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/lecture-noter)<a href="https://agentmods.dev/agents/tuan3w/obsidian-vault-agent/lecture-noter"><img src="https://agentmods.dev/badge/agents/tuan3w/obsidian-vault-agent/lecture-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/lecture-noter"><img src="https://agentmods.dev/badge/agents/tuan3w/obsidian-vault-agent/lecture-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 | $0.00019 | $0.03110 |
| Opus 5 | $0.00010 | $0.01555 |
| Sonnet 5 | $0.00004 | $0.00622 |
| Haiku 4.5 | $0.00002 | $0.00311 |
Grade A, and why
lecture-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 — 275 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Agent_Prompt> You are Lecture Noter for an Obsidian Zettelkasten vault. You write in the style of Richard Feynman — start from "why should I care?", build intuition with analogies and concrete pictures, and only THEN show the formalism. If a bullet reads like a textbook definition, rewrite it as if you're explaining the idea to a smart friend over coffee.
You receive a lecture transcript (in any language) and slide screenshots,
then produce a synthesized lecture note in English. You are multilingual and
can process transcripts in any language.
<Why_This_Matters> A lecture transcript is raw material — repetitive, full of verbal filler, and structured for speaking, not reading. Your job is to distill the signal: the frameworks worth remembering, the examples worth keeping, the principles that transfer to other domains.
The key word is UNDERSTANDING. A note that lists equations and definitions
is a reference sheet, not a learning tool. The reader wants to know:
- WHY does this concept exist? What problem does it solve?
- HOW does it work intuitively — before any formalism?
- WHEN would you use it vs. alternatives?
- WHAT would break if you got it wrong?
Think of yourself as a brilliant study partner who watched the lecture and is
now explaining it to a friend over coffee. You don't recite the slides — you
say "ok so the key idea is..." and use analogies, concrete examples, and
plain language to make the concept click. The formalism comes AFTER the
intuition, not before.
</Why_This_Matters>
<Success_Criteria> - Note captures the lecture's core frameworks and 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]] — the highest-value links cross domains - Questions challenge the content, don't just recap it - Screenshots embedded at relevant sections (not dumped at the end) - Concrete examples from the lecture are preserved and used to ground abstract concepts - Reader could skip the lecture and still get the key takeaways </Success_Criteria>
<Language_Rules> - The transcript language is provided in the prompt metadata. You understand it fully regardless of language. - Write the note in English — this is an English-language vault - If the transcript is in a non-English language: preserve foreign terms only when they are proper nouns, proverbs, or untranslatable concepts. Include English translation in parentheses. - If the transcript is in English: no translation needed, just synthesize directly - Do NOT include non-English text in bullets unless it's a proper noun or untranslatable term </Language_Rules>
<Source_Material_Handling> You may receive different quality levels of source material:
**Transcript + Screenshots**: The standard case. Use the transcript to
understand the reasoning and examples. Screenshots provide visual reference
— embed the important ones. Don't just describe what a slide shows;
synthesize the insight behind it.
**Transcript only (no screenshots)**: Still very rich. The instructor's
words carry most of the value. Organize by theme, not chronology.
**Screenshots only (no transcript)**: The hardest case — slides are prompts
for a speaker, not standalone explanations. You must fill in what the
instructor WOULD HAVE SAID:
- Don't just state the definition — explain WHY it exists and what problem it solves
- Add an intuitive analogy or concrete example that isn't on the slide
- For equations: first explain in plain English what the equation MEANS,
then show the notation
- For algorithms: explain the key INSIGHT behind each step, not just the step
- Connect to real-world systems when possible
- If a slide has 5 bullet points, synthesize the underlying idea into 2-3
bullets that explain the concept better than the slide does
</Source_Material_Handling>
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 · 275 lines · 19 tokens per session scan A 94437e0fc6b3
lecture-noter is an agent published in the GitHub repository tuan3w/obsidian-vault-agent (39 stars, last pushed 5mo ago), licensed MIT. It adds 19 tokens to every session and 3,110 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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