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 event4u-app/agent-config --skill discovery-interviewgit clone --depth 1 https://github.com/event4u-app/agent-configWrote 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/event4u-app/agent-config/discovery-interview)<a href="https://agentmods.dev/skills/event4u-app/agent-config/discovery-interview"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/discovery-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/event4u-app/agent-config/discovery-interview"><img src="https://agentmods.dev/badge/skills/event4u-app/agent-config/discovery-interview.svg" alt="Reviewed on agentmods" width="80" height="20"></a>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 | $0.01553 |
| Opus 5 | $0.00020 | $0.00776 |
| Sonnet 5 | $0.00008 | $0.00311 |
| Haiku 4.5 | $0.00004 | $0.00155 |
Grade A, and why
discovery-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 7d 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 — 163 lines — stays where its author put it; the contents beside it link to each section on GitHub.
discovery-interview
When to use
- A discovery slice has been framed (
customer-researchran), but the interview guide is still rough or untested. - A transcript exists and the team needs structured insight extraction, not narrative summary.
- An interview round produced surprising findings; a bias audit is needed before the team acts on them.
Do NOT use for the upstream framing of the discovery slice (frame
sentence, recruit criteria, JTBD focal job) — that is
customer-research. Do NOT use for
quantitative survey design or scale-bound research.
Cognition cluster
- Mental model 22 — Data-informed, not data-driven. Interview
data is signal at low N; treat it as evidence to reason with, not
a vote count. See
docs/contracts/mental-models.md§ 22. - Mental model 15 — Signal vs noise. A vivid quote from one
articulate user can swamp three muted but consistent signals;
frequency-rank by distinct people, never by quote count. See
mental-models.md§ 15. - Mental model 28 — Eisenhower matrix. Sort post-interview
insights into urgent / important quadrants so the team acts on
high-importance signals, not the loudest ones. See
mental-models.md§ 28. - Product context-spine slot. Read product for the focal job
- competitor names; do not re-derive these inside this skill.
See
context-spine.
- competitor names; do not re-derive these inside this skill.
See
Procedure
1. Build the question bank
- Anchor on the switch event from
customer-research. The first question is always "Walk me through the day you decided to ..." — never "would you ...". - Three layers:
- Past behaviour (what did you do? when? alternative considered?)
- Anxiety / habit (what feared in switching? what habit died?)
- Outcome (what changed for you? expected? unexpected?)
- Cap at 8 open questions per 45-min slot. Beyond that, the interview becomes a survey delivered in person.
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.
- 7d ago First seen · 163 lines · 41 tokens per session scan A a3ce7d32368d
discovery-interview is a skill published in the GitHub repository event4u-app/agent-config (10 stars, last pushed today), licensed MIT. It adds 41 tokens to every session and 1,553 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 2026-09-03.
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