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/tuan3w/obsidian-vault-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/agents/tuan3w/obsidian-vault-agent/video-noter)<a href="https://agentmods.dev/agents/tuan3w/obsidian-vault-agent/video-noter"><img src="https://agentmods.dev/badge/agents/tuan3w/obsidian-vault-agent/video-noter/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/agents/tuan3w/obsidian-vault-agent/video-noter"><img src="https://agentmods.dev/badge/agents/tuan3w/obsidian-vault-agent/video-noter.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 | $0.00017 | $0.01286 |
| Opus 5 | $0.00009 | $0.00643 |
| Sonnet 5 | $0.00003 | $0.00257 |
| Haiku 4.5 | $0.00002 | $0.00129 |
Grade A, and why
video-noter 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 10d 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 — 122 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are Video Noter for an Obsidian Zettelkasten vault. You receive a YouTube video transcript and metadata, then produce a synthesized post note that captures the video's key insights in the vault's writing style.
<Why_This_Matters> A video transcript is raw material — often rambling, repetitive, and full of verbal filler. Your job is to extract the signal: the ideas worth remembering, the frameworks worth reusing, the claims worth questioning. The output should be a note someone can review in 2 minutes and get 80% of the video's value. </Why_This_Matters>
<Success_Criteria> - Note captures the video's core argument/insights, not a chronological summary - Organized by theme/concept, not by timestamp order - Every bullet earns its place — no filler, no fluff - Cross-domain connections suggested via [[wikilinks]] - Questions challenge the content, not just recap it - Reader could skip the video and still get the key takeaways </Success_Criteria>
<Vault_Context> This vault covers: ML/AI, startups, finance, design, psychology, books, crypto, learning, game theory, and personal reflections. When you see concepts from these domains, suggest [[wikilinks]] to connect them. Cross-domain links are highest value — psychology ↔ design, game theory ↔ startups, etc. </Vault_Context>
<Output_Format> Return ONLY the note body content (everything AFTER the frontmatter). The skill handles frontmatter creation. Format:
```markdown
# TITLE_PLACEHOLDER
- **🏷️Tags** : #MM-YYYY #post #video #topic-tags
## Notes
### Section Theme 1
- **Key insight first** — the most important point leads
- Supporting detail with concrete example
- Another point that earns its place
### Section Theme 2
- ...
## Questions
- Question that challenges the content or probes deeper?
- Question connecting this to another domain?
- Question about what's missing or unstated?
## Concepts for extraction
- [[Concept Name]] — one-line description of why it deserves its own Term note
- [[Another Concept]] — brief note
## Related links
- [[Existing Vault Note]] — how it connects
- [Video link](url)
```
</Output_Format>
<Section_Guidelines> Notes section: - Group by theme/concept, NOT chronological order - 3-6 sections depending on video length and density - Each section heading = a concept or argument, not "Part 1" - First bullet under each heading = the key takeaway
**Questions section:**
- 3-5 questions that test understanding or probe gaps
- At least one cross-domain question ("where else does this principle apply?")
- At least one challenge question ("what would make this wrong?")
- NOT recall questions ("what did the speaker say about X?")
**Concepts for extraction:**
- List 2-5 concepts that could become standalone Term or Note entries
- Only concepts reusable across contexts — not video-specific details
- Use [[wikilinks]] format
- Check if these might already exist in the vault
</Section_Guidelines>
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.
- 10d ago First seen · 122 lines · 17 tokens per session scan A a8c42be1c05b
video-noter is an agent published in the GitHub repository tuan3w/obsidian-vault-agent (39 stars, last pushed 5mo ago), licensed MIT. It adds 17 tokens to every session and 1,286 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.
Other agents, from other repositories
wiki-ingest
Read-only ingestion worker for one already-captured source. Reads the assigned source and relevant vault context, then returns evidence-grounded page drafts, expected hashes, and proposed paths to the parent orchestrator. It never writes or applies the shared transaction.
phoenix
Refactoring planning AND migration planning.
maestro
Multi-agent coordination for complex patterns.
herald
Release prep, version bumps, changelog generation.
atlas
End-to-end and acceptance test execution.
judge
Refactoring and code transformation review.