WorkorAI

The problem

Recruiting platforms often rely on opaque black-box scores that hide why a candidate is actually a fit. For job seekers, navigating fragmented application portals and tracking interview status across multiple roles is time-consuming and inefficient.

What it does

• Searches and ranks candidates using white-box evidence including verified skills and interview Q&A transcripts.
• Manages the full job lifecycle from drafting vacancies with AI-assisted parsing to final hiring.
• Automates candidate workflows for finding jobs, tracking invitations, and applying to roles based on interview readiness.
• Handles secure MCP credential management for both employers and candidates without exposing plain-text keys.
• Generates comparative reviews of shortlists backed by real interview evidence rather than just resume keywords.

Frameworks & tools

WorkorAI MCP server, Node.js, and credential-store.mjs for local secret management.

Why this beats prompting it yourself

This skill implements complex multi-step recipes for vacancy creation and tiered candidate ranking that generic prompts cannot replicate. It handles state-dependent logic like contact gating for shortlisted applicants and idempotent job application guards.

Use cases

• Find and invite top-tier developers for a specific vacancy based on proven interview performance.
• Review a hiring funnel and move qualified applicants to the SHORTLISTED status to unlock contact details.
• Search for open jobs as a candidate and manage saved roles and pending invitations.
• Synchronize job drafts and recover from submission timeouts using state-aware tool calls.

Known limitations

Candidate contact information is restricted and only becomes visible once an applicant's status is set to SHORTLISTED or HIRED.