An AI-driven mock interview assistant that utilizes real-time industry trends and resume analysis to prepare Product Managers for specific company hiring rounds.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install pm-interview-coach
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 pm-interview-coach 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 PM Interview Coach?
The PM Interview Coach is a professional-grade AI agent skill designed to simulate the high-pressure environment of a Product Manager interview. By acting as a senior PM from a target company, this skill provides a realistic training ground for candidates. It integrates advanced resume parsing with real-time data fetching to ensure that every session is tailored to the specific role and company culture.
Unlike generic interview bots, this Openclaw Skills implementation emphasizes technical depth and business logic. It focuses on the latest industry patterns by retrieving recent interview experiences from social platforms, ensuring users are prepared for the exact questions being asked in the current market.
PM Interview Coach Use Cases
- Preparing for competitive Product Manager roles at major tech firms like Tencent, ByteDance, or Meituan.
- Simulating specific interview stages, including initial business screenings, deep-dive technical rounds, and GM/HR evaluations.
- Practicing complex business case studies and data analysis scenarios under realistic time constraints.
- Generating high-quality, structured reference answers for resume-based questions to improve self-reflection and performance.
How PM Interview Coach Works
- The user initiates the session by providing their resume (PDF or text), the target company, the specific position, and the current interview round.
- The skill utilizes the Xiaohongshu MCP tool to search for and extract the most recent interview experiences (from the last month) related to that company and role.
- The agent analyzes the collected data and the user's resume to determine question weights, focusing 60% on open business cases and 30% on deep resume probing.
- A 45-minute structured interview is conducted, presenting one question at a time and providing brief feedback after each user response.
- Upon completion, the agent performs a quality-controlled evaluation, providing a multi-dimensional score and comprehensive reference answers exceeding 1500 words for technical questions.
PM Interview Coach Setup
To activate the coach within your environment, ensure you have the necessary MCP configurations for data fetching and trigger the skill using natural language commands.
# Trigger the coach with a command like:
openclaw run "Help me practice for my Tencent PM interview"
# Or provide the resume path directly:
openclaw call pm-interview-coach --resume="./my_resume.pdf" --company="Meituan" --round="1"
PM Interview Coach Data Schema & Taxonomy
The skill manages information through a strict lifecycle to maintain privacy and quality. Data is organized as follows:
| Data Type | Description | Persistence |
|---|---|---|
| Candidate Data | Resume content and JD requirements | Local Only |
| External Trends | Feed IDs and Xsec Tokens from Xiaohongshu | Session Only |
| Evaluation Metrics | Product thinking, data support, collaboration, and business logic | Session Only |
| Quality Gates | Word count (800-1500+), structural dimensions, and digital evidence | Output |
This Openclaw Skills tool ensures all sensitive resume data is processed locally and never uploaded to external servers.
PM Interview Coach Advanced Features
- Dynamic Trend Retrieval: Automatically pulls the latest real-world interview questions using MCP tool integrations.
- Strict Quality Control: Reference answers are passed through a 'quality gate' to ensure they include competitor analysis, data-driven evidence, and business closed-loops.
- Multi-Round Logic Adjustment: Automatically shifts interview focus based on whether the user is in a business-first round or a high-level GM round.
- Visual OCR Support: Uses AI vision models like MiniMax-VL-01 to recognize and process interview question screenshots from community posts.
SKILL.md
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