Agent Skills: AI Cost Check

Calculate AI feature costs and challenge if you actually need it. Invokes ai-cost-analyzer agent for detailed economics modeling.

UncategorizedID: breethomas/pm-thought-partner/ai-cost-check

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pnpm dlx add-skill https://github.com/breethomas/pm-thought-partner/tree/HEAD/skills/ai-cost-check

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skills/ai-cost-check/SKILL.md

Skill Metadata

Name
ai-cost-check
Description
Calculate AI feature costs and challenge if you actually need it. Invokes ai-cost-analyzer agent for detailed economics modeling.

AI Cost Check

Before you build an AI feature, answer two questions:

  1. Do you actually need this feature?
  2. Can you afford it?

Most PMs skip #1 and regret #2 later.

Entry Point

When this skill is invoked, start with:

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 AI COST CHECK
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AI features have marginal costs that scale with usage.
Model this BEFORE building, not after launch.

What AI feature are you considering?

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Usage

/ai-cost-check [feature-name]

Examples:

  • /ai-cost-check "product recommendations" - Calculate recommendation costs
  • /ai-cost-check "email composer" - Model email generation economics
  • /ai-cost-check --compare - Compare cost across different models

What Happens

  1. Invokes the ai-cost-analyzer agent
  2. Challenges the premise first - Do you have evidence users want this?
  3. Models the economics - Cost per request, cost at scale, % of revenue
  4. Provides a verdict - Sustainable, viable but expensive, or unsustainable
  5. Shows optimization paths - Caching, model selection, prompt optimization

The Philosophy

AI products have marginal costs that scale with usage. Every user interaction costs money. Model this BEFORE building, not after launch when you're hemorrhaging cash.

Cost Thresholds

| AI Cost as % of Revenue | Status | Recommendation | |-------------------------|--------|----------------| | <15% | Sustainable | Build it | | 15-30% | Viable | Build with optimization plan | | >30% | Unsustainable | Don't build (or fundamentally rethink) |

What You'll Get

FEATURE DETAILS:
- Model: GPT-4 Turbo
- Calls per recommendation: 1
- Input: 1,500 tokens
- Output: 300 tokens

COST BREAKDOWN:
Per request: $0.024
Per user/month: $2.16

| Scale | Monthly Cost | Your Revenue | AI % of Revenue |
|-------|-------------|--------------|-----------------|
| 100   | $216        | $2,000       | 10.8%           |
| 10K   | $21,600     | $200,000     | 10.8%           |

VERDICT: Sustainable at 10.8% of revenue

OPTIMIZATION PATHS:
1. Caching (saves 40-60%): $8,640/month at 10K users
2. Model selection (saves 70%): Use GPT-3.5 for simple cases

Model Price Reference (January 2025)

| Model | Input | Output | |-------|-------|--------| | GPT-4 Turbo | $0.01/1K | $0.03/1K | | GPT-4o | $0.005/1K | $0.015/1K | | GPT-3.5 Turbo | $0.0005/1K | $0.0015/1K | | Claude 3.5 Sonnet | $0.003/1K | $0.015/1K | | Claude 3 Haiku | $0.00025/1K | $0.00125/1K |

Related Commands

  • /ai-health-check - Full pre-launch readiness audit
  • /four-risks - Includes viability (business model) risk
  • /pmf-survey - Validate willingness to pay

Key insight: "Most AI features are solutions looking for problems. Validate the problem before modeling costs."