agent-usage-optimizer-complexity-tier-model-mapping
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
Recommendednpx skills add vamseeachanta/workspace-hub/plugin add https://github.com/vamseeachanta/workspace-hubgit clone https://github.com/vamseeachanta/workspace-hub.git ~/.claude/skills/agent-usage-optimizer-complexity-tier-model-mappingCopy 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 tier | Keywords | Recommended model |
|---|---|---|
routine | format, rename, config, scaffold, update-doc, copy | Claude Haiku |
standard | implement, review, test, fix, migrate, document | Claude Sonnet |
complex | architecture, design, cross-repo, security, compound | Claude 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
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