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- Bityoungjae
- Marketplace
- Project Interview
project-interview_skill
- Shell
6
GitHub Stars
3
Bundled Files
2 months ago
Catalog Refreshed
4 months ago
First Indexed
Readme & install
Copy the install command, review bundled files from the catalogue, and read any extended description pulled from the listing source.
Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill bityoungjae/marketplace --skill project-interview- conversation-flow.md18.3 KB
- interview-data-template.md3.7 KB
- SKILL.md1.3 KB
Overview
This skill provides guided resources and a conversational approach for conducting interviews that produce learner profiles. It helps an agent gather motivations, prior knowledge, and desired outcomes so a clear persona.md and interview record can be produced. The focus is practical: capture usable facts and preferences through natural, counselor-style questions.
How this skill works
The skill supplies conversation examples and a data-template to record responses. During an interview, the agent uses open questions, listens for cues about level and motivation, and asks targeted follow-ups when details are missing. Once enough information is gathered, the agent summarizes the profile for confirmation and stores the record and persona files.
When to use it
- Initializing a new learning project to build a personalized learner persona
- Collecting background and goals before generating tailored learning materials
- Creating a persistent interview record for future project iterations
- Onboarding learners who prefer conversational, human-centered questioning
Best practices
- Begin with broad, open-ended questions to reveal goals and context
- Listen for implicit clues about experience and adjust follow-ups accordingly
- Use the interview-data template to capture answers verbatim and consistently
- Show a brief persona summary mid-interview to confirm understanding
- Keep tone empathetic and avoid rigid, checklist-style questioning
Example use cases
- A project-interviewer agent runs /init to create persona.md for a new learner
- Converting a casual chat into a structured interview-data.md for team review
- Refining a learner’s desired deliverable (style, length, format) before scaffolding content
- Updating an existing persona after a follow-up conversation or changed goals
FAQ
You should produce persona.md, interview-data.md, and project metadata suitable for the caller to consume.
How do I handle missing or vague answers?
Ask natural, targeted follow-ups, reflect what you heard, and present a tentative summary for correction.