interview

interview is a skill for Claude Code from hg-pyun/claude-code-marketplace. It costs 253 tokens per session (3,697 once invoked), scanned A, original, MIT.

An interactive requirements interview that turns a vague feature idea into a concrete specification by finding unclear decisions and asking the user targeted questions.

In plain words
What is it for?
Use it before building an unclear feature or starting an automated planning workflow when requirements need to be clarified with the user.
Why use it?
It prevents planning or implementation from relying on hidden assumptions, missing details, or unresolved choices.

Skill for Claude Code

Written for Claude Code: $ARGUMENTS substitution. Also seen: names the AskUserQuestion tool.

Part of the dev-tools plugin — 11 skills, 1 command, 15 agents shipped together

Install

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.

agentmods
npx agentmods add skills/hg-pyun/claude-code-marketplace/interview
Any agent
npx skills add hg-pyun/claude-code-marketplace --skill interview
Clone the repo
git clone --depth 1 https://github.com/hg-pyun/claude-code-marketplace

Made for: Claude Code.

Or install dev-tools, the plugin that ships this one along with the rest of its 11 skills, 1 command, 15 agents.

Wrote 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.

agentmods badge for interview

README.md
[![agentmods](https://agentmods.dev/badge/skills/hg-pyun/claude-code-marketplace/interview.svg)](https://agentmods.dev/skills/hg-pyun/claude-code-marketplace/interview)
Your own site
<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>
Per session 253 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 3,697 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. Scan, not verified.
Origin original No closer match found in the catalogue.
Token cost

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.

ModelPer sessionOnce 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

Measured 6d ago against content hash 2f378e4f5b03, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-06, from the pricing page.

Security

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.

plugins/dev-tools/skills/interview/SKILL.md · 126 lines

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 /autopilot or /ralplan, when the request is too ambiguous for the non-interactive Phase 1 intake (which stops PHASE1_AMBIGUOUS) — run this first to produce the spec.md it will reuse.
  • analyst or /autopilot Phase 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 /ralplan or /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 /autopilot or /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 /ralph or /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 analyst decomposition first — do NOT hand-roll the ambiguity analysis. analyst is 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 in analyst'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 assumption analyst labeled Inferred with 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 AskUserQuestion call (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. AskUserQuestion always 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 $ARGUMENTS or 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, default 0.2) 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.md with 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>

Read the full file on GitHub · 126 lines

Changes

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.

  1. 6d ago First seen · 126 lines · 253 tokens per session scan A 2f378e4f5b03

Subscribe to this mod's changes

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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