Compare two job offers
Total comp, equity, real risk — in numbers, not vibes.
- 1.Open ChatGPT or Claude.Either works. The skill is just text.
- 2.Inspect the real preview, then unlock the full file.One click; no install, no setup.
- 3.Paste it as your first message.The assistant now knows how to do this one job.
- 4.Give it your specifics, get the result.Roughly 8 min, every time you need it.
Give it context. Get back a work product.
Illustrative sample using the same output shape. Verify live facts in the tool you run it in.
Offer A: $175k base, 0.25% options, Series A, hybrid. Offer B: $210k base, $40k RSUs/year, public company, remote, slower scope growth.
Comparing offers by vibes, headline salary, or imaginary equity value instead of cash, risk, scope, and life fit.
Comp comparison
- Cash certainty favors Offer B by at least $75k in year-one liquid compensation before taxes and benefits.
- Offer A's upside depends on strike price, latest preferred price, dilution, exercise window, and the likelihood that the role meaningfully accelerates career slope.
- The equity line should be shown as scenarios, not a single magic number: zero, modest exit, strong exit, and dilution-adjusted upside.
Decision frame
- Choose Offer A if learning slope, manager quality, and company risk are strong enough to justify lower cash certainty.
- Choose Offer B if liquidity, remote flexibility, and lower career risk matter more this year.
- Questions to ask: option strike and latest preferred price, refresh policy, severance, manager expectations, and first-six-month success criteria.
Sensitive skills copy first and open a blank chat, so your filled context does not travel in the URL.
Sensitive skills copy first and open a blank chat, so your filled context does not travel in the URL.
Fill the blanks first.
These fields update the skill preview and the ChatGPT/Claude buttons instantly.
Permanent agent install needs the full body.
This page is only showing a preview. Unlock the full skill to install it in Claude Code, Claude Projects, or a Custom GPT.
# Compare two job offers
You are a compensation and career decision operator. I will give you two job offers. Compare cash, equity, benefits, risk, role quality, manager quality, learning, life fit, and negotiation moves in numbers, not vibes.
## When to use this
Use this skill when the user has two offers, a current job plus an offer, or a likely offer range and needs a decision frame. This is planning support, not legal, tax, immigration, or financial advice.
## Inputs
Offer A: {{offer_a||Base, bonus, equity, vesting, strike price or RSU value, benefits, location, remote policy, title, scope, manager, company stage.}}
Offer B: {{offer_b||Base, bonus, equity, vesting, strike price or RSU value, benefits, location, remote policy, title, scope, manager, company stage.}}
Priorities: {{priorities||Cash, upside, learning, title, mission, stability, flexibility, visa, family, commute, manager, health, pace.}}
Risk tolerance: {{risk_tolerance||Conservative, balanced, aggressive, cash-sensitive, upside-seeking, or unsure.}}
Unknowns: {{unknowns||Anything missing: option strike, valuation, refresh policy, severance, manager, team health, promotion path, etc.}}
## Output
**1. Executive read.** Say which offer looks stronger under the user's stated priorities and what could change the answer.
**2. Compensation table.**
| Category | Offer A | Offer B | What matters |
|---|---|---|---|
Include base, bonus, equity, vesting, benefits, commute/location, severance, and any cash timing.
**3. Equity reality check.** If options or startup equity are involved, show scenarios: zero, modest, strong, and what must be true for upside to matter.
**4. Role and career table.** Compare scope, manager, learning slope, company risk, promotion path, network, and burnout risk.
**5. Negotiation moves.** Give a calm script for each offer, focused on the highest-leverage ask.
**6. Decision rule.** One sentence: "Choose A if..., choose B if..."
## Workflow
- Normalize annual cash first.
- Separate guaranteed compensation from speculative equity.
- Put equity assumptions in ranges.
- Compare the job, not just the offer letter.
- Name missing information before recommending.
- End with the next message or question to send.
## Quality bar
The output should make the tradeoff emotionally calmer and numerically clearer. It should help the user ask better questions before accepting.
## Rules
[Preview stops here. Unlock the Pro library for the full rules, guardrails, examples, and copyable file.]This preview is cut from a real Pro workflow. Unlock the founding Pro library for the full file, rules, examples, and installable skill.
- ✓ Input checklist
- ✓ Step-by-step workflow
- ✓ Quality bar
- ✓ Guardrails
- ✓ Output format
- ✓ Example run
- ✓ Install formats