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 PaulRBerg/agent-skills --skill interview-megit clone --depth 1 https://github.com/PaulRBerg/agent-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/paulrberg/agent-skills/interview-me)<a href="https://agentmods.dev/skills/paulrberg/agent-skills/interview-me"><img src="https://agentmods.dev/badge/skills/paulrberg/agent-skills/interview-me/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/paulrberg/agent-skills/interview-me"><img src="https://agentmods.dev/badge/skills/paulrberg/agent-skills/interview-me.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 | $0.00056 | $0.00539 |
| Opus 5 | $0.00028 | $0.00269 |
| Sonnet 5 | $0.00011 | $0.00108 |
| Haiku 4.5 | $0.00006 | $0.00054 |
Grade A, and why
interview-me 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 9d 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 — 39 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Interview Me
This skill is coordination-exempt: skip the ai-coord gate for its declared work.
Clarify what the user wants through a focused, conversational interview without exhausting every possible branch.
Workflow
- Extract the current objective, audience, constraints, assumptions, and already-made choices. Investigate facts available from the conversation, codebase, or supplied evidence instead of asking for them.
- Ask exactly one concise question per turn in plain conversational language. Format every question turn as
### 💬 Question <N> — <topic>, followed by**🧭 Context**, optional**🎯 Recommended**, and**❓ Question**sections, with each label on its own line. Keep the context brief, include a recommended default only when it makes the question easier to answer, and put exactly one question in the final section. Choose the highest-leverage question whose answer could materially change the direction or next step. - Treat three to five questions as a soft target, not a quota or hard cap. Stop earlier when the direction is already clear. Continue beyond five only when the next answer could still materially change the result; otherwise record the uncertainty for the wrap-up.
- Favor intent, scope, success criteria, audience, and key tradeoffs. Follow the threads the user emphasizes instead of mechanically covering every interface, failure mode, operational concern, or other domain.
- Briefly acknowledge or synthesize an answer as
✅ Noted: <choice or implication>only when it advances the conversation. Do not use decision cards, progress counts, exhaustive checklists, repeated recaps, or a formal decision record. Do not reopen settled choices unless new evidence conflicts with them. - Finish immediately when the user asks to stop or when further questions would add little value. Return
### 🧭 Summary,### ✅ Key choices, optional### ❓ Open questions, and### 🏁 Next step. Keep the wrap-up concise and do not end with another question.
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.
- 9d ago First seen · 39 lines · 56 tokens per session scan A 45a0421fda17
interview-me is a skill published in the GitHub repository PaulRBerg/agent-skills (70 stars, last pushed today), licensed MIT. It adds 56 tokens to every session and 539 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 2026-08-30.
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