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model-cost-compare

Starter: compare model costs for a described task — maps task shape to the cheapest adequate seat and shows the price spread

plugins/nyldn/claude-octopus/skills/octopus-starter-pack/model-cost-compare/SKILL.md

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# Model Cost Comparison (Starter Pack)

Answer "which model should I use for this, and what will it cost?" with numbers instead of vibes.

## When to use

The user describes a task (bulk refactor, deep review, quick lookup, long-context analysis) and wants the cheapest seat that is still adequate.

## Steps

1. **Classify the task.** Bucket it: mechanical (rename, format), standard coding, hard reasoning (architecture, security review), long-context (>200K tokens input), or web research.
2. **Estimate volume.** Rough input/output token estimate from the described scope (files touched × average size; state the assumption).
3. **Price the roster.** Using the cost table in CLAUDE.md ($/MTok input/output), compute the estimated cost for each plausible seat: Claude Opus 5.5 (4/20 USD), Claude Opus 5 (5/25 USD), Claude Sonnet 5 (2/10 USD), Fable 5.1 (10/50 USD, 1M context, explicit-only), Codex GPT-5.6 Sol (4/20 USD), Terra (2/12 USD), Luna (0.20/1.20 USD), GPT-6 Astra (10/50 USD, explicit-only), Perplexity Sonar Pro (3/15 USD), and the included-cost seats (agy, copilot, ollama, cursor-agent) at 0 USD. For Astra requests above 272K input tokens, apply 2x input and 1.5x output pricing to the full request.
4. **Recommend one seat.** Pick the cheapest adequate option and defend it in two sentences. Mechanical work goes to included or budget seats; hard reasoning justifies the current Opus default at `high` effort; only a bounded judgment-class call (ambiguous architecture, API design, product tradeoffs) justifies Fable 5.1 at 10/50 USD per MTok.