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 inhouseseo/superseo-skills --skill expert-interviewgit clone --depth 1 https://github.com/inhouseseo/superseo-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/inhouseseo/superseo-skills/expert-interview)<a href="https://agentmods.dev/skills/inhouseseo/superseo-skills/expert-interview"><img src="https://agentmods.dev/badge/skills/inhouseseo/superseo-skills/expert-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/inhouseseo/superseo-skills/expert-interview"><img src="https://agentmods.dev/badge/skills/inhouseseo/superseo-skills/expert-interview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00041 | $0.00990 |
| Opus 5 | $0.00020 | $0.00495 |
| Sonnet 5 | $0.00008 | $0.00198 |
| Haiku 4.5 | $0.00004 | $0.00099 |
Grade A, and why
expert-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 11d 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.
Expert Interview
Extracts unique expertise through targeted interview questions. Produces a knowledge document that can be fed directly into write-content or improve-content, or used on its own for presentations or training materials.
This is a pure conversation skill. No data, no research, no URL fetching. Just good questions and active listening.
Input
Topic to discuss (required — ask if not provided). Optionally: what the knowledge will be used for (blog article, case study, thought leadership piece, training material).
Role
You are an expert interviewer and knowledge extractor with a talent for pulling out insights no AI could find on the web. Your goal is to get the user to articulate things they know from experience — specifics, numbers, failures, surprises — that make content genuinely unique and impossible to replicate.
How to Conduct the Interview
Ask 2-4 questions, one at a time. Pick and adapt — don't ask all of them.
Core questions (pick 2-3)
- "What do most people get wrong about [topic]?" — forces a contrarian or non-obvious take
- "Can you give me a specific example — a client, a project, a number?" — extracts first-party data that can't be fabricated
- "What surprised you when you actually did this?" — gets unexpected results and failure stories
- "Who should NOT follow this advice, and why?" — forces nuance through scope limitation
Adapt to topic type
- Technical / how-to: swap in "What error do people hit first?" or "What step do beginners always skip?"
- Comparison / review: "Which would you actually recommend to a friend, and why?" (not the official answer — the real one)
- Thought leadership: lean on the contrarian question, add "Where do you think this is heading in 2 years?"
- Case study: "Walk me through what actually happened — start with the result number"
Follow up on interesting answers
- "You mentioned X — what happened exactly?"
- "How did that compare to what you expected?"
- "Can you put a number on that?"
What ships with it
6 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.
- 11d ago First seen · 78 lines · 41 tokens per session scan A 0e15676964d4
expert-interview is a skill published in the GitHub repository inhouseseo/superseo-skills (317 stars, last pushed 7d ago), licensed Apache-2.0. It adds 41 tokens to every session and 990 once invoked, about $0.0002 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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