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 ChristinaAndrinopoyloy/claude-skills --skill lecture-notesgit clone --depth 1 https://github.com/ChristinaAndrinopoyloy/claude-skillsWrote 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/christinaandrinopoyloy/claude-skills/lecture-notes)<a href="https://agentmods.dev/skills/christinaandrinopoyloy/claude-skills/lecture-notes"><img src="https://agentmods.dev/badge/skills/christinaandrinopoyloy/claude-skills/lecture-notes/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/christinaandrinopoyloy/claude-skills/lecture-notes"><img src="https://agentmods.dev/badge/skills/christinaandrinopoyloy/claude-skills/lecture-notes.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 | $0.00125 | $0.00939 |
| Opus 5 | $0.00063 | $0.00469 |
| Sonnet 5 | $0.00025 | $0.00188 |
| Haiku 4.5 | $0.00013 | $0.00094 |
Grade A, and why
lecture-notes 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 11d 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 — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Taking Lecture Notes
Purpose
Transform raw lecture content (transcript, plain text, slides) into clean, structured notes that the user can use for study or reference.
Input
The user will provide:
- Required: The lecture text (transcript with or without timestamps, plain text, etc.)
- Optional — detail level: The user may ask for "concise" or "detailed" notes. If not specified, judge based on the complexity of the content.
- Optional — language: If the user does not specify, write the notes in the same language they used in their request.
Notes Principles — Critical
Study these principles carefully. They define the quality of the output:
- Hierarchy over lists. Don't just bullet-point everything. Use headers (
##,###) to show which concepts are central and which are subcategories. - Summarize, don't transcribe. The goal is not to copy the lecture — it's to extract the essence. Use your own words where it aids understanding.
- Surface the "why". If the lecture explains why something exists or why it matters, that should be visible in the notes — not just the "what".
- Analogies and examples. If the lecture uses an analogy or example to explain something difficult, include it — it's often the most useful part for studying.
- Callouts for key points. Use
> ⚠️or> 💡to highlight warnings, exceptions, or particularly important observations. - Tables where helpful. If the lecture compares things (e.g. A vs B) or presents structured data, use a table instead of parallel bullets.
- Don't overload. If something in the lecture is repetitive or obvious, skip it. Notes should be shorter than the lecture.
Notes Structure
Follow this structure (adapt it to fit the content):
- Title — A clear title that reflects the topic of the lecture.
- Main Sections — Group content into thematic sections with
##headers. Each section should have:- A short introductory sentence or two (prose, not a bullet)
- The key points as bullets or subsections
- Analogies/examples if present
- Callouts —
⚠️for pitfalls/exceptions,💡for important observations - Tables — Only where there is a comparison or structured information
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.
- 11d ago First seen · 85 lines · 125 tokens per session scan A f15cbf69dab2
lecture-notes is a skill published in the GitHub repository ChristinaAndrinopoyloy/claude-skills (1 stars, last pushed 3mo ago), licensed MIT. It adds 125 tokens to every session and 939 once invoked, about $0.0006 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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