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Offer Comparison Analyzer

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Paramchoudhary
offer-comparison-analyzer

Compare multiple job offers side-by-side with total compensation analysis

Overview

PublisherParamchoudhary
RepositoryResumeSkills
Skill nameoffer-comparison-analyzer
Stars
2.3K
Forks
197
Bundled files
Instructions only
LicenseMIT
Links
  • Markdown instructions

    A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.

  • Works with any LLM

    AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.

  • Self-contained

    Everything the model needs lives in the instructions — no extra files to sync.

  • Open source

    Published by Paramchoudhary on GitHub. Read the source before you install it.

Installation

Install the Offer Comparison Analyzer AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

1

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

  1. Open the app and go to Plugins → Skills.
  2. Choose "Install from GitHub".
  3. Paste the skill folder URL below and confirm.
  4. Enable the skill in any chat where you want it available.
Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.
2

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills
git clone --depth 1 https://github.com/Paramchoudhary/ResumeSkills.git /tmp/ResumeSkills
mkdir -p .claude/skills
cp -r /tmp/ResumeSkills/skills/offer-comparison-analyzer .claude/skills/offer-comparison-analyzer
Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Offer Comparison Analyzer in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Offer Comparison Analyzer on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Offer Comparison Analyzer is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

  • Loaded only when it is needed

    The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.

  • Switch models mid-chat

    Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

Offer Comparison Analyzer

When to Use This Skill

Use this skill when the user:

  • Has multiple job offers to compare
  • Needs to evaluate total compensation
  • Wants to make a data-driven job decision
  • Is weighing different opportunities
  • Mentions: "compare offers", "multiple offers", "which job", "offer comparison", "deciding between jobs"

Core Capabilities

  • Compare total compensation across offers
  • Evaluate non-monetary factors
  • Create weighted decision frameworks
  • Calculate true offer value
  • Identify hidden costs and benefits
  • Guide the decision-making process

The Comparison Challenge

The Problem: Comparing offers is hard because:

  • Different compensation structures
  • Non-monetary factors matter
  • Hidden benefits and costs
  • Emotional factors cloud judgment
  • Information asymmetry

The Solution: Systematic comparison framework that considers:

  • Total compensation (not just salary)
  • Career growth potential
  • Work-life factors
  • Risk assessment
  • Personal values alignment

Total Compensation Calculator

Components to Include

Cash Compensation:

  • Base salary
  • Signing bonus (one-time)
  • Annual bonus (target %)
  • Commission (for sales roles)
  • Relocation assistance

Equity Compensation:

  • Stock options (value = current price - strike price)
  • RSUs (value = current price × shares)
  • Vesting schedule
  • Refresh grant expectations

Benefits Value:

  • Health insurance (employer contribution)
  • 401(k) match
  • HSA/FSA contributions
  • Life/disability insurance
  • Other insurance benefits

Perks Value:

  • Vacation days (can assign $ value)
  • Remote work (saves commute costs)
  • Professional development budget
  • Equipment/office stipend
  • Meals, gym, etc.

Calculation Template

OFFER A - TOTAL COMPENSATION

CASH
Base Salary:                    $150,000
Signing Bonus (year 1 only):     $25,000
Target Bonus (15%):              $22,500
--------------------------------
Cash Compensation:              $197,500 (year 1)
                               $172,500 (ongoing)

EQUITY
RSU Grant: $200,000 over 4 years
Annual Value:                    $50,000
--------------------------------
Equity Compensation:             $50,000/year

BENEFITS
401(k) Match (4%):               $6,000
Health Insurance:                $15,000 (employer portion)
HSA Contribution:                 $1,000
--------------------------------
Benefits Value:                  $22,000/year

PERKS
Vacation: 20 days (vs 10 standard)
  Extra 10 days × ~$575/day:      $5,750 value
Remote Work Savings:              $3,000 (commute, lunch)
Professional Dev:                 $2,000 budget
--------------------------------
Perks Value:                     $10,750/year

TOTAL YEAR 1:        $280,250
TOTAL ONGOING:       $255,250/year

Side-by-Side Comparison Template

markdown
# OFFER COMPARISON

|                          | Company A | Company B | Notes |
|--------------------------|-----------|-----------|-------|
| **CASH**                 |           |           |       |
| Base Salary              | $150,000  | $160,000  | B +$10K |
| Signing Bonus            | $25,000   | $10,000   | A +$15K |
| Target Bonus             | 15%       | 10%       | A +$6.5K |
| **Cash Total (Yr 1)**    | $197,500  | $186,000  | A +$11.5K |
|                          |           |           |       |
| **EQUITY**               |           |           |       |
| Grant Value (4yr)        | $200,000  | $300,000  | B +$100K |
| Annual Equity            | $50,000   | $75,000   | B +$25K |
|                          |           |           |       |
| **BENEFITS**             |           |           |       |
| 401(k) Match             | 4%        | 6%        | B +$3.2K |
| Health Insurance         | Good      | Premium   | B better |
| PTO                      | 20 days   | Unlimited | Varies |
|                          |           |           |       |
| **TOTAL COMP (Yr 1)**    | $280,250  | $285,000  | B +$4.7K |
| **TOTAL COMP (Ongoing)** | $255,250  | $275,000  | B +$19.7K |

Non-Monetary Factor Framework

Career Growth (Weight: High)

Questions to Consider:

  • Which role offers more learning?
  • Which company/brand helps future job search?
  • Which has better promotion track?
  • Which offers more scope/responsibility?
  • Which manager will develop you more?

Scoring:

Company A: Growth Score
- Learning opportunity: 8/10
- Brand/resume value: 7/10
- Promotion potential: 6/10
- Scope: 8/10
Average: 7.25/10

Company B: Growth Score
- Learning opportunity: 7/10
- Brand/resume value: 9/10
- Promotion potential: 8/10
- Scope: 7/10
Average: 7.75/10

Work-Life Balance (Weight: Personal)

Factors:

  • Expected hours
  • Remote/hybrid flexibility
  • Vacation usage culture
  • On-call requirements
  • Travel requirements
  • Commute time

Team & Culture (Weight: High)

Factors:

  • Manager quality (crucial!)
  • Team health/dynamics
  • Company culture fit
  • DEI considerations
  • Company stability/growth
  • Values alignment

Risk Assessment (Weight: Medium)

Startup vs. Established:

  • Funding runway
  • Market position
  • Company trajectory
  • Equity risk (could be worth $0)

Questions:

  • What happens if company struggles?
  • How stable is this role?
  • What's the severance policy?

Weighted Decision Matrix

Step 1: Define Your Priorities

Factor                  Weight
------------------------------------
Total Compensation       25%
Career Growth            25%
Work-Life Balance        20%
Team & Culture           20%
Location/Commute         10%
------------------------------------
Total:                   100%

Step 2: Score Each Factor

                    Company A   Company B
Factor              Score (1-10)
------------------------------------
Compensation        7           8
Career Growth       7           8
Work-Life           8           6
Team & Culture      9           7
Location            8           5

Step 3: Calculate Weighted Score

Company A:
(7 × 0.25) + (7 × 0.25) + (8 × 0.20) + (9 × 0.20) + (8 × 0.10)
= 1.75 + 1.75 + 1.60 + 1.80 + 0.80
= 7.70

Company B:
(8 × 0.25) + (8 × 0.25) + (6 × 0.20) + (7 × 0.20) + (5 × 0.10)
= 2.00 + 2.00 + 1.20 + 1.40 + 0.50
= 7.10

Result: Company A scores higher (7.70 vs 7.10)

Red Flags to Watch

In the Offer

  • ❌ Vague bonus language ("up to 20%")
  • ❌ Equity with no liquidity path
  • ❌ High base but no equity (at startup)
  • ❌ Cliff longer than 1 year
  • ❌ Vesting acceleration absent
  • ❌ Non-compete restrictions
  • ❌ Verbal promises not in writing

About the Company

  • ❌ High turnover (check LinkedIn)
  • ❌ Recent layoffs or reorgs
  • ❌ Manager seems checked out
  • ❌ Glassdoor patterns in bad reviews
  • ❌ Funding concerns
  • ❌ Unclear path to profitability

About the Role

  • ❌ Vague responsibilities
  • ❌ Role seems to change during interviews
  • ❌ Red flags in why position is open
  • ❌ No growth path discussed
  • ❌ Unrealistic expectations set

Questions to Ask Yourself

The Gut Check

  • Which offer excites me more?
  • Which would I regret not taking?
  • Which aligns with my 5-year goals?
  • Which would I brag about to friends?

The Monday Morning Test

  • Which job do I want to wake up for?
  • Which team do I want to work with?
  • Which problems do I want to solve?

The Learning Test

  • Where will I grow more?
  • Which skills will I develop?
  • Which looks better on my resume in 3 years?

The Risk Test

  • What's the downside of each?
  • Which failure would I regret more?
  • What's my backup plan for each?

Output Format

When comparing offers:

markdown
# JOB OFFER COMPARISON

## Offers Being Compared
- **Offer A:** [Role] at [Company]
- **Offer B:** [Role] at [Company]

## Total Compensation Comparison

| Component | Offer A | Offer B | Difference |
|-----------|---------|---------|------------|
| Base | $X | $X | |
| Bonus | $X | $X | |
| Equity (annual) | $X | $X | |
| Benefits | $X | $X | |
| **Year 1 Total** | $X | $X | |
| **Ongoing Total** | $X | $X | |

## Non-Monetary Comparison

| Factor | Offer A | Offer B | Notes |
|--------|---------|---------|-------|
| Career Growth | X/10 | X/10 | |
| Work-Life | X/10 | X/10 | |
| Team/Culture | X/10 | X/10 | |
| Risk Level | X/10 | X/10 | |

## Weighted Analysis

Using your priorities:
- Offer A Score: X.XX
- Offer B Score: X.XX

## Key Differences
1. [Key difference 1]
2. [Key difference 2]
3. [Key difference 3]

## Recommendation

Based on your stated priorities of [X, Y, Z], **Offer [A/B]** appears to be the stronger choice because:
- [Reason 1]
- [Reason 2]
- [Reason 3]

## Things to Clarify Before Deciding
- [ ] [Question for Company A]
- [ ] [Question for Company B]

## Negotiation Opportunities
- [Opportunity 1]
- [Opportunity 2]

Comparison Checklist

  • ✅ Calculated total comp (not just base)
  • ✅ Included equity with realistic valuation
  • ✅ Factored in benefits value
  • ✅ Considered tax implications
  • ✅ Weighted non-monetary factors
  • ✅ Assessed career growth potential
  • ✅ Evaluated team and manager quality
  • ✅ Checked company stability/risk
  • ✅ Aligned with personal priorities
  • ✅ Gut-checked the decision

Frequently asked questions

What does the Offer Comparison Analyzer AI skill do?

Compare multiple job offers side-by-side with total compensation analysis

Why use Offer Comparison Analyzer on TypingMind?

Because you install it once and use it with any model. Offer Comparison Analyzer is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Offer Comparison Analyzer in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/Paramchoudhary/ResumeSkills/tree/main/skills/offer-comparison-analyzer. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Offer Comparison Analyzer?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Offer Comparison Analyzer?

As many as you like. As long as a model supports skills, you can use Offer Comparison Analyzer with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Offer Comparison Analyzer AI skill free?

Yes. It is published on GitHub by Paramchoudhary under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

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