skills.rest
sun2443
sun2443COMMUNITY
Explore all skills by this author →
GitHub

comp-analysis

Benchmark compensation against percentile bands and model equity grants.

Updated Apr 8, 2026
Search Tags:#benchmarking#compensation#equity modeling#total compensation#retention risk#band placement#hiring offers
One-click install
npx skills add https://github.com/sun2443/designer-skills --skill comp-analysis-sun2443
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: comp-analysis
Source: https://github.com/sun2443/designer-skills/tree/main/human-resources/skills/comp-analysis
Command: npx skills add https://github.com/sun2443/designer-skills --skill comp-analysis-sun2443

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

This Skill helps compensation teams determine appropriate pay levels by benchmarking against market ranges, placing offers into bands, and modeling equity outcomes without manual spreadsheets.

Core Features & Use Cases

  • Compensation benchmarking: Compare base, equity, and total compensation against percentile bands to assess competitiveness for hiring and retention.
  • Band placement and outlier detection: Analyze provided comp bands or employee comp to identify misalignment and potential retention risks.
  • Equity grant modeling: Estimate how an equity refresh or new grant performs over time based on share count and assumed stock price.
  • Use case: When preparing an offer for a Senior Software Engineer in SF, it can translate role/level/location context into recommended percentile-aligned compensation components and equity structure.

Quick Start

Ask it to analyze a specific role and location, such as: what should we pay a Senior Software Engineer in SF?

Frequently Asked Questions about comp-analysis

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

FAQPage Schema
How do I benchmark compensation for a specific role and location?▼

To benchmark compensation, provide role, level, and location context to generate percentile-based base, equity, and total comp outputs for offer competitiveness and retention analysis.

What is the best way to assess retention risk using employee compensation data?▼

Assess retention risk by providing current employee comp data alongside comp bands to perform outlier detection and identify potential retention risks.

Can I model equity grants and refresh outcomes based on stock price assumptions?▼

Yes, you can model equity grants by specifying share count and assumed stock price to estimate how an equity refresh or new grant performs over time.

How do I place hiring offers into compensation bands?▼

Place hiring offers into comp bands by interpreting role, level, and location context to produce recommended percentile-aligned compensation components and equity structure.

Do I need to provide comp bands to detect outliers?▼

Yes, providing comp bands is required to perform outlier detection, analyze provided comp data for misalignment, and identify potential retention risks.

Related Skills

Explore More Finance & Accounting Skills→
TravisLeeeeeeTravisLeeeeee
110

Compensation Benchmarker

Benchmark employee compensation against market rates by role, level, location, and industry.

Community
Advanced
1479089714790897
7

kwp-human-resources-comp-analysis

Analyze compensation data for benchmarking, band placement, and equity modeling.

Community
Intermediate
hck717hck717

fundamentals-analysis

Analyze equity fundamentals by combining SQLite financial data with knowledge graph evidence.

Community
Advanced
ilove323ilove323

comp-analysis

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

Community
Intermediate