comp-analysis

Analyze compensation data to benchmark salaries, detect pay-band outliers, and model equity grants.

1|Updated Mar 30, 2026
One-click install
npx skills add https://github.com/ilove323/comlan-skills --skill comp-analysis-ilove323
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: comp-analysis
Source: https://github.com/ilove323/comlan-skills/tree/main/human-resources/skills/comp-analysis
Command: npx skills add https://github.com/ilove323/comlan-skills --skill comp-analysis-ilove323

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze compensation and equity data to provide clear market benchmarking, pay-band positioning, and grant modeling so hiring, retention, and equity decisions are informed and consistent.

Core Features & Use Cases

  • Market benchmarking: Generate 25th/50th/75th/90th percentile benchmarks for base salary, equity, and total compensation by role, level, and location.
  • Pay-band analysis: Ingest internal CSV salary bands to identify outliers, quantify positioning, and suggest adjustments relative to market data.
  • Equity modeling: Model option or RSU grants across vesting schedules and share price scenarios to estimate value at different percentiles.
  • Use Case: Compare a Senior Software Engineer in San Francisco against market percentiles, analyze an uploaded payroll CSV for band misalignment, or model a 4-year option grant at multiple price points.

Quick Start

Ask the assistant to analyze a Senior Software Engineer in San Francisco for market compensation percentiles and recommend pay-band positioning.

Frequently Asked Questions about comp-analysis

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I benchmark salary data against market percentiles for a specific role?

Salary benchmarking compares internal compensation against 25th, 50th, 75th, and 90th percentile market data by role, level, and location. Provide a role and location to generate percentile-based benchmarks and receive pay-band positioning recommendations.

Can I analyze a CSV payroll file to identify pay-band outliers?

Yes, you can upload a bulk CSV salary band file to detect pay-band outliers and quantify internal positioning. The analysis identifies anomalies and suggests adjustments relative to market data while respecting data privacy.

How does equity grant modeling work across different vesting schedules and price scenarios?

Equity grant modeling estimates option or RSU value by applying vesting schedules and share price scenarios across multiple percentiles. It calculates potential grant values across different company stages and locations.

Does pay-band analysis support location adjustments for high-cost areas like San Francisco?

Yes, pay-band analysis applies location adjustments to market benchmarks. It factors in geographic cost differences when generating percentile benchmarks and recommending internal pay-band positioning for roles in specified locations.

What's the best way to model a 4-year option grant at multiple price points?

Model a 4-year option grant by defining the vesting schedule and inputting various share price scenarios. The equity modeling feature estimates the grant's value at different percentiles based on those price point inputs.

Why does my internal payroll CSV show band misalignment compared to market data?

Band misalignment occurs when internal salaries deviate from market percentiles. Ingesting your CSV identifies outliers, quantifies the positioning gap relative to market data, and outputs suggested adjustments to correct the misalignment.