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 akovalion/paranoid-qa --skill interviewgit clone --depth 1 https://github.com/akovalion/paranoid-qaWrote 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/akovalion/paranoid-qa/interview)<a href="https://agentmods.dev/skills/akovalion/paranoid-qa/interview"><img src="https://agentmods.dev/badge/skills/akovalion/paranoid-qa/interview/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/akovalion/paranoid-qa/interview"><img src="https://agentmods.dev/badge/skills/akovalion/paranoid-qa/interview.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 | $0.00052 | $0.00791 |
| Opus 5.5 | $0.00021 | $0.00316 |
| Sonnet 5.5 | $0.00010 | $0.00158 |
| Haiku 4.5 | $0.00005 | $0.00079 |
Grade A, and why
interview 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 — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview: сбор требований через вопросы
Помоги пользователю структурировать неформальное описание задачи в полные требования, готовые к передаче в скиллы test-cases или testing.
Когда применять
- Задача описана устно или общими словами, без тикета
- Нет AC, нет макетов, нет чёткого scope
- Пользователь сам не уверен, что именно тестировать/автоматизировать
Если задача уже из трекера (Jira и т.п.) с полным описанием — этот скилл не нужен: собери контекст прямо из тикета (через MCP трекера: описание, комментарии, вложения, связанные задачи) и передай в test-cases.
Процесс
Раунд 1: scope и контекст. Задай 3-4 вопроса через AskUserQuestion:
- Что именно проверяем (фича, страница, элемент)
- Где это живёт (URL, экран, путь в навигации)
- Тип задачи (новая функциональность / регресс / баг)
- Платформы (desktop / mobile / оба)
Раунд 2: поведение и AC. На основе ответов 1-го раунда:
- Happy path — какое поведение считается корректным
- Edge cases — что важно проверить из негативных сценариев
- Состояния UI (loading, error, empty, disabled) — если применимо
- Интеграции — есть ли API / внешние сервисы
Раунд 3: уточнения по оставшимся пробелам. Только если после 1-2 раундов остались критичные пробелы. Группируй связанные вопросы.
Максимум 3 раунда. Если требования всё ещё неполные — зафиксируй пробелы как «Вопросы для аналитика/PM» и работай с тем, что есть.
Формат вывода
После завершения опроса собери структурированный summary:
# Требования: <короткое название задачи>
## Контекст
- Тип: <новая фича / регресс / баг>
- Платформы: <desktop / mobile / оба>
- URL / расположение: <…>
## Scope
<что именно проверяем, кратко>
## Acceptance Criteria
- <AC 1>
- <AC 2>
## Сценарии
**Happy path:** <описание>
**Edge cases:**
- <case 1>
- <case 2>
## Интеграции
<API, внешние сервисы — если есть>
## Открытые вопросы для аналитика/PM
- <вопрос 1>
Сохрани summary в md-файл (например, requirements_<task_name>.md в текущей рабочей директории) и предложи пользователю передать его в test-cases или testing.
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 · 78 lines · 52 tokens per session scan A 52f33ee14b14
interview is a skill published in the GitHub repository akovalion/paranoid-qa (16 stars, last pushed 3d ago), licensed MIT. It adds 52 tokens to every session and 791 once invoked, about $0.0002 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 2026-08-30.
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