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

vamseeachanta
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Esta habilidad proporciona una guía de selección de modelos basada en la complejidad de la tarea, asignando tareas rutinarias a Haiku, tareas estándar a Sonnet y tareas complejas a Opus. Ayuda a los desarrolladores a optimizar costos dirigiendo tareas más simples a modelos más económicos, mientras reserva modelos potentes para trabajos exigentes. Úsela junto con el mapeo de rutas cuando la naturaleza de la tarea sea clara, para cerrar la brecha entre la eficiencia teórica y la observada en la implementación.

Instalación rápida

Claude Code

Recomendado
Principal
npx skills add vamseeachanta/workspace-hub
Comando PluginAlternativo
/plugin add https://github.com/vamseeachanta/workspace-hub
Git CloneAlternativo
git clone https://github.com/vamseeachanta/workspace-hub.git ~/.claude/skills/agent-usage-optimizer-complexity-tier-model-mapping

Copia y pega este comando en Claude Code para instalar esta habilidad

Documentación

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

Repositorio GitHub

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

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