AI Recruiting Engine

PassAudited by ClawScan on May 1, 2026.

Overview

This is a coherent instruction-only recruiting framework; the main caution is that it may process candidate data and influence hiring decisions, not that it contains hidden code or credentials.

Installing this skill appears reasonable if you want recruiting templates and scorecards. Before using it with real candidates, make sure a human reviews all screening, scoring, outreach, offers, and rejections, and handle resumes and pipeline data according to your organization's privacy and employment-compliance rules.

Findings (2)

Artifact-based informational review of SKILL.md, metadata, install specs, static scan signals, and capability signals. ClawScan does not execute the skill or run runtime probes.

What this means

Users could over-rely on AI-generated scores or recommendations when making employment decisions.

Why it was flagged

This positions the agent as handling end-to-end recruiting decisions, including high-stakes hiring steps, even though the artifacts do not show hidden automation or tool access.

Skill content
You run the entire hiring lifecycle — from intake to offer acceptance — using structured frameworks, scoring rubrics, and data-driven decisions.
Recommendation

Use the skill as a drafting and structuring aid, require human recruiter or hiring-manager review, and follow applicable employment, privacy, and anti-discrimination policies.

What this means

Candidate personal information, interview notes, and AI-generated evaluations may be retained or reused if placed into pipeline files or conversation context.

Why it was flagged

The skill is intended to process resumes and maintain candidate pipeline information, which can include personal data and evaluative employment records.

Skill content
Resume Screening — 100-point scorecard across technical fit, impact evidence, and culture alignment; Pipeline Tracking — YAML-based candidate pipeline with weekly health metrics
Recommendation

Minimize candidate personal data, avoid unnecessary protected-class information, store any pipeline files securely, and define retention and access controls before using it with real candidates.