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 agentmods add skills/jtprogru/bear-skills/content-tutorial-structurenpx skills add jtprogru/bear-skills --skill content-tutorial-structuregit 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/content-tutorial-structure)<a href="https://agentmods.dev/skills/jtprogru/bear-skills/content-tutorial-structure"><img src="https://agentmods.dev/badge/skills/jtprogru/bear-skills/content-tutorial-structure.svg" alt="Measured on agentmods" 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 | $0.00115 | $0.01449 |
| Opus 5 | $0.00057 | $0.00724 |
| Sonnet 5 | $0.00023 | $0.00290 |
| Haiku 4.5 | $0.00012 | $0.00145 |
Grade A, and why
content-tutorial-structure 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 4d 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 — 148 lines — stays where its author put it; the contents beside it link to each section on GitHub.
content-tutorial-structure — Скелет технического туториала
Цель: дать читателю повторяемый путь от исходного состояния к цели. Не теория, не эссе — пошаговая инструкция, где каждый шаг проверяем.
Перед началом прочитай:
~/.claude/rules/content-voice.md~/.claude/rules/content-formatting.md— раздел про туториалы~/.claude/rules/sre-runbook-template.md— стиль исполняемых процедур (туториал близок к runbook'у по принципам команд)
Шаг 1. Определи scope
Спроси:
- цель туториала: «после прочтения читатель сможет <глагол + результат>»
- примеры: «развернуть Postgres-кластер с replication на 3 нодах», «настроить OAuth-логин через Google в Express-приложении», «измерить heap-аллокации в Go-сервисе»
- исходное состояние читателя: что у него есть, что предполагается
- финальное состояние: что должно работать в конце
- платформа / стек: версии, ОС, облако
Если цель размытая («туториал по k8s») — остановись и помоги вычленить конкретику. Туториал «по k8s» невозможен — возможен «развернуть minikube + deploy stateless API + expose via Ingress».
Шаг 2. Сложи скелет
# <Название: глагол + результат>
> **Цель:** после прохождения туториала ты сможешь _<конкретно>_.
> **Время:** ~X минут.
> **Уровень:** новичок / средний / продвинутый.
## Что понадобится
- <тулинг: версия>
- <тулинг: версия>
- <доступ: где взять>
- <облако/окружение, если применимо>
## Шаг 1. <Глагол + что>
<1-2 строки контекста: что делаем и зачем.>
```<lang>
<команда>
Проверка: <ожидаемый результат / команда, подтверждающая успех>
Шаг 2. <Глагол + что>
...
Шаг N. <Глагол + что>
...
Проверка финального состояния
<команда или сценарий, который проверяет, что всё работает end-to-end>
Troubleshooting
<Симптом 1>
Причина: ... Решение: ...
<Симптом 2>
...
Cleanup
<команды, чтобы откатить всё созданное — если читатель не хочет оставлять>
Что дальше
<2-3 ссылки: углубление темы, related туториалы, доки>
What ships with it
1 file 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.
- 4d ago First seen · 148 lines · 115 tokens per session scan A 43079974725d
content-tutorial-structure is a skill published in the GitHub repository jtprogru/bear-skills (1 stars, last pushed 17d ago), licensed MIT. It adds 115 tokens to every session and 1,449 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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