Hiring and interviewing

SkillMedia

Designs and runs hiring — role definition, sourcing, interview loop design, structured evaluation, and the decision itself. Use this to open a role, write a job description or scorecard, design an interview process, prepare interview questions, calibrate a hiring decision, or diagnose why a hiring process produces poor outcomes.

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 Hiring and interviewing skill

What this skill tells your AI

The instructions your AI receives, as published by cbrock84/headcount in plugins/people/skills/hiring-and-interviewing/SKILL.md and read by ahel’s review.

Define before sourcing

Write, before posting anything:

  • What this person will accomplish in their first year — outcomes, not responsibilities.
  • The three or four competencies that actually predict those outcomes.
  • What is genuinely required versus what is preferred. Long requirement lists are the most reliable way to shrink and homogenize a candidate pool, and most of the list is never used in the decision.
  • The bar, agreed by everyone on the loop, before the first interview.

Undefined roles produce interview loops where each interviewer evaluates against a private definition, and the decision goes to whoever argues hardest.

Design the loop

Each interview assesses different competencies, stated in advance. Overlapping interviews produce four opinions on the same thing and none on the rest.

  • Structured beats unstructured, consistently and by a wide margin. Same questions, same order, same rubric. Unstructured interviews mostly measure similarity to the interviewer.
  • Work samples predict best. A realistic exercise close to the actual job beats any amount of discussion about it. Keep it time-boxed and pay for anything substantial.
  • Behavioral questions about the past, with follow-ups for specifics: what was the situation, what did you do, what happened, what would you change. Hypotheticals measure articulacy.
  • Fewer, better interviews. Long loops lose good candidates and add little signal after the fourth conversation.

Evaluating

Interviewers write their assessment against the rubric before any discussion. Group discussion first produces convergence on the first confident opinion rather than an aggregation of independent ones.

Debrief on evidence: what did they say or do that supports this rating? "Culture fit" without behavioral evidence is where bias enters, and it should be challenged every time it appears.

Deciding

A yes needs evidence on every required competency, not a strong overall impression. Where evidence is missing, get it — an extra conversation is cheap compared to a mis-hire.

Ambiguity means no. The cost of a bad hire is far larger and lasts far longer than the cost of a longer search, and it is borne by the team, not the hiring manager.

Tooling

Applicant tracking, roughly by scale: Workable, JazzHR or the hiring module of an all-in-one HRIS at small scale; Greenhouse, Lever or Ashby once structured interviewing and reporting matter; Workday Recruiting or SmartRecruiters at enterprise scale, and similar.

Sourcing and scheduling: LinkedIn Recruiter, Gem, GoodTime, and similar.

Put the scorecard in the tracking system rather than beside it. A structured process that lives in a separate document is a structured process that stops being followed in the first busy week.

Never

  • Lower the bar because the search has been long. Reopen the role definition instead.
  • Let one interviewer's strong view override written independent assessments.
  • Skip reference checks on judgment and collaboration, which are exactly what interviews measure worst.

Signals

GitHub stars
1k
Forks
209
Last commit
Sep 2026
Advanced
Catalog kind
skill
Gateway key
hiring-and-interviewing
Source
github.com/cbrock84/headcount