- /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
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- Cash compensation
- Equity
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- RSUs, stock options, or other equity
- Bonus
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- Annual target bonus, signing bonus
- Benefits
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- Health, retirement, perks (harder to quantify)
- Key Variables
- Role
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- Function and specialization
- Level
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- IC levels, management levels
- Location
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- Geographic pay adjustments
- Company stage
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- Startup vs. growth vs. public
- Industry
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- Tech vs. finance vs. healthcare
- Data Sources
- With ~~compensation data
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- 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 | |
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|
|
| | 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 | |
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|
|
|
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| | [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.