Recruitment Manager
Paste the following prompt into your AI chat to install this skill:
To install this skill, please follow the guide at https://skillhub.cn/install/skillhub.md and use the skill ID: @user_fcba917f/recruitment-manager.
About this skill
Specific Pain Points in Recruitment
For hiring teams or engineers involved in hiring, common pain points include: disorganized candidate resumes in multiple formats (Word, PDF, images) that are time-consuming to parse; subjective matching analysis against a Job Description (JD) without structured dimensions; the effort needed to prepare targeted interview questions; a lack of a unified, professional format for candidate evaluation reports; and time-consuming drafting of professional communication emails (interview invitations, offer letters).
How the Skill Works: Core Capabilities & Workflow
This skill automates and structures this workflow through executable Python scripts. Its key capabilities are:
-
Intelligent Resume Parsing:
scripts/resume_parser.pyparses candidate resumes. It employs a layered strategy for PDFs, prioritizingpypdfium2.get_textpage()to extract hidden text layers from scanned documents (a v2.0 optimization), with fallbacks topdfplumberandPyPDF2, and OCR as a last resort. The output automatically extracts structured fields like contact info, education, work experience, skills, and projects. -
Structured Job-Candidate Matching:
Based on your provided JD, it scores matches (0-100) across multiple dimensions like skill alignment, experience level, and educational background. Output includes strength analysis, gap analysis, and risk indicators. -
Interview Question Generation & Reporting:
- Generates structured interview questions (with question content, evaluation criteria, and follow-up directions) covering technical, behavioral (STAR), and situational types.
- Consolidates all analyses into a candidate evaluation report. Reports are generated in HTML, PDF, and Word formats. The PDF report uses a professional pipeline from
scripts/pdf_pipeline/, with automatic detection and application of system Chinese fonts (e.g., SimHei) for high-quality typography.
-
Automated Recruitment Communication:
scripts/email_sender.pygenerates and sends various recruitment emails (interview invitations, follow-ups, offers, rejections). v2.1 added a "representative mode" (where contact ≠ candidate) and utility functions likebuild_smtp_config(). It supports SMTP configurations for services like 163, QQ, and Tencent Exmail for one-click sending.
Scope & Important Considerations
- Resume parsing accuracy is highly dependent on the quality of the source file; image-based resumes require OCR, which may have errors.
- The generated evaluation reports, matching analyses, and interview questions are designed as decision-support aids and structured inputs, not replacements for a recruiter's professional judgment.
- For the email function, SMTP details must be configured correctly. For personal mailboxes like 163 or QQ, you must use an app-specific authorization code, not the login password.
- When handling candidate personal data, ensure compliance with relevant data protection regulations (e.g., GDPR, PIPL).
- Technical dependencies such as
pypdfium2andreportlabmust be installed in the execution environment.
Use Cases
- As an HR, you receive numerous resumes in Word, PDF, and scanned image formats, and need to quickly extract structured data like names, experience, and skills for initial screening.
- After receiving several resumes, you need to compare them against a detailed Job Description (JD), quantitatively assess each candidate's skill and experience match, and generate a strength/weakness analysis.
- To prepare for an upcoming interview, you want to automatically generate targeted technical questions, behavioral interview questions (STAR), and situational simulation questions based on the candidate's resume and job requirements.
- You need to produce a professional PDF or Word evaluation report for a screened and interviewed candidate, including basic info, matching analysis, interview assessment, and hiring recommendations, for team discussion and records.
Best For
- HR specialists handling recruitment for multiple positions, who need to process resumes in various formats efficiently and produce standardized evaluation materials.
- Recruitment managers from business units who, before participating in interview decisions, require structured data and comparative candidate analyses to inform their judgment.
- Technical team leads who also handle hiring, wanting to quickly generate interview questions related to a role's tech stack and quantitatively assess a candidate's technical fit.
- Headhunting consultants who need to create professional evaluation reports for candidates and communicate with corporate HR in a structured manner.
Related Skills
AI agent tool for generating HTML proposals for client visit business scenarios, featuring deep research and dynamic mainline mapping.
Bid Proposal Verification Tool is used to verify the consistency between bid proposals and tender documents, checking table of contents, page numbers, attachments, and seals, based on Shibot Technology's bid data API.
An AI engine built on extensive bidding data to precisely search for tender projects and potential clients using natural language or structured criteria.
Automates bid document, response table, and material list generation from bid files and enterprise data using Shibuo Technology API.