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 AlekseiUL/sprut-agent-kit --skill deep-research-progit clone --depth 1 https://github.com/AlekseiUL/sprut-agent-kitWrote 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/alekseiul/sprut-agent-kit/deep-research-pro)<a href="https://agentmods.dev/skills/alekseiul/sprut-agent-kit/deep-research-pro"><img src="https://agentmods.dev/badge/skills/alekseiul/sprut-agent-kit/deep-research-pro.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 5.1 | $0.00024 | $0.01095 |
| Opus 5 | $0.00012 | $0.00548 |
| Sonnet 5 | $0.00005 | $0.00219 |
| Haiku 4.5 | $0.00002 | $0.00110 |
Grade A, and why
deep-research-pro 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 8d 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 — 137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Deep Research Pro 🔬
Мощный скилл глубокого ресёрча. Ищет по нескольким источникам, синтезирует и выдаёт отчёт с цитатами.
Когда использовать
- "Проведи ресёрч по теме X"
- "Глубокий анализ рынка / технологии / конкурентов"
- "Что сейчас происходит с X? Собери полную картину"
- "Исследуй тему для видео / поста"
- Любая задача где нужен СИСТЕМНЫЙ сбор информации из 10+ источников
НЕ использовать (есть инструменты лучше)
- Быстрый фактологический вопрос →
web_search - Что говорят на Reddit/X → скилл
last30days - Саммари одного видео/статьи → скилл
summarize
Workflow
Step 1: Уточнение (30 сек)
1-2 вопроса:
- "Цель - узнать для себя, принять решение или написать контент?"
- "Какой угол или глубина нужна?"
Если "просто исследуй" → дефолтные настройки.
Step 2: Планирование
Разбить тему на 3-5 подвопросов. Пример:
- Тема: "AI агенты для бизнеса"
- Какие основные платформы агентов существуют?
- Какие реальные кейсы применения в бизнесе?
- Сколько стоит внедрение?
- Какие ограничения и риски?
- Куда движется рынок в 2026?
Step 3: Мультиисточниковый поиск
Для КАЖДОГО подвопроса:
web_search(query="<ключевые слова подвопроса>", count=10)
Стратегия:
- 2-3 вариации ключевых слов на подвопрос
- Цель: 15-30 уникальных источников
- Приоритет: академические, официальные, авторитетные СМИ > блоги > форумы
- Для свежих тем: добавить
freshness="pm"(последний месяц)
Step 4: Глубокое чтение ключевых источников
Для 3-5 лучших URL:
web_fetch(url="<url>", maxChars=5000)
Не полагаться только на сниппеты поиска - читать полные статьи.
Step 5: Синтез и отчёт
# [Тема]: Отчёт Deep Research
*Дата: [дата] | Источников: [N] | Достоверность: [Высокая/Средняя/Низкая]*
## Краткое резюме
[3-5 предложений с ключевыми находками]
## 1. [Первая тема]
[Находки с цитатами]
- Ключевой факт ([Источник](url))
- Подтверждающие данные ([Источник](url))
## 2. [Вторая тема]
...
## Ключевые выводы
- [Вывод 1]
- [Вывод 2]
- [Вывод 3]
## Источники
1. [Название](url) — краткое описание
2. ...
## Методология
Исследовано [N] запросов. Проанализировано [M] источников.
Подвопросы: [список]
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.
- 8d ago First seen · 137 lines · 24 tokens per session scan A 78b78e4dcbf6
deep-research-pro is a skill published in the GitHub repository AlekseiUL/sprut-agent-kit (63 stars, last pushed 3mo ago), licensed MIT. It adds 24 tokens to every session and 1,095 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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