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comp-analysis Skill

AI Agent SkillPythonOpen source

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. Published by anthropics in knowledge-work-plugins.

What is comp-analysis Skill?

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. Published by anthropics in knowledge-work-plugins. This profile combines repository metadata with install, compatibility, and usage signals so developers can quickly decide whether it fits their agent workflow before opening the source repository.

Trust signal
95/100
Maintenance signal
90/100
Adoption signal
100/100

Automated repository signals based on public metadata such as recency, license, installation evidence, and adoption. These are not a security audit or endorsement.

Key capabilities

  • Includes SKILL.md support
  • Reusable instructions support
  • Data analysis
  • Data analysis use cases

Technical details

Copy skill directory
  • Install or run with Copy skill directory

When to use comp-analysis Skill

  • Use it for data analysis.

Built with

PythonCopy skill directory

Editorial notes

Source

  • Creator: anthropics
  • Repository: anthropics/knowledge-work-plugins
  • Skill file: human-resources/skills/comp-analysis/SKILL.md

What it does

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.

Skill instructions

/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

Explore related resources

Frequently asked questions

What is comp-analysis?

comp-analysis is a open-source AI agent skill with Copy skill directory. 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.

Who is comp-analysis best for?

comp-analysis is best for reusing agent instructions, scripts, and references, data analysis workflows.

How do I install comp-analysis?

Install or run comp-analysis using Copy skill directory. Check comp-analysis for the latest setup command.

Is comp-analysis actively maintained?

comp-analysis may need a closer maintenance check before production use.

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22,594
Forks
2,657
Last commit
9 days ago
Repository age
6 months
License
Apache-2.0

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