team-composition-analysis
by wshobsonteam-composition-analysis helps founders, operators, and recruiting leads plan early-stage startup hiring by stage, ARR, and budget. Use it to sequence roles, shape team structure, and estimate compensation and equity from pre-seed through Series A.
This skill scores 78/100, which means it is a solid directory listing candidate for users who need startup hiring and org-design guidance. The repository evidence shows substantial, non-placeholder workflow content with clear stage-based triggers and practical outputs, though adoption still depends on reading a long markdown guide rather than using supporting files, templates, or executable artifacts.
- Strong triggerability: the description clearly names when to use it for headcount planning, hiring order, compensation, equity, org design, and hiring budgets.
- Substantive operational content: the skill body is long, structured, and organized by startup stage, team structure, and practical planning topics rather than being a placeholder.
- Good agent leverage over a generic prompt: it packages stage-specific heuristics like team size ranges, role priorities, and department allocation guidance in one reusable workflow.
- No support files, templates, references, or scripts, so execution relies entirely on the markdown guidance and may require agent interpretation.
- Trust and decision precision are limited by the lack of cited benchmarks or linked source material for compensation, equity, and hiring recommendations.
Overview of team-composition-analysis skill
What team-composition-analysis does
The team-composition-analysis skill helps founders, startup operators, and recruiting leads design an early-stage hiring plan that fits company stage, ARR, and budget reality. It is built for pre-seed through Series A planning, with guidance on team shape, role sequencing, compensation ranges, and equity allocation.
Who this skill is best for
This skill is most useful if you need to answer questions like:
- Which roles should we hire next?
- How large should the team be at our current stage?
- When should we add product, sales, or customer success?
- How should cash compensation and equity differ by role?
- How do we avoid over-hiring before revenue supports it?
It is especially relevant for founders, heads of talent, startup CFO/COO operators, and recruiters supporting venture-backed startups.
The real job-to-be-done
Most users do not just want a generic org chart. They want a defendable hiring plan that connects stage, revenue, and functional priorities to actual headcount decisions. The team-composition-analysis skill is valuable because it frames hiring as a sequencing and tradeoff problem, not just a list of common startup roles.
What makes it different from a generic prompt
A normal prompt might produce broad advice like “hire engineers first, then sales.” This skill is more useful when you need stage-specific structure:
- expected team size by startup phase
- likely departmental mix by Series A
- role priorities tied to company maturity
- compensation and equity planning context
- hiring budget thinking aligned to milestones
That makes it more decision-oriented than a one-off brainstorming prompt.
What to know before installing
The repository evidence shows this skill is primarily a single SKILL.md document with embedded guidance rather than a larger toolkit with scripts, references, or rule files. That means team-composition-analysis install is simple, but output quality depends heavily on the inputs you provide. If your company context is vague, the analysis will stay generic.
How to Use team-composition-analysis skill
Install team-composition-analysis skill
Install it with:
npx skills add https://github.com/wshobson/agents --skill team-composition-analysis
Because the skill lives inside a larger repo, this command is the practical entry point for most users evaluating team-composition-analysis usage.
Read this file first
Start with:
plugins/startup-business-analyst/skills/team-composition-analysis/SKILL.md
There are no visible companion resources, scripts, or rule files in this skill path, so most of the usable guidance is concentrated in that one file. This is good for quick adoption, but it also means you should not expect hidden benchmark datasets or automated calculators.
What input the skill needs to work well
The team-composition-analysis skill performs best when you provide the operating context the base document cannot infer. At minimum, include:
- company stage: pre-seed, seed, or Series A
- current ARR or revenue range
- current headcount and founder coverage
- product type: SaaS, marketplace, AI tool, services-assisted software, etc.
- near-term goal: PMF, repeatable sales, enterprise expansion, retention, fundraising
- hiring budget or burn constraints
- geography or compensation market
- whether you need salary, equity, or both
Without these details, the model will default to broad stage advice.
Turn a rough goal into a usable prompt
Weak prompt:
Help me plan my startup team.
Better prompt:
Use the team-composition-analysis skill to recommend a hiring plan for a seed-stage B2B SaaS startup at $1.2M ARR with 9 employees. Current team: 2 founders, 4 engineers, 1 designer, 1 AE, 1 ops generalist. We have 18 months runway, want to reach $3M ARR, and need to decide the next 5 hires. Include role order, rationale, rough compensation/equity bands, and which hires to delay.
Why this works better:
- it gives a stage and revenue anchor
- it shows current team coverage and gaps
- it defines a target milestone
- it forces prioritization, not a wish list
Best prompt pattern for Recruiting teams
For team-composition-analysis for Recruiting, ask for an output that recruiting can actually operationalize. Example:
Use team-composition-analysis to build a recruiting brief for a pre-Series A startup at $2.5M ARR. Recommend the next 6 hires over 12 months, including function, seniority, why each role is needed now, salary range, equity range, and dependencies between hires. Flag any roles that should stay fractional or contract instead of full-time.
This turns the skill into a practical intake tool for talent teams, not just strategy commentary.
Suggested workflow in practice
A strong workflow looks like this:
- Define current stage, ARR, runway, and team.
- Ask the skill for the next-hire sequence.
- Request tradeoffs: “What if we optimize for product velocity vs revenue growth?”
- Ask which roles can remain founder-led, fractional, or outsourced.
- Convert the final recommendations into recruiter-ready job priorities.
This workflow makes team-composition-analysis usage more robust than asking for a single static org design.
What the skill appears to cover best
Based on the source, the clearest strength is early-stage structure planning:
- pre-seed team composition
- seed hiring priorities
- Series A departmental build-out
- startup compensation and equity framing
It is strongest when the question is “what should the team look like at this stage?” rather than “build me a detailed compensation benchmark by city and level.”
Where the skill is likely thin
Because the repository evidence only exposes one markdown skill file, do not assume the skill includes:
- market-by-market salary databases
- role-specific scorecards
- interview processes
- automated budgeting models
- legal or tax-safe equity guidance by jurisdiction
If you need those, use team-composition-analysis for structure and sequencing, then validate details with compensation data, finance tools, and counsel.
Practical tips that improve output quality
Ask the model to produce decisions in tables such as:
- role
- timing
- business reason
- estimated cash comp
- estimated equity
- risk if delayed
- cheaper alternative
Also ask for “roles not to hire yet.” This is often where the skill creates the most value, because early-stage hiring mistakes usually come from premature specialization.
Good repository-reading path
If you want to inspect before adopting, the shortest useful path is:
- Open
SKILL.md - Read the stage sections for team size and role mix
- Check whether the compensation and equity guidance is specific enough for your use case
- Decide whether you need a startup planning skill or a full recruiting ops framework
This is the right evaluation lens for a team-composition-analysis guide: assess decision quality, not document length.
team-composition-analysis skill FAQ
Is team-composition-analysis good for non-startups?
Usually no. The skill is clearly oriented toward early-stage startup planning from pre-seed through Series A. If you are staffing a mature company, a large enterprise, or a heavily regulated org, the assumptions around team size, function mix, and equity will be a weaker fit.
Is this skill useful for beginners?
Yes, if you already understand your company basics. The structure is approachable, but beginners still need to supply context like stage, runway, and growth goals. Without that, the output will sound reasonable while remaining too generic to act on.
How is team-composition-analysis better than normal prompting?
The value is not magic automation. The value is better default framing: stage-aware headcount planning, hiring order, and compensation/equity discussion. That usually leads to more grounded answers than a blank-slate prompt.
Can I use team-composition-analysis for compensation decisions?
Yes, but cautiously. Use it for directional planning and relative tradeoffs, not final offer design. Compensation ranges and equity should be verified with current market benchmarks and legal/finance review.
Is team-composition-analysis for Recruiting only?
No. It also fits founders, operators, and finance leads. But it is especially useful for Recruiting when intake is vague and stakeholders need a stage-aware hiring roadmap before opening roles.
When should I not use this skill?
Skip it when you need:
- exact local salary benchmarking
- deep org design for later-stage companies
- technical capacity planning at engineering-manager detail
- legal advice on equity grants
- a hiring process playbook
In those cases, team-composition-analysis skill is a planning input, not the full solution.
How to Improve team-composition-analysis skill
Give the skill harder constraints
The fastest way to improve team-composition-analysis results is to add real limits:
- hiring budget cap
- runway target
- founder strengths and weaknesses
- time-to-fill assumptions
- must-hit milestone by date
The skill gets sharper when forced to choose between good options.
Provide current team coverage, not just headcount
“10 employees” is weak input. This is stronger:
- 2 founders covering product and GTM
- 5 engineers, no engineering manager
- 1 designer
- 1 AE
- 1 customer support generalist
That lets the model reason about missing functions and overloaded founders.
Ask for sequencing, not a shopping list
A common failure mode is getting an inflated list of roles. Ask instead:
- next 3 hires
- next 6 hires by quarter
- hires to postpone
- hires that can stay contractor/fractional
This makes the team-composition-analysis guide materially more actionable.
Force tradeoff analysis
Ask the skill to compare scenarios such as:
- growth-first vs efficiency-first
- product-heavy vs sales-heavy
- founder-led GTM vs early sales hire
- full-time vs fractional finance, design, or recruiting
This is where the skill becomes more useful than a generic startup advice prompt.
Improve the compensation output
If you want better pay guidance, provide:
- hiring geography
- remote vs in-office
- seniority level
- cash vs equity preference
- fundraising status
Otherwise compensation advice will stay broad and may not support real approvals.
Iterate after the first output
After the first pass, ask follow-ups like:
Which recommendation is riskiest if our sales cycle is longer than expected?What changes if we freeze hiring for 2 quarters?Which role gives the highest leverage per dollar today?What are the signs we are hiring this role too early?
These questions improve trust and reveal whether the initial plan is robust.
Watch for common misfires
The most likely weak outputs are:
- over-hiring management too early
- adding specialized functions before PMF
- assuming all work needs full-time hires
- giving compensation ranges without market context
- skipping founder role coverage in the analysis
You can reduce these by explicitly asking the skill to justify every recommended hire against stage and revenue.
Use team-composition-analysis as a draft, then operationalize
The best final workflow is:
- Use
team-composition-analysis skillto define team structure and hiring order. - Convert top roles into recruiter briefs or finance models.
- Pressure-test salary and equity externally.
- Re-run the skill when stage, revenue, or runway changes.
That is the highest-value way to improve team-composition-analysis usage over time.