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comp-analysis

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

46|11|Updated Mar 29, 2026
Search Tags:#benchmarking#compensation#market-data#analyze#data-quality#equity-modeling#band-analysis
One-click install
npx skills add https://github.com/clawpod-app/awesome-openclaw-agent-packs --skill comp-analysis-clawpod-app
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: comp-analysis
Source: https://github.com/clawpod-app/awesome-openclaw-agent-packs/tree/main/packs/human-resources/skills/comp-analysis
Command: npx skills add https://github.com/clawpod-app/awesome-openclaw-agent-packs --skill comp-analysis-clawpod-app

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Analyze compensation data for benchmarking, band placement, and equity modeling. This tool helps HR and compensation teams align pay with market data, set fair offers, and plan for retention.

Core Features & Use Cases

  • Benchmark compensation across markets, roles, levels, and company stages
  • Model equity grants and retention scenarios to forecast impact
  • Identify outliers and data quality issues in compensation datasets
  • Generate percentile bands (25th, 50th, 75th, 90th) with location and stage context
  • Accept data uploads (CSV or pasted data) and respond to role-based prompts

Quick Start

Provide your compensation context as arguments to the command, for example '/comp-analysis 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 data for a specific role across different locations?▼

Compensation benchmarking analyzes pay data by parsing role descriptors and computing percentile bands (25th, 50th, 75th, 90th) while applying location and company-stage context to generate structured market comparisons.

What is the best way to model equity grants for retention scenarios?▼

Equity grant modeling forecasts retention impact by evaluating compensation datasets and role-based prompts to produce structured recommendations for hiring and compensation planning across various company stages.

Can I upload a CSV file to analyze compensation bands and identify outliers?▼

Yes, compensation band analysis accepts CSV data uploads or pasted datasets to identify outliers, resolve data quality issues, and generate percentile bands with location and stage context.

How do percentile bands work when setting fair compensation offers?▼

Percentile bands calculate the 25th, 50th, 75th, and 90th percentiles of market compensation data, applying location and company-stage context to help HR teams align pay and set fair offers.

Does compensation benchmarking work for early-stage startups and large companies?▼

Yes, compensation benchmarking applies company-stage context to role-based market data, allowing HR teams to align pay structures accurately across early-stage startups and established large companies.

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