algernon-interview

What This Skill Does

The algernon-interview skill transforms your OpenClaw agent into a high-caliber senior AI engineering interviewer. Rather than conducting a simple Q&A, this skill employs an adaptive questioning engine that mirrors the pressure and depth of real-world technical screenings. By leveraging your local database of study materials, the agent generates 8-10 targeted questions across four critical domains: fundamental concepts, practical application, architectural trade-offs, and production-level system design. The agent continuously monitors your technical depth; if you stumble on a concept, it probes for clarity, and if you excel, it increases the complexity of upcoming questions. The experience concludes with a professionalized, structured report, identifying specific knowledge gaps and providing a concrete study roadmap to improve your readiness for future interviews.

Installation

To integrate this skill into your environment, run the following command in your terminal: clawhub install openclaw/skills/skills/antoniovfranco/algernon-interview Ensure your ALGERNON_HOME path is correctly configured to point to your study database. If you wish to save your performance reports to your workspace, ensure the NOTION_CLI is installed and the NOTION_PAGE_ID environment variable is defined.

Use Cases

• Pre-Interview Prep: Simulate a high-pressure environment before actual company screenings to reduce anxiety and identify blind spots.
• Skill Verification: Use this after completing a course or reading a textbook to verify if you have truly internalized the material.
• Knowledge Auditing: Identify where your foundational theory meets its limits when applied to production-grade system design.

Example Prompts

1. "/algernon interview machine-learning-basics"
2. "simula uma entrevista técnica para mim sobre arquitetura de microserviços"
3. "quero praticar entrevista, você pode me fazer perguntas técnicas sobre react?"

Tips & Limitations

• Be Specific: The agent interprets brevity as a lack of mastery. When probed for details, expand on the 'why' and 'how' of your technical choices.
• Honesty: Treat the simulation as a mirror. If you don't know an answer, admitting it allows the agent to correctly calibrate the difficulty of subsequent questions.
• Database Dependency: The quality of the interview is limited by the quality of your study database. Ensure your cards include comprehensive tags for better question variety.