HR Screening

SkillAI & models

Screen inbound applications against role requirements. Filter, summarize, and route to the CAO.

Available today. Use it from your connected AI after setup.

Connect ahel once, and every AI you use reads what you have installed.

Then ask your AI: use the HR Screening skill

About this capability

The open-source company brain. Run your entire company with AI agents, skills, and a self-improving context.

What this skill tells your AI

The instructions your AI receives, as published by getnao/sylph in .claude/skills/hr-screening/SKILL.md and read by ahel’s review.

Screen inbound applications against role requirements. Filter, summarize, and route to the CAO.

MCP connectors

ConnectorPurpose
GmailRead applications, send screening responses
NotionUpdate candidate tracking board

Hard filters checklist

Before summarizing, check each application against these filters. If any are NOT met, mark as "filtered out" with the reason.

FilterCheck
LocationWithin required timezone range or willing to relocate (if specified)
Experience levelMeets minimum years / seniority for the role
Core skillsHas the must-have technical skills listed in the job description
LanguageMeets language requirements (English fluency for all roles)
AvailabilityCan start within the required timeframe
Work authorizationHas or can obtain work authorization (if applicable)

Process

  1. Read the job description - load the role requirements from hr/roles/
  2. Read all new applications - process the full batch
  3. Apply hard filters - check each application against the checklist above
  4. Summarize passing candidates - for each:
    • Name, current role, company
    • Years of relevant experience
    • Key matching skills (mapped to job requirements)
    • Notable strengths or concerns
    • Recommendation: strong yes / yes / maybe / no
  5. Route to the CAO - save the screening summary to hr/_drafts/YYYY-MM-DD_screening-[role].md

Summary format

## [Candidate Name]
- **Current**: [role] at [company]
- **Experience**: [X years relevant]
- **Key skills**: [skill 1, skill 2, skill 3]
- **Strengths**: [brief]
- **Concerns**: [brief or "none"]
- **Recommendation**: [strong yes / yes / maybe / no]

Guardrails

  • No name-based inference of nationality, ethnicity, or gender - evaluate skills and experience only
  • No age inference from graduation dates
  • Never reject automatically - flag as "filtered out" with reason; the CAO makes final calls
  • No outreach to candidates - screening only, no communication
  • Keep all candidate data in hr/ folder only - never copy to other locations
  • PII handling - do not include candidate emails or phone numbers in the summary

Self-improvement

After the CAO reviews a screening batch:

  1. If the CAO overrides a recommendation (promotes a "maybe" to "yes" or rejects a "yes"), note why in hr/_insights.md
  2. If her overrides reveal a pattern (e.g. "values startup experience over years of experience", "cares more about portfolio than pedigree"), add it to the Hard filters checklist or create a new soft-signal section
  3. If the summary format wasn't useful - too long, missing context, wrong emphasis - update the Summary format section
  4. If a screening summary was particularly well-calibrated, save it to hr/_examples/ as a reference (with PII removed)

Signals

GitHub stars
196
Forks
58
Last commit
May 2026
Advanced
Catalog kind
skill
Gateway key
hr-screening
Source
github.com/getnao/sylph