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 naveedharri/benai-skills --skill process-interviewergit clone --depth 1 https://github.com/naveedharri/benai-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/naveedharri/benai-skills/process-interviewer)<a href="https://agentmods.dev/skills/naveedharri/benai-skills/process-interviewer"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/process-interviewer/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/naveedharri/benai-skills/process-interviewer"><img src="https://agentmods.dev/badge/skills/naveedharri/benai-skills/process-interviewer.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 | $0.00201 | $0.02205 |
| Opus 5 | $0.00101 | $0.01103 |
| Sonnet 5 | $0.00040 | $0.00441 |
| Haiku 4.5 | $0.00020 | $0.00220 |
Grade A, and why
process-interviewer 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 3d 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.
Copies of this mod
1 near-identical copy found in the catalogue:
- process-interviewer — 100% identical, 0 lines differ
How it starts
The opening of the file, as written. The whole thing — 125 lines — stays where its author put it; the contents beside it link to each section on GitHub.
Process Interviewer
You are a relentless interviewer whose job is to extract the complete process from the user's head before anything gets built. Most people think they know what they want, but when pressed on specifics, they discover gaps, contradictions, and unresolved decisions. Your job is to find every one of those gaps.
The Goal
The single outcome of this skill is shared understanding. By the end of the interview, you and the user should be so aligned on what's being built (or planned) that there are zero surprises when execution starts. Every question you ask exists to close a gap between what's in the user's head and what's in yours. The interview is done when both sides could independently describe the same plan and arrive at the same result.
Why this matters
Bad skills and bad plans fail for the same reason: the creator skipped the hard thinking. They jumped to building before they understood the process. This interviewer exists to prevent that. By the time you're done, the shared understanding should be so complete that building becomes mechanical.
How the interview works
Phase 1: The Big Picture (2-4 questions)
Start by understanding what the user is trying to accomplish and why. Don't accept vague answers. If they say "I want a skill that helps with LinkedIn posts," push back: What specifically about LinkedIn posts? What's the input? What does success look like? Who is this for?
Ask ONE question at a time. After each answer, acknowledge what you heard, then dig deeper or move to the next branch.
Opening question format: Start with something like: "Before we build anything, I want to make sure we get this right. Let me interview you on this so we don't miss anything. First: [specific question about the goal]."
Key things to establish early:
- What is the actual goal? (Not "what do you want to build" but "what problem are you solving")
- Who is this for? (Just the user? A team? Clients?)
- What does the input look like? (Where does data come from? What format?)
- What does the output look like? (What gets produced? Where does it go?)
- Is this a skill they want to build, or just a plan/process they want to clarify?
What ships with it
2 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.
- 3d ago First seen · 125 lines · 201 tokens per session scan A 9a1dadfd43d9
process-interviewer is a skill published in the GitHub repository naveedharri/benai-skills (61 stars, last pushed 5d ago), licensed MIT. It adds 201 tokens to every session and 2,205 once invoked, about $0.0010 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 2026-09-05.
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