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Cost-Aware LLM Pipeline

poraffaan-m·affaan-m· v1.0.0 · atualizado em 2026-04-10

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Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching.

llmcost-optimizationmodel-routingprompt-cachingretry-logicapi-usagebudget-tracking

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Documento do Skill

SKILL.mdcost-aware-llm-pipeline/workflow

Determine Task Complexity: — Analyze input text length and item count.

Select Model: — Route to appropriate LLM (Haiku, Sonnet, Opus) based on complexity.

Check Budget: — Ensure the call is within the defined budget limits.

Build Cached Messages: — Utilize prompt caching for system prompts.

Call LLM API: — Execute the API call with retry logic for transient errors.

Track Cost: — Record input/output tokens and cost in an immutable tracker.

Telemetria de Agentes

Execuções

total

Taxa de Sucesso

últimos 30d

Latência Média

0.0s

p50

Alucinação

0.0%

detecção

Tokens Entrada

avg 0/exec

Tokens Saída

avg 0/exec

Uso por Plataforma

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Árvore do Skill

Cost-Aware LLM Pipeline

cost-aware-llm-pipeline

Fases Cognitivas5

1.SENSE

2.CONTEXTUALIZE

3.ACT

4.EVALUATE

5.REFLECT

Triggers8

optimize LLM API costsimplement model routing for LLMstrack LLM spendingadd retry logic to LLM callscache LLM promptsreduce LLM inference costsbuild a cost-aware LLM pipelineuse cheaper models for simple tasks

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Score Breakdown

⭐Avaliação Humana0%

🤖Sucesso de Agentes0%

🕐Atualidade100%

🔗Saúde de Dependências100%

🕸️Centralidade no Grafo0%

🛡️Segurança50%

CompositeScore = α·Humano + β·Agente + γ·Recência + δ·Deps + ε·Centralidade + ζ·Segurança

Instalação

$ synaptic mcp download cost-aware-llm-pipeline

$ synaptic skills detail cost-aware-llm-pipeline

$ synaptic skills live cost-aware-llm-pipeline

Dependências

anthropic dataclasses time

Links

GitHub Repository