An AI-driven parsing engine that converts resume files into structured, developer-friendly JSON data.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install 51mee-resume-parse
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 51mee-resume-parse 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 51mee Resume Parser?
The 51mee Resume Parser is a technical skill designed to bridge the gap between unstructured candidate documents and automated recruitment workflows. By utilizing large language models, this skill can read files in formats like PDF, DOCX, and even images, extracting specific details such as work history, education, and contact information. As part of the ecosystem of Openclaw Skills, it provides a reliable way to standardize diverse resume formats into a single, queryable schema.
This skill is particularly useful for developers building HR tech solutions or AI agents that need to process applicant data at scale. It ensures high accuracy by using a strict TypeScript-based prompt architecture, which forces the model to return valid JSON while handling missing information gracefully with null values.
51mee Resume Parser Use Cases
- Automating candidate profile creation in Applicant Tracking Systems (ATS).
- Batch processing resumes from multiple formats into a centralized database.
- Extracting structured data from scanned resume images using OCR-backed LLM analysis.
- Standardizing date formats and contact details across international candidate pools.
How 51mee Resume Parser Works
- The user uploads a resume file (PDF, DOC, DOCX, JPG, or PNG) to the agent interface.
- The skill extracts the raw text content from the document, regardless of its original layout.
- The extracted text is injected into a specialized prompt template containing a ResumeInfo TypeScript interface.
- The LLM analyzes the text to map information to fields like work experience, project history, and professional skills.
- The skill validates and returns a clean JSON object containing the structured candidate data.
51mee Resume Parser Setup
To integrate this parser into your environment using Openclaw Skills, follow these configuration steps:
# Ensure your agent has access to the skill definition
# Load the 51mee-resume-parse skill into your configuration
# Configure your LLM provider (e.g., GPT-4o or similar) to handle JSON mode
Ensure that the file system permissions allow the agent to read uploaded documents in the supported formats.
51mee Resume Parser Data Schema & Taxonomy
The output is structured according to a strict TypeScript schema to ensure compatibility with downstream systems. Key data points include:
| Object | Fields | Description |
|---|---|---|
| Basic Info | name, gender, age, birthday | Core identity details |
| Work Experience | company, position, startDate, endDate | Array of career history |
| Education | school, major, degreeName | Array of academic history |
| Contact | phone, email, weixin | Structured contact methods |
| Metadata | keywords, awards, skills | Extracted highlights and tags |
Dates are consistently formatted as YYYY-MM-DD or YYYY.
51mee Resume Parser Advanced Features
- Multi-format support covering both text-based documents and image files.
- Strict TypeScript interface enforcement for reliable JSON responses.
- Automated date normalization and phone number cleaning.
- Intelligent handling of missing fields by returning explicit null values instead of hallucinations.
- Support for project-specific experience and salary expectations extraction.
SKILL.md
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