comp-benchmarking
Analyze market compensation data and establish competitive pay structures
npx skills add a5c-ai/babysitter --skill comp-benchmarking --agent claude-code
Same command for any agent — swap --agent for codex, cursor, copilot.
Weekly change comes from our own snapshots, not the repository page — it measures attention, not adoption.
# Compensation Benchmarking Skill ## Overview The Compensation Benchmarking skill provides capabilities for analyzing market compensation data and establishing competitive pay structures. This skill enables market percentile positioning, salary range development, and compensation competitiveness monitoring. ## Capabilities ### Survey Data Analysis - Import and analyze salary survey data - Blend multiple survey sources - Age and trend data appropriately - Handle different data cuts - Validate data quality ### Market Positioning - Calculate market percentiles and positioning - Determine competitive positioning strategy - Analyze positioning by job family - Track positioning trends - Compare against target percentile ### Salary Range Development - Build salary range structures - Calculate range spread and midpoint - Design grade structures - Create multiple range types (broad, narrow) - Support geographic differentials ### Scenario Modeling - Model compensation scenarios and costs - Project budget impacts - Analyze merit increase scenarios - Model structure adjustments - Calculate cost of living impacts ### Reporting - Generate market pricing reports - Create competitiveness summaries
- Overview
- Capabilities
- Survey Data Analysis
- Market Positioning
- Salary Range Development
- Scenario Modeling
- Reporting
- Geographic Analysis
- Usage
- Market Analysis
- Range Structure Design
- Process Integration
- Best Practices
- Metrics and KPIs
What does the comp-benchmarking skill do?
Analyze market compensation data and establish competitive pay structures
How do I install it?
Run `npx skills add a5c-ai/babysitter --skill comp-benchmarking --agent claude-code` — it drops the skill into your project so the agent can pick it up. Swap the --agent value for codex, cursor or copilot if you use one of those.
Where does this skill come from?
From a5c-ai/babysitter, a repository with 1,642 stars. We read it straight from the repository tree rather than a submitted listing, so what you see here is what is actually published.
Is a popular skill a good skill?
Not necessarily. Stars measure attention, not adoption — a repository can trend for a week and be abandoned. That is why we show the weekly change from our own snapshots next to the total, instead of a single flattering number.