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 jtprogru/bear-skills --skill obsidian-refactor-lecturegit clone --depth 1 https://github.com/jtprogru/bear-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/jtprogru/bear-skills/obsidian-refactor-lecture)<a href="https://agentmods.dev/skills/jtprogru/bear-skills/obsidian-refactor-lecture"><img src="https://agentmods.dev/badge/skills/jtprogru/bear-skills/obsidian-refactor-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/jtprogru/bear-skills/obsidian-refactor-lecture"><img src="https://agentmods.dev/badge/skills/jtprogru/bear-skills/obsidian-refactor-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 | $0.00174 | $0.02353 |
| Opus 5 | $0.00087 | $0.01177 |
| Sonnet 5 | $0.00035 | $0.00471 |
| Haiku 4.5 | $0.00017 | $0.00235 |
Grade A, and why
obsidian-refactor-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 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 — 205 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Обзор
Скилл превращает большой конспект лекции в структурированный граф знаний:
- оригинальная лекция становится "оглавлением" — разделы заменяются кратким резюме +
[[wikilink]]; - извлечённые концепты создаются как отдельные заметки с именем
<Дисциплина> – <Концепт>.md; - дисциплинарный MOC обновляется ссылками на новые заметки.
Лимит: не более 3 конспектов за один запуск. Если пользователь указал больше — спроси, какие три обработать сейчас, остальные — следующим запуском.
Базовые правила
Структура хранилища, таксономия тегов, frontmatter, имена файлов — в .agents/rules/:
vault-struct.md, tags.md (раздел «Структурные теги»), note-types-frontmatter.md, file-naming.md.
Формат конспекта лекции
Файл лекции следует паттерну Lecture – <Дисциплина> – <Дата> – <Тема>.md и содержит:
---
aliases: [...]
tags:
- lecture
discipline: "[[<Дисциплина>]]" # ссылка на дисциплинарный MOC в 02. Сферы/04. Образование/МТИ/Предметы/
up:
- "[[<Дисциплина>]]"
down:
- "[[...]]" # заметки, уже выделенные из этой лекции
links: []
other: []
date: "[[YYYY-MM-DD]]"
---
Алгоритм обработки
Шаг 1. Прочитай и определи кандидатов
Критерии «выделять / оставить» — навык /knowledge-structures (раздел «Когда выделять раздел в отдельную заметку»). Особенность лекций: Q&A-блоки оставляй в лекции как есть; выноси только если ответ — развёрнутый концепт ≥10 строк.
Шаг 2. Составь план и покажи пользователю
Протокол план → подтверждение → действие — workflows.md. Формат:
Лекция: [[Lecture – ВышМат – 2025-11-20 – Алгебра матриц]]
Дисциплина: [[ВышМат]]
Извлечь в 03. Ресурсы/04. Заметки/ (атомарные факты):
1. [[ВышМат – Транспонированная матрица]] → #thought + #lecture
2. [[ВышМат – Определитель матрицы]] → #thought + #lecture
Извлечь в 00. Входящие/ (требуют дальнейшей обработки):
3. [[ВышМат – Операции над матрицами]] → сводная концептуальная заметка
4. [[ВышМат – Обратная матрица]] → требует связей с другими темами
Оставить в лекции (не атомарны / слишком контекстуальны):
- Вводный абзац о применении матриц
What ships with it
2 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.
- 10d ago First seen · 205 lines · 174 tokens per session scan A c7a7cd054aec
obsidian-refactor-lecture is a skill published in the GitHub repository jtprogru/bear-skills (1 stars, last pushed 22d ago), licensed MIT. It adds 174 tokens to every session and 2,353 once invoked, about $0.0009 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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