An intelligent recruitment agent that automates resume screening, candidate ranking, and the creation of customized interview guides based on specific job descriptions.
Install & Download
1. ClawHub CLI
The fastest way to install a skill directly from the registry.
npx clawhub@latest install easy-recruitment
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 easy-recruitment 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 Recruitment Assistant?
The Recruitment Assistant is a high-performance skill designed for the Openclaw Skills ecosystem to transform how teams handle hiring workflows. It functions as a localized AI recruiter that parses Job Descriptions (JD) to extract core requirements and then evaluates candidate resumes against those criteria. Unlike cloud-based platforms, this skill operates locally on your machine, ensuring that sensitive candidate data remains private while providing professional-grade analysis and ranking.
By leveraging advanced LLM capabilities, the skill doesn't just look for keywords; it understands project complexity, experience relevance, and technical depth. It synthesizes this information into comprehensive reports that help hiring managers move from a pile of resumes to a shortlist of high-potential candidates in minutes rather than hours.
Recruitment Assistant Use Cases
- Batch screening hundreds of resumes across multiple job openings to identify top talent quickly.
- Preparing detailed interview questions tailored to a specific candidate's resume and the recruiter's personal interviewing style.
- Re-ranking a pool of applicants instantly after updating or refining a Job Description.
- Conducting deep-dive technical gap analyses between a candidate's background and the required tech stack.
How Recruitment Assistant Works
- The agent identifies a structured job folder containing a JD.txt file and associated resume files in various formats like PDF or DOCX.
- It parses the JD to establish a weighted scoring baseline consisting of hard requirements, core skills, soft skills, and bonus qualifications.
- The skill performs a local batch analysis of all resumes, extracting contact info, work history, and quantifiable project achievements.
- A multi-dimensional scoring algorithm ranks candidates on a 100-point scale, categorizing them into Strong Recommend, Suggest Consider, or Low Match.
- The system generates a final report including a ranking table, risk assessments for each candidate, and a customized list of behavioral and technical questions.
Recruitment Assistant Setup
To begin using this skill within your Openclaw Skills environment, organize your files as follows:
- Create a root directory named
jobs/. - Inside
jobs/, create a folder for each position using the formatPositionName-Level/(e.g.,Backend-Senior/). - Place a
JD.txtfile inside the position folder describing the job requirements. - Drop all candidate resumes (PDF, DOCX, TXT, or HTML) into the same position folder.
- (Optional) Create a
personalprefer.txtin the rootjobs/folder to define your interviewing persona and specific traits you value across all roles.
Recruitment Assistant Data Schema & Taxonomy
The Recruitment Assistant organizes recruitment data using a transparent folder-based taxonomy:
| File/Folder | Purpose | Requirement |
|---|---|---|
jobs/ |
The root workspace for the recruitment skill | Mandatory |
[Job-Name]/JD.txt |
Defines the evaluation criteria and technical requirements | Mandatory |
[Job-Name]/*.pdf |
Raw candidate resumes in multiple supported formats | Mandatory |
personalprefer.txt |
Global configuration for interviewer personality and focus | Optional |
Report.html/md |
The final output containing rankings and interview guides | Generated |
Recruitment Assistant Advanced Features
- Personalized Interview Persona: Uses a global preference file to align generated questions with the interviewer's unique style and organizational culture.
- Local-First Privacy: All resume parsing and scoring occurs locally, ensuring no candidate data is uploaded to external third-party services.
- STAR Method Questioning: Automatically designs interview questions using the Situation, Task, Action, and Result framework based on specific resume highlights.
- Multi-Format Reporting: Generates professional-grade HTML reports with interactive tables or clean Markdown files for easy documentation sharing within Openclaw Skills.
SKILL.md
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