interview-user

interview-user is a skill for Claude Code from xdg/xdg-claude. It costs 55 tokens per session (4,530 once invoked), scanned A, original, Apache-2.0.

A structured interview process for developing an unfinished plan, design, or strategy through one question at a time, with the answers saved to disk.

In plain words
What is it for?
Thinking through a product idea, design, or strategy, exploring alternatives, and recording answers in a branching question tree.
Why use it?
It turns vague ideas into organized source material that can be resumed and reviewed without relying only on chat history.

Skill for Claude Code

Written for Claude Code: shipped in a Claude Code plugin.

Part of the interview-user plugin — 1 skill shipped together

Good fit Thinking through a product idea, design, or strategy, exploring alternatives, and recording answers in a branching question tree.

Compare 6 skills from other repositories ↓
Install with agentmods
npx agentmods add skills/xdg/xdg-claude/interview-user
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.

Any agent
npx skills add xdg/xdg-claude --skill interview-user
Clone the repo
git clone --depth 1 https://github.com/xdg/xdg-claude

Made for: Claude Code.

Or install interview-user, the plugin that ships this one along with the rest of its 1 skill.

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-user

README.md
[![agentmods](https://agentmods.dev/badge/skills/xdg/xdg-claude/interview-user.svg)](https://agentmods.dev/skills/xdg/xdg-claude/interview-user)
Your own site
<a href="https://agentmods.dev/skills/xdg/xdg-claude/interview-user"><img src="https://agentmods.dev/badge/skills/xdg/xdg-claude/interview-user.svg" alt="Measured on agentmods" height="20"></a>
Per session 55 Skills are progressive disclosure: only the name and description are preloaded; the body loads when the skill is used.
When invoked 4,530 The whole file, excluding the scripts and references it only reads on demand.
Security scan A 0 findings. A grade says what 26 rules found in the file — not that it is safe.
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 $0.00055 $0.04530
Opus 5 $0.00028 $0.02265
Sonnet 5 $0.00011 $0.00906
Haiku 4.5 $0.00006 $0.00453

Measured 7d ago against content hash 35ff5b7806de, method: parsed. Prices are Anthropic first-party input rates as of 2026-09-07, from the pricing page.

Security

Grade A, and why

interview-user 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.

interview-user/skills/interview-user/SKILL.md · 228 lines

How it starts

The opening of the file, as written. The whole thing — 228 lines — stays where its author put it; the contents beside it link to each section on GitHub.

interview-user

Elicit structure from an under-formed idea by asking one question at a time, recording each question and answer in a persistent tree on disk. The tree is the source of truth — not chat history.

This skill produces raw material. It does not produce the final artifact. When the user signals "we're done," hand off; do not slide into drafting the PRD/design doc/memo inline.

When to use

Trigger on phrases like: "interview me about X," "grill this idea," "help me think through Y," "let's poke holes in this plan," "I want to design X but haven't thought it through."

Do not use for: well-scoped implementation tasks, debugging, code review, or any case where the user already knows what they want and is asking for execution.

Core discipline

Write the question down before asking it. This is the single most important rule. The on-disk tree is updated first, then the question is posed to the user. Skipping this step collapses the skill into ordinary chat and forfeits the resumability and branch-coverage value.

One question at a time. Always. Multi-question messages overwhelm the user and produce shallow answers.

Preserve the user's coinages verbatim. When the user invents a term or lands a load-bearing phrasing -- "constraint-driven development," "one person's fix becomes everybody's fix" -- record those exact words in the Answer. Paraphrase only the connective tissue around them. The user's own vocabulary is the highest-value material the interview captures; a paraphrase of a coinage discards the thing worth keeping. This matters most for dictated input, which runs long and self-correcting with the gold buried in one specific clause -- read for the clause, keep it intact.

Recommend an answer only on convergent questions. A convergent question picks among known options, ratifies a default, or scopes something concrete; lead with a recommendation so the user can "yes / different / why?" A divergent question is generative -- values, success criteria, "what should X be" -- where a confident guess anchors the user before they've explored. Ask divergent questions raw. If the user stalls or asks "what do you think?", then offer a recommendation. See "Recommending answers" below.

Read the full file on GitHub · 228 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. 7d ago First seen · 228 lines · 55 tokens per session scan A 35ff5b7806de

Subscribe to this mod's changes

interview-user is a skill published in the GitHub repository xdg/xdg-claude (20 stars, last pushed 17d ago), licensed Apache-2.0. It adds 55 tokens to every session and 4,530 once invoked, about $0.0003 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 2026-08-30.

Related

Other skills, from other repositories

systematic-debugging

Use when encountering any bug, test failure, or unexpected behavior, before proposing fixes.

obra/superpowers · 21 tokens

local-ai-agents

Build local-first AI agents that run entirely on a developer workstation with Microsoft Foundry Local and Qwen function-calling models. Covers Small Language Models (SLMs), the OpenAI-compatible local endpoint, sandboxed local tools, local RAG with Chroma, local MCP servers, hybrid cloud/local routing, and the…

microsoft/ai-agents-for-beginners · 200 tokens

next-cache-components-adoption

Turn on Cache Components in a Next.js app and resolve the blocking routes it surfaces. Use when the user wants to enable, adopt, or migrate to Cache Components, flip the cacheComponents flag, work through a flood of blocking-prerender / instant validation errors, run the cache-components-instant-false codemod, or…

vercel/next.js · 95 tokens

next-partial-prefetching-adoption

Turn on Partial Prefetching in a Next.js app and work through the insights it surfaces. Use when the user wants to enable or adopt Partial Prefetching, flip the partialPrefetching flag, opt routes in with export const prefetch = 'partial', audit Link prefetch={true} behavior, preserve existing prefetched UI with…

vercel/next.js · 103 tokens

chronicle

Analyze Copilot session history for standup reports, usage tips, session search, and session reindexing. Use when the user asks for a standup, daily summary, usage tips, workflow recommendations, wants to search or find past sessions by keyword/file/PR, wants to reindex their session store, or asks about deleting…

microsoft/vscode · 72 tokens

babysit-pr

Babysit a GitHub pull request after creation by continuously polling review comments, CI checks/workflow runs, and mergeability state until the PR is merged/closed or user help is required. Diagnose failures, retry likely flaky failures up to 3 times, auto-fix/push branch-related issues when appropriate, and keep…

openai/codex · 114 tokens