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agent-usage-optimizer-complexity-tier-model-mapping

vamseeachanta
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About

This skill provides a model selection guide based on task complexity, mapping routine tasks to Haiku, standard tasks to Sonnet, and complex tasks to Opus. It helps developers optimize costs by routing simpler tasks to cheaper models while reserving powerful models for demanding work. Use it alongside route mapping when the task nature is clear to close the gap between theoretical and observed implementation efficiency.

Quick Install

Claude Code

Recommended
Primary
npx skills add vamseeachanta/workspace-hub
Plugin CommandAlternative
/plugin add https://github.com/vamseeachanta/workspace-hub
Git CloneAlternative
git clone https://github.com/vamseeachanta/workspace-hub.git ~/.claude/skills/agent-usage-optimizer-complexity-tier-model-mapping

Copy and paste this command in Claude Code to install this skill

Documentation

Complexity Tier → Model Mapping

Complexity Tier → Model Mapping

Use this alongside Route mapping when task nature is clear:

Complexity tierKeywordsRecommended model
routineformat, rename, config, scaffold, update-doc, copyClaude Haiku
standardimplement, review, test, fix, migrate, documentClaude Sonnet
complexarchitecture, design, cross-repo, security, compoundClaude Opus

Key insight: the gap between theoretical and observed exposure is an implementation gap — not a capability gap. Routing routine tasks to cheaper models closes this gap for our workflow. See WRK-5002 to automate tier detection in task_classifier.sh.


Use this skill before any multi-item work session or when quota is a concern. Related: ai/optimization/model-selection, ai/optimization/usage-optimization

GitHub Repository

vamseeachanta/workspace-hub
Path: .claude/skills/ai/agent-usage-optimizer/complexity-tier-model-mapping

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