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84
markit
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Productivity
credit-optimizer
Routes AI tasks by complexity and prompt quality to lower-cost model tiers, using task splitting, context pruning, output scoping, caching, and batch processing.
★ 50
GitHub Stars
78
Quality score
1
Files
About this Skill
Automatically optimize AI agent credit usage by routing tasks to the most cost-efficient execution path. Use when you want to reduce AI API costs by 30-75% without quality loss, classify task complexity before execution, route simple tasks to free or low-cost models, split complex tasks into optimized sub-tasks, or detect vague prompts before wasting credits.
Use cases
- Classifying tasks by complexity before execution
- Routing simple tasks to lower-cost models
- Splitting compound requests into sub-tasks
- Detecting vague prompts before execution
- Reducing context and output token usage
Features
- Task complexity classification
- Prompt clarity and scope checks
- Model tier routing guidance
- Context pruning and output scoping
- Caching and batch processing directives
Supported Agents
Skill files
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