A specialized AI agent skill designed to conduct realistic, multi-phase LeetCode-style mock coding interviews.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install leetcode-mock-interviewer
2. Manual Installation
Copy the skill folder to one of these locations
~/.openclaw/skills/ <project>/skills/ Priority: Workspace > Local > Bundled
3. Prompt Installation
Copy this prompt to OpenClaw to install it automatically.
Help me install leetcode-mock-interviewer using Clawhub. If Clawhub is not installed, install it first (npm i -g clawhub).
Prefer to download?
Get the raw skill files in a ZIP archive.
What is LeetCode Mock Interviewer?
LeetCode Mock Interviewer is a professional simulation tool within the Openclaw Skills ecosystem that transforms your AI agent into a rigorous technical interviewer. Unlike standard coding tutors, this skill enforces a strict interview lifecycle, requiring candidates to verbalize their thought process, analyze complexity, and handle follow-up probes before writing a single line of code. It is designed to bridge the gap between solving problems in isolation and performing under pressure in a live interview setting.
By leveraging Openclaw Skills, developers can simulate various interview personas and difficulty levels, ensuring they are prepared for the high-stakes environment of Big Tech hiring. The skill focuses on communication, problem decomposition, and optimization paths, providing a structured experience that mirrors real-world engineering interviews.
LeetCode Mock Interviewer Use Cases
- Preparing for SWE, MLE, or AI Engineer technical rounds at top tech companies.
- Practicing verbal communication and problem decomposition during coding sessions.
- Improving time and space complexity analysis under interviewer scrutiny.
- Mastering the art of handling follow-up questions and edge-case identification.
- Refining interview performance through structured, scored feedback sessions using Openclaw Skills.
How LeetCode Mock Interviewer Works
- Setup Phase: The candidate defines their target role, difficulty level, problem topic, and whether hints are enabled.
- Problem Presentation: The interviewer provides a paraphrased LeetCode problem with constraints and examples without revealing the algorithm category.
- Interview Loop: The candidate must clarify the problem and state a brute-force approach before moving to optimization.
- Implementation: Once the strategy is approved, the candidate implements the solution in their language of choice.
- Follow-up Probes: The interviewer asks 3-5 deep-dive questions about the solution, tradeoffs, and potential edge cases.
- Feedback: The session concludes with a comprehensive report including scores for communication, problem-solving, and code quality.
LeetCode Mock Interviewer Setup
To begin using this tool within the Openclaw Skills framework, simply invoke the skill through your AI agent. You can initiate a session by asking the agent to start a mock interview or practice coding problems. Ensure your agent has access to the skill definition to follow the prescribed interview phases.
# Example prompt to trigger the skill if using a CLI agent
openclaw run leetcode-mock-interviewer
LeetCode Mock Interviewer Data Schema & Taxonomy
The skill organizes interview data and session parameters to ensure a consistent evaluation flow as part of the Openclaw Skills library:
| Data Point | Description |
|---|---|
| Role | Target position (e.g., SWE, MLE, AI Engineer) |
| Difficulty | Easy, Medium, or Hard calibration |
| Topic | Targeted algorithm category (e.g., Graphs, DP, Trees) |
| Interview Mode | Full mock, Follow-up only, or Rapid-fire warmup |
| Feedback Schema | Structured Markdown table with scores (1-5) and actionable suggestions |
| Problem Metadata | Constraints, examples, and hidden optimal complexity targets |
LeetCode Mock Interviewer Advanced Features
- Multi-mode simulations including 10-minute Rapid-fire warmups and targeted Follow-up sessions.
- Intelligent hint system that provides directional nudges rather than direct answers to preserve the challenge.
- Dynamic problem generation that paraphrases known challenges to prevent rote memorization.
- Strict verbal-first enforcement that prevents the candidate from jumping to code without a verified plan.
- Integration with Openclaw Skills reference files for detailed scoring rubrics and problem banks.
SKILL.md
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