entrevistador

Conduct guided conversational interviews and update Obsidian markdown interview documents.

Updated Apr 9, 2026

Search Tags:#agent #obsidian #data-collection #user-interview #entrevista #interview-flow

Ready to run

npx skills add https://github.com/eusouwillnunes/sistema-maestro --skill entrevistador

💬 Prompt for ChatGPT / Claude Chat▼

Please help me install this Agent Skill.
Skill: entrevistador
Source: https://github.com/eusouwillnunes/sistema-maestro/tree/main/skills/entrevistador
Command: npx skills add https://github.com/eusouwillnunes/sistema-maestro --skill entrevistador

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

The Entrevistador centralizes and structures conversational data collection, removing ambiguity and incomplete responses that block specialist agents in Obsidian-based projects.

Core Features & Use Cases

Guided one-question-at-a-time interviews: Conducts interviews interactively, always asking a single question and following up for depth when answers are superficial.
Stateful document updates: Reads interview markdown files, updates frontmatter status (em-andamento, concluida) and timestamps, and fills the "## Respostas" and "## Notas do Entrevistador" sections.
Coordination with project workflows: Lists pending interviews, resumes in-progress sessions, verifies related task unblock conditions, and reports completion to the Maestro or project manager.
Use case: Run when an agent requests needs_data or insufficient_data to collect missing brand or product information and unlock downstream tasks.

Quick Start

Start an interview session by asking: "Tenho entrevistas pendentes para este projeto? Por qual quer começar?"

Frequently Asked Questions about entrevistador

High-intent search queries and answers about installing and using this skill.

FAQPage Schema

How do I conduct guided user interviews to collect project data in Obsidian?▼

Guided user interviews in Obsidian are conducted one question at a time, following up for depth on superficial answers. The session reads and writes directly to interview markdown files, updating frontmatter status and populating response sections.

What is the best way to structure conversational data collection for specialist agents?▼

Conversational data collection is structured by centralizing responses into dedicated markdown files with frontmatter tracking. This removes ambiguity and ensures specialist agents receive fully clarified needs or product data to unblock downstream tasks.

Can I resume an in-progress interview if the session was interrupted?▼

Yes, in-progress interviews can be resumed. The system reads the existing markdown file, checks the frontmatter status, and continues the guided conversational flow exactly where the previous session left off.

How do I track the status of user interviews within a project workflow?▼

Interview status is tracked using frontmatter fields in the markdown files. The system automatically updates status to em-andamento or concluida, and records start and conclusion timestamps to coordinate with project workflows.

Does this interview flow work when an agent reports insufficient data for a task?▼

Yes, the interview flow is triggered when an agent reports insufficient data. It collects the missing brand or product information through guided questions and reports completion to the project manager to unblock tasks.

What are the limitations of using markdown files for user interview data collection?▼

This approach requires read and write access to the project's entrevistas index and individual markdown files. It is limited to Obsidian-based project workflows where agents require clarified user data to proceed.