compensation-benchmarking

Benchmark compensation against market and internal data to produce percentile salary ranges.

2|1|Updated Apr 3, 2026
One-click install
npx skills add https://github.com/GACLove/feishu-aily-skills --skill compensation-benchmarking-gaclove
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: compensation-benchmarking
Source: https://github.com/GACLove/feishu-aily-skills/tree/main/skills/compensation-benchmarking
Command: npx skills add https://github.com/GACLove/feishu-aily-skills --skill compensation-benchmarking-gaclove

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Many companies struggle to determine competitive pay levels, risking overpayment or talent loss.

Core Features & Use Cases

  • Data Gathering: Retrieves internal benchmarks via knowledge base and external market rates via web search.
  • Analysis: Compares role, level, location, and company stage against peer groups and provides percentile bands.
  • Outcome: Delivers clear compensation ranges with confidence intervals for base, equity, and total pay.

Quick Start

Ask the skill to benchmark the compensation for a senior software engineer in San Francisco at a mid‑stage startup.

Frequently Asked Questions about compensation-benchmarking

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, you compare role, seniority level, geographic location, and company stage against peer groups. The skill retrieves internal knowledge base and external market rates to produce percentile salary ranges with confidence intervals.

What salary data is needed for accurate pay analysis?

Accurate pay analysis requires internal compensation benchmarks and external market rate data. The skill validates data sources and checks data freshness to ensure the resulting salary ranges reflect current market conditions.

Can I get percentile salary ranges for base, equity, and total pay?

Yes, percentile salary ranges are generated for base, equity, and total pay. The analysis applies role, level, and company stage filters to peer group data, delivering compensation ranges complete with confidence interval reporting.

How does market data source validation work for salary benchmarking?

Market data source validation ensures benchmarking accuracy by checking data freshness and source reliability. This process satisfies requirements for confidence interval reporting, helping you avoid overpayment or talent loss.

What is the best way to compare internal compensation against market rates?

The best way to compare internal and market rates is filtering by role, seniority, location, and company stage. The skill retrieves both datasets, compares them against peer groups, and outputs percentile bands for total compensation.