Install
openclaw skills install hiremateAI recruiting assistant for generating job descriptions, resume screening criteria, interview questions, candidate scoring, match analysis, salary reports, and interview evaluations. Use when the user asks to: create a job description (JD), write a job posting, generate interview questions, screen resumes, evaluate candidates, analyze candidate-job fit, check salary benchmarks/compensation data, create interview scorecards, or build recruiting workflows. Supports both free features (JD generation, screening criteria, interview questions) and premium features (resume scoring, candidate matching, salary reports, interview evaluations). Triggers on phrases like "job description", "JD", "招聘", "interview questions", "screen resume", "candidate match", "salary report", "compensation", "interview evaluation", "hire", "recruit".
openclaw skills install hiremateComplete recruiting toolkit: generate JDs, screen resumes, create interview questions, score candidates, analyze matches, benchmark salaries, and evaluate interviews.
python3 <skill_dir>/scripts/generate_jd.py \
--role <role_template> --company <name> --seniority <level> \
--location <loc> --language <lang> --framework <fw> \
--industry <ind> --years <n> [--output file.md]
Roles: software_engineer, product_manager, data_scientist, ux_designer, marketing_manager, sales_representative
python3 <skill_dir>/scripts/generate_screening_criteria.py \
--role <role> --years <n> --languages "Py,Go" \
--frameworks "Django" --industry <ind> [--format json]
python3 <skill_dir>/scripts/generate_interview_questions.py \
--role <role> --level <junior|mid|senior|all> \
--num-tech 5 --num-behavioral 3 [--seed <n> for reproducibility]
python3 <skill_dir>/scripts/score_resume.py \
--resume "<text>" --keywords skill1 skill2 skill3 \
--min-years 3 --education <bachelors|masters|phd>
Resume can be text or @file_path. Returns weighted score (keyword 40%, experience 25%, education 15%, tech skills 20%).
python3 <skill_dir>/scripts/match_candidate.py \
--candidate-skills a b c --candidate-years 5 \
--candidate-edu bachelors --candidate-location "SF" \
--job-skills a b d --job-min-years 3 \
--job-role software_engineer --job-seniority mid
Returns skill overlap, experience gap, education match, and salary context.
python3 <skill_dir>/scripts/salary_report.py \
--role <role> --region <us|europe|uk|asia_pacific> \
--seniority <junior|mid|senior|staff>
Includes regional comparisons and market notes.
python3 <skill_dir>/scripts/interview_evaluation.py \
--candidate "Name" --role "Role" \
--technical 85 --problem-solving 80 --communication 75 \
--cultural-fit 90 --experience 80 --learning 85 \
--strengths "Strong X" "Great Y" \
--concerns "Needs Z"
Weighted scoring: technical 30%, problem-solving 20%, communication 15%, cultural fit 15%, experience 10%, learning 10%.
references/jd_templates.json — JD templates for 6 role typesreferences/interview_questions_db.json — 50+ questions across 6 categoriesreferences/salary_data.json — Global salary benchmarks (US, EU, UK, APAC)--format markdown (default) and --format json--output file.md to save to file instead of stdout--seed for reproducible interview question sets