Comprehensive team structure, compensation, and equity planning for early-stage startups from pre-seed through Series A.
Works with
Provides role-by-role hiring guidance, salary benchmarks (US 2024), and fully-loaded cost calculations across engineering, sales, product, customer success, and G&A functions
Includes equity allocation frameworks by stage and role, option pool sizing, and founder vesting guidelines
Covers organizational design patterns, reporting structures, span-of-control ra
AI-first code editor with Composer
Before installing skills in Cursor, ensure your development environment meets these requirements:
node --versionteam-composition-analysisExecute the skills CLI command in your project's root directory to begin installation:
Fetches team-composition-analysis from wshobson/agents and configures it for Cursor.
The CLI shows a list of agents. Use arrow keys and space to select Cursor:
Confirm successful installation by checking the skill directory location:
Restart Cursor to activate team-composition-analysis. Access via /team-composition-analysis in your agent's command palette.
We perform automated surface-level scans (Gen AI Scanner, Socket, Snyk) during installation. These checks detect common vulnerabilities but do not guarantee complete security. Always review skill source code and verify the publisher's reputation before production use.
Skills execute code in your environment. Always review source, verify the publisher, and test in isolation before production.
Submit your Claude Code skill and start earning
Create detailed user stories, acceptance criteria, and feature specs
Example
Generate user stories for 'password reset feature' with acceptance criteria, edge cases, and test scenarios
Reduce spec writing time by 50%, ensure comprehensive coverage
Research competitors, compare features, identify gaps
Example
Analyze 5 competitor products, create feature comparison matrix, suggest differentiation opportunities
Complete competitive research in 2 hours instead of 2 days
Evaluate features using frameworks (RICE, ICE, Kano) and create prioritized backlogs
Example
Score 20 feature ideas using RICE framework, generate prioritized roadmap with rationale
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Design optimal team structures, hiring plans, compensation strategies, and equity allocation for early-stage startups from pre-seed through Series A.
Build the right team at the right time with appropriate compensation and equity. Plan role-by-role hiring aligned with revenue milestones, budget constraints, and market benchmarks.
Team Size: 2-5 people
Core Roles:
Focus: Build and validate product-market fit
Team Size: 5-15 people
Key Hires:
Focus: Scale product and prove repeatable sales
Team Size: 15-50 people
Department Build-Out:
Focus: Scale revenue and build repeatable processes
Pre-Seed:
Seed:
Series A:
Pre-Seed:
Seed:
Series A:
Pre-Seed:
Seed:
Series A:
Pre-Seed:
Seed:
Series A:
Pre-Seed:
Seed:
Series A:
Engineering:
Sales:
Product:
Marketing:
Customer Success:
Total Comp = Base Salary × 1.30 (benefits & taxes) + Equity Value
Fully-Loaded Cost:
Rule of Thumb: Multiply base salary by 1.3-1.4 for fully-loaded cost
San Francisco / New York: +20-30% above benchmarks Seattle / Boston / Los Angeles: +10-20% Austin / Denver / Chicago: +0-10% Remote / Other US Cities: -10-20% International: Varies widely by country
Founders:
Early Employees (Pre-Seed):
Seed Stage Hires:
Series A Hires:
Option Pool by Round:
Pre-Funding Dilution: Investors often require option pool creation before investment, diluting founders.
Example:
Pre-money: $10M
Investors want 15% option pool post-money
Calculation:
Post-money: $15M ($10M + $5M investment)
Option pool: $2.25M (15% × $15M)
Founders diluted by pool creation before new money
Pre-Seed:
Founders (flat structure)
├── Contractors
└── First hires (report to founders)
Seed:
CEO
├── Engineering Lead (2-4 engineers)
├── Sales/Growth Lead (1-2 reps)
├── Product Manager
└── Operations
Series A:
CEO
├── CTO / VP Engineering (6-20 people)
│ ├── Engineering Manager(s)
│ └── Individual Contributors
├── VP Sales (5-15 people)
│ ├── Sales Manager
│ ├── Account Executives
│ └── SDRs
├── Head of Product (2-5 people)
│ ├── Product Managers
│ └── Designers
├── Head of Customer Success (2-5 people)
└── CFO / Finance Lead (2-5 people)
├── Recruiter
└── Operations
Manager Ratios:
Full-Time:
Contract:
Role Opening to Hire:
Time to Productivity:
Always add 2-3 months buffer to hiring plans.
Example: If need engineer by July 1:
Early Stage (Seed):
Growth Stage (Series A):
Total Comp Budget = Σ (Role Count × Fully-Loaded Cost × % of Year)
Example:
3 Engineers × $202K × 100% = $606K
2 AEs × $230K × 75% (mid-year start) = $345K
1 PM × $162K × 100% = $162K
Total: $1.1M
To plan team composition:
Make data-driven prioritization decisions faster
Draft PRDs, status updates, and stakeholder presentations
Example
Create executive summary of Q3 roadmap, monthly progress report, feature launch announcement
Save 3-5 hours/week on communication overhead
Prerequisites
Time Estimate
30-60 minutes to see productivity improvements
Steps
Common Pitfalls
✓ Do
✗ Don't
💡 Pro Tips
✓ Use when
Use for user story writing, competitive research, roadmap prioritization, stakeholder communication, and PRD drafting. Best for reducing repetitive documentation and research work.
✗ Avoid when
Avoid for strategic product vision (requires deep customer empathy), pricing decisions (needs market and financial expertise), or when face-to-face customer discovery is more valuable than speed.
mattpocock/skills
parcadei/continuous-claude-v3
cursor/plugins
ailabs-393/ai-labs-claude-skills
pproenca/dot-skills
mattpocock/skills
I recommend team-composition-analysis for anyone iterating fast on agent tooling; clear intent and a small, reviewable surface area.
team-composition-analysis fits our agent workflows well — practical, well scoped, and easy to wire into existing repos.
team-composition-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
Keeps context tight: team-composition-analysis is the kind of skill you can hand to a new teammate without a long onboarding doc.
Useful defaults in team-composition-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
Registry listing for team-composition-analysis matched our evaluation — installs cleanly and behaves as described in the markdown.
team-composition-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
Solid pick for teams standardizing on skills: team-composition-analysis is focused, and the summary matches what you get after install.
Useful defaults in team-composition-analysis — fewer surprises than typical one-off scripts, and it plays nicely with `npx skills` flows.
team-composition-analysis has been reliable in day-to-day use. Documentation quality is above average for community skills.
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