comp-analysis

name comp-analysis description Analyze compensation — benchmarking, band placement, and equity modeling. Trigger with "what should we pay a [role]", "is this offer competitive", "model this equity grant", or when uploading comp data to find outliers and retention risks. argument-hint <role, level, or dataset> /comp-analysis If you see unfamiliar placeholders or need to check which tools are connected, see CONNECTORS.md . Analyze compensation data for benchmarking, band placement, and planning. Helps benchmark compensation against market data for hiring, retention, and equity planning. Usage /comp-analysis $ARGUMENTS What I Need From You Option A: Single role analysis "What should we pay a Senior Software Engineer in SF?" Option B: Upload comp data Upload a CSV or paste your comp bands. I'll analyze placement, identify outliers, and compare to market. Option C: Equity modeling "Model a refresh grant of 10K shares over 4 years at a $50 stock price." Compensation Framework Components of Total Compensation Base salary : Cash compensation Equity : RSUs, stock options, or other equity Bonus : Annual target bonus, signing bonus Benefits : Health, retirement, perks (harder to quantify) Key Variables Role : Function and specialization Level : IC levels, management levels Location : Geographic pay adjustments Company stage : Startup vs. growth vs. public Industry : Tech vs. finance vs. healthcare Data Sources With ~~compensation data : Pull verified benchmarks Without : Use web research, public salary data, and user-provided context Always note data freshness and source limitations Output Provide percentile bands (25th, 50th, 75th, 90th) for base, equity, and total comp. Include location adjustments and company-stage context. ## Compensation Analysis: [Role/Scope] ### Market Benchmarks | Percentile | Base | Equity | Total Comp | |------------|------|--------|------------| | 25th | $[X] | $[X] | $[X] | | 50th | $[X] | $[X] | $[X] | | 75th | $[X] | $[X] | $[X] | | 90th | $[X] | $[X] | $[X] | **Sources:** [Web research, compensation data tools, or user-provided data] ### Band Analysis (if data provided) | Employee | Current Base | Band Min | Band Mid | Band Max | Position | |----------|-------------|----------|----------|----------|----------| | [Name] | $[X] | $[X] | $[X] | $[X] | [Below/At/Above] | ### Recommendations - [Specific compensation recommendations] - [Equity considerations] - [Retention risks if applicable] If Connectors Available If ~~compensation data is connected: Pull verified market benchmarks by role, level, and location Compare your bands against real-time market data If ~~HRIS is connected: Pull current employee comp data for band analysis Identify outliers and retention risks automatically Tips Location matters — Always specify location for benchmarking. SF vs. Austin vs. London are very different. Total comp, not just base — Include equity, bonus, and benefits for a complete picture. Keep data confidential — Comp data is sensitive. Results stay in your conversation.