model-cost-compare

Compares LLM seat costs for a described task and recommends the cheapest adequate model.

4.0k|375|Updated Jan 15, 2026
One-click install
npx skills add https://github.com/nyldn/claude-octopus --skill model-cost-compare
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: model-cost-compare
Source: https://github.com/nyldn/claude-octopus/tree/main/skills/octopus-starter-pack/model-cost-compare
Command: npx skills add https://github.com/nyldn/claude-octopus --skill model-cost-compare

SYSTEM DOCUMENTATION & REQUIREMENTS

What problem does it solve?

Choosing which LLM to run a task on is often guesswork, leading to overspending on premium models for mechanical work or under-provisioning hard reasoning tasks. This Skill turns a described task into concrete dollar estimates across the available model roster.

Core Features & Use Cases

  • Task Classification: Buckets work into mechanical, standard coding, hard reasoning, long-context, or web research categories.
  • Cost Estimation: Computes per-model dollar estimates from token volume assumptions and a price table covering Claude Opus 5, Sonnet 5, Fable 5, Codex GPT-5.6, Terra, Luna, Perplexity Sonar Pro, and zero-cost seats.
  • Risk-Aware Recommendation: Escalates to Opus 5 for security-sensitive code, API contracts, release artifacts, or breaking changes, and shows a three-row spread of recommended, cheaper, and premium options.
  • Use Case: Before dispatching a bulk refactor across 40 files, ask for a cost comparison to learn that an included-cost seat handles it for $0 instead of spending dollars on Opus.

Quick Start

Ask the assistant to compare model costs for a bulk rename across 30 files and recommend the cheapest adequate seat with a price spread.

Frequently Asked Questions about model-cost-compare

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I choose the cheapest LLM for a coding task?▼

Classify the task first: mechanical work like renames goes to included-cost or budget seats, standard coding fits mid-tier models, and hard reasoning justifies premium seats. Then estimate token volume from files touched and compute cost per model using the price table.

How do I estimate LLM API costs before running a task?▼

Estimate input and output tokens from the task scope, such as files touched multiplied by average size, then multiply by each model's per-million-token input and output rates. State your volume assumptions explicitly so the estimate is auditable.

When should I use a premium model instead of a cheap one?▼

Escalate to a premium seat like Opus 5 when the task touches API or schema contracts, security-sensitive code, CI configuration, release artifacts, user-facing UI, new modules, or breaking changes. Cheap-seat agreement never settles judgment-class decisions.

Can I use the most expensive model for security audits?▼

Not always. Fable 5 is explicitly excluded from security audits because its safety classifiers can refuse offensive-security phrasing; security review goes to Opus 5 instead. Price alone does not determine fitness for sensitive task types.

What are the limitations of LLM cost estimation?▼

Estimates depend on rough token volume assumptions, so actual costs vary with real context sizes and retry counts. The skill flags any estimate exceeding $1 before dispatch, but it cannot predict exact billing for open-ended tasks.