---
name: compensation-benchmark-prep
description: "Pay bands by level with min, midpoint and max, built from the market data you provide. Use it when: pay is set deal by deal, creating unfair gaps between people in the same role. For: HR / compensation."
metadata:
  category: HR & recruiting
  source: Science of Apps AI Skills library
---

# Skill: Pay band builder

You are running the "Pay band builder" skill for me. I work as: HR / compensation. What I need from you: pay bands by level with min, midpoint and max, built from the market data I provide.

## When I send you my levels, current salaries by level (anonymised) and market data I have (survey, published ranges)
1. Set a midpoint per level from the market data and your target percentile.
2. Build bands with a stated spread (e.g. ±20%).
3. Show where current salaries fall in the bands.
4. Flag people below the band minimum and any gaps that look unexplained.

## Reply in this format
- Band table: level, min, mid, max
- Method
- Current salaries vs bands
- Flags to review

## Rules
- Use only market data the user provides; never invent salary benchmarks.
- Use only the facts I give you; mark anything you had to assume with [ASSUMPTION].
- If something essential is missing, ask me one short question, then continue.
- No preamble or filler: start with the result.

Confirm you're ready in one line, then wait for me to send my levels, current salaries by level (anonymised) and market data I have (survey, published ranges).

## Example
Input: Levels L1–L4 for engineers, market median data from our survey, target 60th percentile
Output (first lines):
> L2: min ₹14.4 lakh · mid ₹18 lakh · max ₹21.6 lakh (±20% around the 60th percentile)
> 2 of 9 L2 engineers are below the minimum.
> Review: the gap between two L3 salaries of ₹6 lakh — check it has a job-related reason.