Handles compensation benchmarking and equity modeling when you're trying to figure out what to pay someone or whether your current bands make sense. You can ask about specific roles ("what should we pay a Senior SWE in SF"), upload your comp data to spot outliers and retention risks, or model equity grants with vesting schedules. It pulls from connected compensation databases if you have them, otherwise falls back to web research and public salary data. The output is straightforward percentile tables (25th through 90th) broken down by base, equity, and total comp, plus recommendations. Useful for offer negotiations, annual reviews, or when someone on your team gets a competing offer and you need market context fast.

skills.sh installs
2.9K
GitHub stars
35.3K
last updated
Aug 21, 2026

Install

$ npx -y skills add anthropics/knowledge-work-plugins --skill comp-analysis --agent claude-code

Installs into .claude/skills of the current project.

Files

/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)

Sponsors

Details

Repository
github.com/anthropics/knowledge-work-plugins
First seen
Apr 16, 2026

More from anthropics/knowledge-work-plugins

All 198

Recommended

1juliusbrussee avatarcavemanjuliusbrussee/cavemanUltra-compressed communication mode. Cuts output tokens 65% (measured) by speaking like caveman while keeping full technical accuracy. Supports intensity levels618.3Kskills.sh installs
2mattpocock avatargrill-memattpocock/skillsA relentless interview to sharpen a plan or design.1.5Mskills.sh installs
3shadcn avatarimproveshadcn/improveSurvey any codebase as a senior advisor and produce prioritized, self-contained implementation plans for OTHER models/agents to execute. Strictly read-only on s40Kskills.sh installs
4obra avatarsystematic-debuggingobra/superpowersUse when encountering any bug, test failure, or unexpected behavior, before proposing fixes326.7Kskills.sh installs
5forrestchang avatarkarpathy-guidelinesforrestchang/andrej-karpathy-skillsBehavioral guidelines to reduce common LLM coding mistakes through explicit assumptions, simplicity, and verifiable success criteria.17.9Kskills.sh installs
6vercel-labs avatarfind-skillsvercel-labs/skillsHelps users discover and install agent skills when they ask questions like "how do I do X", "find a skill for X", "is there a skill that can...", or express int4.3Mskills.sh installs