyword. Backed by Muapi's live SEO API:POST /api/v1/seo-youtube-organic(live, tested 2026-09-09).youtube.related_keywords— still planned; a dedicated related-term expansion for YouTube search behavior is not wired up on Muapi.POST /api/v1/seo-related-keywordsexists but is Google web-search data, not YouTube-native — per the decision rule below, it is not a substitute.
Workflow
- Expand the seed topic into a candidate keyword/tag list.
- Pull YouTube-specific search volume and competition per candidate via
youtube.search_volume. - Expand top candidates with related terms via
youtube.related_keywords. - Rank by volume-to-competition ratio, flagging both high-volume/high-competition ("hard to break into") and lower-volume/low-competition ("easier win") options.
- Return a ranked keyword list plus a suggested tag set (primary + close variants + broader category tags).
Decision rules
- Never present Google web-search volume as a stand-in for YouTube search volume — if only the Google-side proxy is available (via
ai-seo-agent'sseo.keyword_research), say so explicitly rather than implying it's YouTube-native data. - Prefer a mix of one or two high-volume "reach" keywords with several lower-competition "easier win" keywords, rather than an all-high-competition list.
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.
- 3d ago Changed · -1 lines 567cd72c438a
- 4d ago Changed c4c2304901d8
- 13d ago First seen · 73 lines · 26 tokens per session scan A 986ddf7acc35
Keyword & Tag Research Agent is a skill published in the GitHub repository SamurAIGPT/open-ai-youtube-agent (2 stars, last pushed 3d ago), licensed MIT. It adds 26 tokens to every session and 814 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 2026-08-30.
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