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 agentmods add skills/hg-pyun/claude-code-marketplace/interviewnpx skills add hg-pyun/claude-code-marketplace --skill interviewgit clone --depth 1 https://github.com/hg-pyun/claude-code-marketplaceWrote 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/hg-pyun/claude-code-marketplace/interview)<a href="https://agentmods.dev/skills/hg-pyun/claude-code-marketplace/interview"><img src="https://agentmods.dev/badge/skills/hg-pyun/claude-code-marketplace/interview.svg" alt="Measured on agentmods" 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 | $0.00253 | $0.03697 |
| Opus 5 | $0.00127 | $0.01849 |
| Sonnet 5 | $0.00051 | $0.00739 |
| Haiku 4.5 | $0.00025 | $0.00370 |
Grade A, and why
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 6d 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 — 126 lines — stays where its author put it; the contents beside it link to each section on GitHub.
<Use_When>
- The user brings a fuzzy idea/feature/spec and wants the ambiguity pinned down into concrete requirements before planning or building.
- Before
/autopilotor/ralplan, when the request is too ambiguous for the non-interactive Phase 1 intake (which stopsPHASE1_AMBIGUOUS) — run this first to produce thespec.mdit will reuse. analystor/autopilotPhase 1 reported ambiguity above threshold and you want to close the gaps interactively rather than rewrite the idea by hand.- The user would rather be asked targeted questions with candidate answers than free-write a full spec.
- Trigger phrases (EN): "clarify this", "ask me what you need to build this", "interview me to nail down the requirements", "/interview".
- Trigger phrases (KO): "이거 애매한데 질문해서 정리해줘", "요구사항 명확히 해줘", "모호한 부분 짚어서 스펙으로 만들어줘". </Use_When>
<Do_Not_Use_When>
- The request is already unambiguous — skip clarification and go straight to
/ralplanor/autopilot. - The user wants to reach their OWN design decisions by being questioned, without being handed candidate answers or a finished spec — that is
buddy:socratic-interview(it keeps the pen in their hand; this skill resolves the ambiguity for them and emits an artifact). - The user just wants it built now ("그냥 만들어줘", "just build it") — go to
/autopilotor/ralph. - It is a simple factual lookup (an API signature, how a library behaves) — answer directly.
- A vetted plan already exists and only execution remains — use
/ralphor/team. </Do_Not_Use_When>
<Why_This_Exists>
The orchestration pipeline's Phase 1 intake is deliberately non-interactive: analyst scores the idea's ambiguity and, if it is above --threshold, /autopilot stops PHASE1_AMBIGUOUS and asks for a clearer idea or a pre-written spec.md — it will not interview in-loop. That leaves a gap: someone has to turn the fuzzy idea into that clearer spec. This skill is that step. It reuses the same analyst decomposition the pipeline already trusts, but adds the interactive resolution loop autopilot intentionally omits — asking the user to settle each ambiguity via AskUserQuestion with concrete options — and emits the exact spec.md the pipeline consumes. It is the front door to the pipeline for anything that starts vague. (For sharpening your own thinking without being handed answers, that is a different goal — see buddy:socratic-interview.)
</Why_This_Exists>
<Execution_Policy>
- Always run the
analystdecomposition first — do NOT hand-roll the ambiguity analysis.analystis the sanctioned engine for requirement decomposition, assumption classification (Stated/Inferred/Speculative), clarity scoring, and gap-with-clarifying-question output. - Resolve open points via
AskUserQuestion. Give each question 2–4 concrete candidate answers grounded inanalyst's assumptions/gaps and the codebase — the user picks rather than free-writing a spec. - A marked default is allowed here. Unlike
buddy:socratic-interview, this skill exists to resolve ambiguity, so it MAY mark a sensible default(Recommended)(place it first) where one clearly fits — e.g. an assumptionanalystlabeledInferredwith an obvious conventional default. Never fabricate a default where the choice is genuinely open; leave those to the user. - Batch independent clarifications into a single
AskUserQuestioncall (up to 4 questions). Sequence questions only when a later one genuinely depends on an earlier answer — then ask the blocking one first and re-carve the next from the answer. - Trust "Other" as the escape hatch.
AskUserQuestionalways offers free-text "Other"; do not fabricate a "none of these" option. - Prioritize by leverage. Resolve the ambiguities that most reduce aggregate ambiguity first (lowest-clarity dimensions, gaps blocking the most requirement units). Do NOT ask about points already settled by
$ARGUMENTSor the codebase. - Fold every answer into the spec as a concrete requirement, constraint, or acceptance criterion; record which prior assumption or gap it resolved.
- Stop at the gate. Stop when residual ambiguity is low (mirror the pipeline gate:
1 − weighted clarity≤--threshold, default0.2) or when the user chooses to stop. Never force completion. - Read-only on the user's code. Read to ground the questions; never modify source. The only sanctioned write is the clarified
spec.md. - Conduct the interview (question + option text) and write the spec in
$LANGUAGE; structural headers (## Goal,## Requirements,## Constraints,## Acceptance Criteria) stay English per repo convention — only their content is translated. - Output placement: slug context (
--slug=<slug>or an active hand-off slug) → write.dt-handoff/<slug>/spec.mdwith descriptor frontmatter and tell the user it is ready for/autopilot//ralplan. Free-standing (no slug) → present the spec inline; write a file only if the user names a path or accepts a derived slug (confirm once). Never auto-commit or open a PR. </Execution_Policy>
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.
- 6d ago First seen · 126 lines · 253 tokens per session scan A 2f378e4f5b03
interview is a skill published in the GitHub repository hg-pyun/claude-code-marketplace (2 stars, last pushed 2mo ago), licensed MIT. It adds 253 tokens to every session and 3,697 once invoked, about $0.0013 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 2026-08-31.
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