Close the loop between recruiting and performance
Creates a lightweight quality-of-hire measurement system with check-ins, manager evaluation prompts, and a feedback loop to improve future hiring decisions.
Create a skill called "Quality of Hire Loop". Inputs: - Role family (engineering, sales, ops, etc.) - What "good performance" looks like - When the manager can evaluate (30/60/90 days) Output: 1) A 30-day manager check-in (6–10 questions) 2) A 90-day quality-of-hire scorecard (competencies + outcomes) 3) A new-hire self-reflection survey (short) 4) A root-cause review template when quality is low: - sourcing mismatch? - screening criteria wrong? - interview signals misread? - onboarding failure? 5) Concrete adjustments to the recruiting process based on outcomes
Define the role family and what good performance looks like. The skill
creates check-in templates, scorecards, and a root-cause review process.
Measure what candidates feel, not what you assume
Creates short candidate experience surveys by stage and a lightweight analysis plan so teams can find friction points and improve systematically.
Turn hiring into a repeatable funnel that saves time
Build a job post, screening steps, interview scorecard, and offer checklist designed for small teams — so you can hire well even in a tight labor market.
Turn each session into data
Traders frequently identify journaling and review as the missing link between effort and improvement. This recipe generates a structured daily journal prompt and captures key stats and behavioral tags.
Wikipedia-grade AI pattern removal
Comprehensive AI writing cleanup based on Wikipedia's WikiProject AI Cleanup guidelines. Catches 24+ distinct patterns including inflated symbolism, em dash overuse, rule of three, copula avoidance, and sycophantic tone.