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Readme & install
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Installation
Preview and clipboard use veilstrat where the catalogue uses aiagentskills.
npx veilstrat add skill openclaw/skills --skill resume-screener-pro- _meta.json468 B
- SKILL.md9.5 KB
Overview
This skill is a four-stage, end-to-end recruiting assistant that runs resume screening, interview design, interview evaluation, and final recommendation. It combines Topgrading scorecards, performance-prediction techniques, and bias-control practices to produce data-driven hiring decisions. It is built for HR leaders, recruiters, and interviewers who need a structured, repeatable hiring process.
How this skill works
The skill ingests candidate resumes (PDF/DOCX/TXT) and the job description, extracts key information, and scores candidates against a defined scorecard. It then generates layered interview question sets using STAR and deeper probing, supports multi-role expert evaluation across defined dimensions, and produces a decision matrix for final recommendations. Outputs include ranked screening reports, tailored interview question lists, structured interview evaluation reports, and a clear hire/no-hire recommendation.
When to use it
- When you need to screen a large batch of resumes against a specific job description.
- When designing interview guides that target measurable outcomes and competencies.
- When you want structured, bias-mitigated interview questions and deep behavioral probes.
- When you need multi-dimensional interview evaluations from role-specific expert perspectives.
- When you require a final, data-backed recommendation for hiring decisions.
Best practices
- Define the scorecard (mission, 12-month outcomes, competencies) before reviewing resumes.
- Use STAR + layered probes to verify real behavior and underlying logic behind achievements.
- Combine resume scores and interview ratings for a composite decision, not one data point.
- Apply red/green signal checks to surface both strengths and risks explicitly.
- Document scoring rationale and evidence for defensible hiring decisions.
Example use cases
- HR leader screening 200 applicants for a senior product manager role and producing a ranked shortlist.
- Recruiter generating a candidate-specific onion-style interview guide to deeply verify key achievements.
- Interview panel using role-expert evaluation templates to score candidates consistently across technical and cultural dimensions.
- Hiring manager receiving a one-page evaluation report and a final recommendation based on resume + interview data.
- External recruiter assembling evidence-backed candidate profiles to present to clients.
FAQ
Provide candidate resumes (PDF/DOCX/TXT) and the job description or scorecard definition.
How does it control bias?
It enforces scorecard-first evaluation, uses structured STAR probes, and includes a bias-control reviewer in the expert evaluation mix.