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 Desko77/cursor-1c-skills --skill v8unpack-cfgit clone --depth 1 https://github.com/Desko77/cursor-1c-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/desko77/cursor-1c-skills/v8unpack-cf)<a href="https://agentmods.dev/skills/desko77/cursor-1c-skills/v8unpack-cf"><img src="https://agentmods.dev/badge/skills/desko77/cursor-1c-skills/v8unpack-cf/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/desko77/cursor-1c-skills/v8unpack-cf"><img src="https://agentmods.dev/badge/skills/desko77/cursor-1c-skills/v8unpack-cf.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector warn
SkillSpector: 1 finding, up to medium
These are SkillSpector’s own severities. On a checked sample its high-severity flags on skills were ~96% false positives — a documented command, a public API, a “never do X” rule — so we show them as a caution to read, not a verdict. Why →
- medium analysis-evasion · line 1 Suspicious Unicode normalization or mixed-script contentFix: Review the flagged content for security risks. Ensure no credentials, secrets, or sensitive data are exposed.
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 | $0.00063 | $0.01685 |
| Opus 5 | $0.00032 | $0.00843 |
| Sonnet 5 | $0.00013 | $0.00337 |
| Haiku 4.5 | $0.00006 | $0.00169 |
Grade A, and why
v8unpack-cf 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 6d 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 — 152 lines — stays where its author put it; the contents beside it link to each section on GitHub.
v8unpack-cf - распаковка и сборка бинарных файлов 1С
Утилита saby v8unpack (Python) распаковывает CF/CFE/EPF файлы 1С в человекочитаемые исходники (JSON + BSL) с деревом метаданных - без платформы 1С.
Установка: pip install v8unpack (или dev-install из репозитория).
Команды
Распаковка (-E)
python -m v8unpack -E "<файл.cf>" "<папка_исходников>" --temp "<папка_temp>"
| Параметр | Описание |
|---|---|
<файл.cf> |
Путь к CF, CFE или EPF файлу |
<папка_исходников> |
Куда распаковать (создается автоматически) |
--temp <путь> |
Папка для промежуточных данных (не удаляется - для отладки) |
--processes N |
Количество потоков (по умолчанию cpu_count - 2) |
--descent XYYZZZ |
Режим версионирования расширений (суффикс версии конфигурации) |
--auto_include |
Динамическое оглавление из папки, а не из заголовка |
--prefix STR |
Префикс имен метаданных 1-го уровня |
Сборка (-B)
python -m v8unpack -B "<папка_исходников>" "<файл.cf>"
| Параметр | Описание |
|---|---|
<папка_исходников> |
Папка с распакованными исходниками |
<файл.cf> |
Путь к выходному CF/CFE/EPF файлу |
--index <path> |
JSON-файл оглавления (маппинг файлов по папкам) |
--version XYYZZ |
Версия режима совместимости (для расширений), напр. 80306 = 8.3.6 |
--descent XYYZZZ |
Суффикс версии конфигурации |
Индексация (-I)
python -m v8unpack -I "<папка_исходников>" --index index.json --core core
Генерирует/обновляет index.json - файл оглавления для раскладки исходников по подпапкам.
Пакетные операции (-EA, -BA, -IA)
python -m v8unpack -EA products.json # распаковать все продукты
python -m v8unpack -BA products.json # собрать все продукты
python -m v8unpack -BA products.json --index KEY # собрать конкретный продукт
Файл products.json описывает несколько продуктов с индивидуальными параметрами сборки.
Python API
import v8unpack
v8unpack.extract('d:/sample.cf', 'd:/src')
v8unpack.extract('d:/sample.cf', 'd:/src', temp_dir='d:/temp',
options={'descent': 4100200, 'auto_include': True})
v8unpack.build('d:/src', 'd:/repacked.cf')
v8unpack.build('d:/src', 'd:/repacked.cf', index='index.json',
options={'descent': 4100200, 'version': '80306'})
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.
- 6d ago First seen · 152 lines · 63 tokens per session scan A 1efe44d27bb2
v8unpack-cf is a skill published in the GitHub repository Desko77/cursor-1c-skills (55 stars, last pushed 8d ago), licensed MIT. It adds 63 tokens to every session and 1,685 once invoked, about $0.0003 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 2026-09-03.
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1c-epf-dump
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composing-1c-queries
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humanize-ai-text
A writing aid for rewriting text produced by language-model agents into a more natural human style. It keeps the original meaning, facts, numbers, and technical terms.
transcribe
A tool for turning video and audio recordings into written text, with optional speaker identification and video analysis.