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

vamseeachanta
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À propos

Cette compétence fournit un guide de sélection de modèle basé sur la complexité de la tâche, associant les tâches routinières à Haiku, les tâches standard à Sonnet et les tâches complexes à Opus. Elle aide les développeurs à optimiser les coûts en acheminant les tâches plus simples vers des modèles moins coûteux, tout en réservant les modèles puissants pour les travaux exigeants. Utilisez-la conjointement avec le mapping de routage lorsque la nature de la tâche est claire, afin de réduire l'écart entre l'efficacité théorique et l'efficacité observée en mise en œuvre.

Installation rapide

Claude Code

Recommandé
Principal
npx skills add vamseeachanta/workspace-hub
Commande PluginAlternatif
/plugin add https://github.com/vamseeachanta/workspace-hub
Git CloneAlternatif
git clone https://github.com/vamseeachanta/workspace-hub.git ~/.claude/skills/agent-usage-optimizer-complexity-tier-model-mapping

Copiez et collez cette commande dans Claude Code pour installer cette compétence

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

Dépôt GitHub

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

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