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Agent skill

Expert Interview Generator

by aipoch in aipoch/medical-research-skills

Generates a full expert interview article including introduction, Q&A body, and summary based on interview questions and expert background.

MITAuto-check passedBusiness, Finance & HR

Install Expert Interview Generator

skills CLI
$ npx skills add aipoch/medical-research-skills --skill expert-interview-generator -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install aipoch/medical-research-skills expert-interview-generator --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/aipoch/medical-research-skills.git skills-src && mkdir -p .claude/skills && cp -r skills-src/scientific-skills/Other/expert-interview-generator .claude/skills/expert-interview-generator && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
expert-interview-generator
GitHub stars
2k
Token cost
~1.7k tokens
SKILL.md length
790 words
Files
4 (incl. scripts, references)
Skills in repo
567
Repo updated
First seen
Licence
MIT

At a glance

Generates a full expert interview article including introduction, Q&A body, and summary based on interview questions and expert background.

  • Works in 5 steps: Generate Expert Introduction → Generate Q&A Body → Generate Preface → …
  • You have interview questions and an expert profile and need a polished article
  • SKILL.md covers When to Use, Key Features, Dependencies and Example Usage, plus 9 more sections
  • Runs Python scripts from its folder; calls python

What it does

Expert Interview Generator is an agent skill from aipoch/medical-research-skills. Generates a full expert interview article including introduction, Q&A body, and summary based on interview questions and expert background. Use when you have interview questions and an expert profile and need a polished article.

Its SKILL.md is about 1.7k tokens, which your agent loads only when the skill is triggered. The skill folder holds 5 other files, including scripts and reference files (for example `expert-interview-generator_audit_result_v2.json`, `references/prompts.md` and `scripts/flow.py`).

It sits in Business, Finance & HR, covering Interview preparation. The repository describes itself as: Hundreds of agent skills for medical research, including protocol design, data analysis, evidence insights, and academic writing. The licence is MIT.

When your agent uses it

  • You have interview questions and an expert profile and need a polished article
  • Tasks that involve Interview preparation

Example prompts

  • “Use the expert-interview-generator skill to generate a full expert interview article including introduction, Q&A body, and summary based on…”
  • “/expert-interview-generator”

Requirements

  • Python 3

Workflow steps

5 steps, taken from the step headings in SKILL.md.

  1. Generate Expert Introduction
  2. Generate Q&A Body
  3. Generate Preface
  4. Generate Summary
  5. Final Assembly

What it can do on your machine

Read from SKILL.md and the folder at commit 686e09d. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Ships 1 file in scripts/ (Python), which the agent can run.

    Shell commands in SKILL.md call:

    • python

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Expert Interview Generator loads about 1.7k tokens when it runs, and up to ~2.5k if it reads all its reference files. Until then it costs about 64 tokens; SKILL.md has 790 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~64
When it runs · the whole SKILL.md, loaded when a task matches
~1.7k
With references · SKILL.md plus every file in references/, read only if the agent opens them
~2.5k

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check passed

The automated check found no risky patterns in SKILL.md.

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); the scripts in this folder are not scanned.

SKILL.md

The full file from aipoch/medical-research-skills at commit 686e09d, republished under its MIT licence (© aipoch). 790 words, ~1,689 tokens.

Download SKILL.mdSave it as .claude/skills/expert-interview-generator/SKILL.md (or your agent's skills folder). This skill also uses 3 other files; get the full folder from GitHub.
name
expert-interview-generator
description
Generates a full expert interview article including introduction, Q&A body, and summary based on interview questions and expert background. Use when you have interview questions and an expert profile and need a polished article.
license
MIT
author
AIPOCH

Source: https://github.com/aipoch/medical-research-skills

Expert Interview Article Generator

This skill orchestrates the generation of a professional expert interview article, simulating a Dify workflow.

When to Use

  • Use this skill when the request matches its documented task boundary.
  • Use it when the user can provide the required inputs and expects a structured deliverable.
  • Prefer this skill for repeatable, checklist-driven execution rather than open-ended brainstorming.

Key Features

  • Scope-focused workflow aligned to: Generates a full expert interview article including introduction, Q&A body, and summary based on interview questions and expert background. Use when you have interview questions and an expert profile and need a polished article.
  • Packaged executable path(s): scripts/flow.py.
  • Reference material available in references/ for task-specific guidance.
  • Structured execution path designed to keep outputs consistent and reviewable.

Dependencies

  • Python: 3.10+. Repository baseline for current packaged skills.
  • Third-party packages: not explicitly version-pinned in this skill package. Add pinned versions if this skill needs stricter environment control.

Example Usage

bash
cd "20260316/scientific-skills/Others/expert-interview-generator"
python -m py_compile scripts/flow.py
python scripts/flow.py --help

Example run plan:

  1. Confirm the user input, output path, and any required config values.
  2. Edit the in-file CONFIG block or documented parameters if the script uses fixed settings.
  3. Run python scripts/flow.py with the validated inputs.
  4. Review the generated output and return the final artifact with any assumptions called out.

Implementation Details

See ## Workflow above for related details.

  • Execution model: validate the request, choose the packaged workflow, and produce a bounded deliverable.
  • Input controls: confirm the source files, scope limits, output format, and acceptance criteria before running any script.
  • Primary implementation surface: scripts/flow.py.
  • Reference guidance: references/ contains supporting rules, prompts, or checklists.
  • Parameters to clarify first: input path, output path, scope filters, thresholds, and any domain-specific constraints.
  • Output discipline: keep results reproducible, identify assumptions explicitly, and avoid undocumented side effects.

Inputs

  • background (Required): Expert profile (Name, Title, Affiliation, Research Direction, Achievements).
  • question (Required): List of interview questions.
  • title (Required): Article title.
  • text1 (Optional): Existing interview draft content.

Workflow

Step 1: Generate Expert Introduction

Use the Expert Introduction Prompt in references/prompts.md to generate the intro section. Input: background

Step 2: Generate Q&A Body

Determine which generation path to use based on text1:

  • Path A (With Draft): If text1 is provided (not empty), use the Body Generation (With Draft) Prompt in references/prompts.md.
    • Inputs: text1, question, background, title
  • Path B (No Draft): If text1 is empty, use the Body Generation (No Draft) Prompt in references/prompts.md.
    • Inputs: question, background, title

Constraint: The output must be approximately 2000 words, strictly following the Q&A format defined in the prompt.

Step 3: Generate Preface

Use the Preface Prompt in references/prompts.md to write a 150-word introduction. Inputs: Generated Body (from Step 2), title, background

Step 4: Generate Summary

Use the Summary Prompt in references/prompts.md to write a 150-word conclusion. Inputs: Generated Body (from Step 2), Generated Preface (from Step 3), background, title

Show full SKILL.md (330 more words)Show less
Step 5: Final Assembly

Combine the generated sections into a final Markdown article using the structure below. You may use scripts/flow.py to handle text processing if needed, or assemble manually.

Structure:

  1. Title: title
  2. Preface: (Result from Step 3)
  3. Expert Profile: (Result from Step 1)
  4. Interview Content: (Result from Step 2)
  5. Summary: (Result from Step 4)

When Not to Use

  • Do not use this skill when the required source data, identifiers, files, or credentials are missing.
  • Do not use this skill when the user asks for fabricated results, unsupported claims, or out-of-scope conclusions.
  • Do not use this skill when a simpler direct answer is more appropriate than the documented workflow.

Required Inputs

  • A clearly specified task goal aligned with the documented scope.
  • All required files, identifiers, parameters, or environment variables before execution.
  • Any domain constraints, formatting requirements, and expected output destination if applicable.

Output Contract

  • Return a structured deliverable that is directly usable without reformatting.
  • If a file is produced, prefer a deterministic output name such as expert_interview_generator_result.md unless the skill documentation defines a better convention.
  • Include a short validation summary describing what was checked, what assumptions were made, and any remaining limitations.

Validation and Safety Rules

  • Validate required inputs before execution and stop early when mandatory fields or files are missing.
  • Do not fabricate measurements, references, findings, or conclusions that are not supported by the provided source material.
  • Emit a clear warning when credentials, privacy constraints, safety boundaries, or unsupported requests affect the result.
  • Keep the output safe, reproducible, and within the documented scope at all times.

Failure Handling

  • If validation fails, explain the exact missing field, file, or parameter and show the minimum fix required.
  • If an external dependency or script fails, surface the command path, likely cause, and the next recovery step.
  • If partial output is returned, label it clearly and identify which checks could not be completed.

Quick Validation

Run this minimal verification path before full execution when possible:

bash
python scripts/flow.py --help

Expected output format:

text
Result file: expert_interview_generator_result.md
Validation summary: PASS/FAIL with brief notes
Assumptions: explicit list if any

© aipoch, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

SKILL.md and 3 other files (scripts, references) in scientific-skills/Other/expert-interview-generator of aipoch/medical-research-skills.

  • SKILL.md
  • expert-interview-generator_audit_result_v2.json
  • references/prompts.md
  • scripts/flow.py

Open the folder on GitHubat commit 686e09d

Compare with similar skills

Expert Interview Generator next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Expert Interview Generator compared with similar skills
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Expert Interview Generator this skillaipoch/medical-research-skills2k—~1.7kAutomated safety check: PassMIT
Career-Ops Job Search Centercareer-ops-hq/career-ops74k—~3.3kAutomated safety check: PassMIT
Internship Project Preparation ToolLiuMengxuan04/shushu-internship-tool2.1k—~2.3kAutomated safety check: PassCustom licence
Job Application AssistantMadsLorentzen/ai-job-search45k1 repos~1.2kAutomated safety check: NotesMIT
Interview Coachnoamseg/interview-coach-skill2.3k—~3.7kAutomated safety check: PassMIT
Algo Senseikaranb192/algo-sensei284—~1.7kAutomated safety check: PassMIT

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Categories

Questions about Expert Interview Generator

What does Expert Interview Generator do?

Generates a full expert interview article including introduction, Q&A body, and summary based on interview questions and expert background. Expert Interview Generator is an agent skill from aipoch/medical-research-skills. Generates a full expert interview article including introduction, Q&A body, and summary based on interview questions and expert background.

When should I use Expert Interview Generator?

Expert Interview Generator fits situations like: you have interview questions and an expert profile and need a polished article; tasks that involve Interview preparation.

How do I install Expert Interview Generator in Claude Code?

Run `npx skills add aipoch/medical-research-skills --skill expert-interview-generator -a claude-code`. Or copy the skill folder (scientific-skills/Other/expert-interview-generator in aipoch/medical-research-skills) into .claude/skills/expert-interview-generator in your project. Claude Code loads it when a task matches its description.

How do I install Expert Interview Generator in Codex?

Run `npx skills add aipoch/medical-research-skills --skill expert-interview-generator -a codex`. Or copy the skill folder (scientific-skills/Other/expert-interview-generator in aipoch/medical-research-skills) into .agents/skills/expert-interview-generator in your project. Codex loads it when a task matches its description.

Can I use Expert Interview Generator in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add aipoch/medical-research-skills --skill expert-interview-generator -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/expert-interview-generator, .gemini/skills/expert-interview-generator, .github/skills/expert-interview-generator and .opencode/skills/expert-interview-generator in your project.

What does Expert Interview Generator need to run?

Going by SKILL.md and its folder, Expert Interview Generator needs Python for the scripts in its folder and the command-line tools its instructions call (python). Our summary lists: Python 3.

Does Expert Interview Generator access the network?

SKILL.md contains no URLs. Any network use would come from the scripts or tools the agent runs. This is read from the text; nothing was executed.

Is Expert Interview Generator safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. The check reads SKILL.md only: the scripts in the folder are not scanned, so read them before running anything.

What licence does Expert Interview Generator use?

Expert Interview Generator is published under the MIT licence (declared in SKILL.md). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Expert Interview Generator use?

About 1.7k tokens (SKILL.md is roughly 6.8k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full. Its references folder adds about 815 tokens, read only when the agent opens those files.

What are the alternatives to Expert Interview Generator?

Skills that share tags, products or a category with Expert Interview Generator: Career-Ops Job Search Center (career-ops-hq/career-ops, 74k stars), Internship Project Preparation Tool (LiuMengxuan04/shushu-internship-tool, 2.1k stars), Job Application Assistant (MadsLorentzen/ai-job-search, 45k stars) and Interview Coach (noamseg/interview-coach-skill, 2.3k stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Expert Interview Generator?

aipoch (a GitHub organization) maintains it in aipoch/medical-research-skills, which has 1,974 GitHub stars. The repository holds 567 skills in this directory. The repository was last updated on September 17, 2026.

Source: aipoch/medical-research-skills on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.