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 wvov7/course-revision-skills --skill note-single-lecturegit clone --depth 1 https://github.com/wvov7/course-revision-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/wvov7/course-revision-skills/note-single-lecture)<a href="https://agentmods.dev/skills/wvov7/course-revision-skills/note-single-lecture"><img src="https://agentmods.dev/badge/skills/wvov7/course-revision-skills/note-single-lecture/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/wvov7/course-revision-skills/note-single-lecture"><img src="https://agentmods.dev/badge/skills/wvov7/course-revision-skills/note-single-lecture.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 | $0.00103 | $0.04456 |
| Opus 5.5 | $0.00041 | $0.01782 |
| Sonnet 5.5 | $0.00021 | $0.00891 |
| Haiku 4.5 | $0.00010 | $0.00446 |
Grade A, and why
note-single-lecture 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 1mo 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 — 243 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Note Single Lecture
Applicability
- User asks for 单讲笔记, 课程笔记, lecture notes, mind-map notes, or
note-single-lecture - Input is one lecture PDF/PPT (ask which file if several candidates exist)
- Desired pipeline: mind map → note-generation prompt → Chinese classroom notes
Output Contract
For one lecture file, create these workspace-relative output folders unless the user asks otherwise:
- Intermediate folder:
note-single-lecture-work/<pdf-stem>/ - Final notes folder:
note-single-lecture/
Put every intermediate/generated working artifact in note-single-lecture-work/<pdf-stem>/, including extracted text, rendered page images, outline JSON, mind map PNG, prompt MD, scratch audits, and temporary checks.
Put the final classroom note Markdown only in note-single-lecture/.
Produce exactly these named artifacts unless the user asks otherwise:
note-single-lecture-work/<pdf-stem>/<pdf-stem>_思维导图.pngnote-single-lecture-work/<pdf-stem>/<pdf-stem>_笔记生成提示词.mdnote-single-lecture/<pdf-stem>_课程笔记.md
Use the source lecture PDF/PPT, generated mind map, and generated prompt as inputs for the final notes. Copy the final Markdown notes to the clipboard only when the user explicitly wants Feishu-ready output.
Workflow
1. Inspect the lecture
- Identify the single source lecture file. If multiple candidate PDFs/PPTs exist, ask which one.
- Define
<pdf-stem>from the source file name without extension. - Create
note-single-lecture-work/<pdf-stem>/for intermediate artifacts andnote-single-lecture/for final notes. - Extract slide/page text with
pdftotext -layoutfor PDFs when available. For PPTX, use available Office/Python extraction tools. - Get page/slide count and a title list.
- Render sparse or visual-heavy pages to images using
pdftoppmor another local renderer, especially pages with diagrams, screenshots, code images, tables, examples, exercises, or answer slides. - Treat the current lecture file as authoritative; prior notes are only examples.
- Ignore non-course-content administrative information by default, including opening lecturer names/affiliations and closing email/contact/forum/Q&A-channel slides, unless the user explicitly asks to preserve administrative information.
What ships with it
3 files beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 1mo ago First seen · 243 lines · 103 tokens per session scan A 4b80a95311c1
note-single-lecture is a skill published in the GitHub repository wvov7/course-revision-skills (3 stars, last pushed 2mo ago), licensed MIT. It adds 103 tokens to every session and 4,456 once invoked, about $0.0004 per session on Opus 5.5. 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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