compensation-benchmark

Generate survey-backed compensation pay bands from comp survey exports and firm philosophy.

Updated May 2, 2026
One-click install
npx skills add https://github.com/marius-bughiu/ooligo --skill compensation-benchmark
Or copy as Structured Prompt for Agent
Please help me install this Agent Skill.
Skill: compensation-benchmark
Source: https://github.com/marius-bughiu/ooligo/tree/main/apps/web/public/artifacts/compensation-benchmark-skill
Command: npx skills add https://github.com/marius-bughiu/ooligo --skill compensation-benchmark

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill eliminates manual, error-prone compensation benchmarking work by automating the process of building pay bands from market survey data, ensuring alignment with firm compensation philosophy and pay transparency laws to reduce legal risk and pay inequity.

Core Features & Use Cases

  • Survey-aligned pay band generation: Pulls percentile data from Radford, Pave, Carta, or custom CSV exports to build data-backed base, equity, and bonus/OTE bands.
  • Compliance-first public ranges: Automatically formats pay ranges that meet NYC LL 32-A, CO/CA/WA pay transparency requirements, with warnings for bands that fall below "good faith" width thresholds.
  • Audit-ready reporting: Generates full internal benchmark reports with documented fallback chains for low-sample survey cells, calibration notes, and JSONL audit records to support annual pay equity reviews. Use case: A comp analyst can use this Skill to generate a fully compliant pay band for a senior software engineer in San Francisco in minutes, instead of manually cross-referencing multiple survey sources and checking regional legal requirements.

Quick Start

Provide the role definition, valid compensation survey export, and your firm's compensation philosophy file to the compensation-benchmark skill to receive a complete, compliant pay band recommendation and public-facing range report.

Frequently Asked Questions about compensation-benchmark

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

FAQPage Schema
How do I generate compliant pay bands from a compensation survey export?

Generate compliant pay bands by providing a valid compensation survey export, role definition, and your firm's compensation philosophy file. The system calibrates base, equity, and bonus/OTE bands against target percentiles to produce audit-ready pay recommendations.

How do I handle low-sample survey cells when benchmarking salary data?

Handle low-sample survey cells by using documented fallback chains that validate input role definitions. This ensures your compensation benchmarking maintains data integrity and produces audit-ready documentation for annual pay equity reviews despite limited market data.

Can I use this tool to create public-facing pay ranges for NYC LL 32-A and CA transparency laws?

Create public-facing pay ranges compliant with NYC LL 32-A and CO/CA/WA transparency laws. The system formats compliant ranges automatically and flags bands falling below "good faith" width thresholds for legal risk reduction.

Does compensation benchmarking work with Radford, Pave, and Carta survey data?

Compensation benchmarking works with Radford, Pave, Carta, or custom CSV survey exports. It pulls percentile data from these sources to build data-backed pay bands aligned with your firm's compensation philosophy.

What do I need to start automating salary calibration for pay equity reviews?

Start automating salary calibration by providing a role definition, valid compensation survey export, and firm compensation philosophy file. The system outputs internal benchmark reports and JSONL audit records supporting annual pay equity reviews.

What is the best way to structure pay transparency reporting for multiple states?

Structure pay transparency reporting by generating both internal benchmark reports and public-facing compliant pay ranges. The system formats ranges meeting CO/CA/WA and NYC requirements while providing calibration notes for audit defense.