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 nWave-ai/nWave --skill nw-jtbd-interviewsgit clone --depth 1 https://github.com/nWave-ai/nWaveWrote 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/nwave-ai/nwave/nw-jtbd-interviews)<a href="https://agentmods.dev/skills/nwave-ai/nwave/nw-jtbd-interviews"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-jtbd-interviews/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/nwave-ai/nwave/nw-jtbd-interviews"><img src="https://agentmods.dev/badge/skills/nwave-ai/nwave/nw-jtbd-interviews.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 | $0.00039 | $0.01422 |
| Opus 5.5 | $0.00016 | $0.00569 |
| Sonnet 5.5 | $0.00008 | $0.00284 |
| Haiku 4.5 | $0.00004 | $0.00142 |
Grade A, and why
nw-jtbd-interviews 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 — 145 lines — stays where its author put it; the contents beside it link to each section on GitHub.
JTBD Discovery Techniques
Use when conducting interactive discovery conversations to uncover jobs users are trying to accomplish. Adapted from Bob Moesta's Switch interview methodology for AI-guided feature discovery — the user describes their situation, Luna extracts forces and jobs through structured questioning.
Four Forces Extraction
Map user responses to Four Forces of Progress. Each force has characteristic language patterns to listen for and prompts to surface them.
Force 1: Push of Current Situation
User says: "I'm frustrated that..." | "It keeps breaking when..." | "I waste so much time on..." | "The last straw was when..."
Prompts:
- "What's your biggest frustration with how things work now?"
- "Tell me about the worst experience with the current approach."
- "What finally made this intolerable?"
- "What triggered this request — was there a specific incident?"
Force 2: Pull of New Solution
User says: "I want to be able to..." | "I imagine being able to..." | "My colleague said it could..." | "I need it to..."
Prompts:
- "What would the ideal outcome look like?"
- "What could you do that you can't do now?"
- "What specific capability excites you most about this?"
- "If this worked perfectly, what would change in your workflow?"
Force 3: Anxiety of New Solution
User says: "I'm worried that..." | "What if it doesn't..." | "I'm not sure I can learn..." | "The risk is..."
Prompts:
- "What concerns do you have about this new approach?"
- "What could go wrong that would make you regret this change?"
- "What would need to be true for you to feel safe adopting this?"
- "Is there anything that almost made you not request this?"
Force 4: Habit of Present
User says: "I'm used to..." | "At least with the old way, I know..." | "I've already invested..." | "My team is comfortable with..."
Prompts:
- "What do you like about the current approach, despite its problems?"
- "What feels safe or familiar about staying as-is?"
- "What would you have to give up or relearn?"
- "What workaround have you built that actually works well enough?"
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 · 145 lines · 39 tokens per session scan A 2888141ada8e
nw-jtbd-interviews is a skill published in the GitHub repository nWave-ai/nWave (620 stars, last pushed 1mo ago), licensed MIT. It adds 39 tokens to every session and 1,422 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 2026-09-03.
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