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cost-optimize

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UpdatedMay 20, 2026 at 11:12

Analyze token usage patterns and recommend cost optimizations with estimated savings

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jpoindexter

jpoindexter/theft-kit

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Software DevelopersComputer and Mathematical Occupations·SOC 15-1252

SKILL.md

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name	cost-optimize
description	Analyze token usage patterns and recommend cost optimizations with estimated savings
argument-hint
allowed-tools	mcp__claude-flow__agentdb_hierarchical-recall mcp__claude-flow__agentdb_pattern-search mcp__claude-flow__agentdb_pattern-store mcp__claude-flow__agentdb_semantic-route Bash

Cost Optimize

Analyze recent token usage across agents and models, identify waste, and recommend specific optimizations with estimated dollar savings.

When to use

When costs are higher than expected or you want to proactively reduce spending. Analyzes model selection efficiency, cache utilization, agent redundancy, and prompt efficiency.

Steps

Load usage data -- call mcp__claude-flow__agentdb_hierarchical-recall to fetch recent token usage records from cost-tracking namespace (last 7 days)
Analyze model fit -- for each agent, assess whether the model tier matches task complexity:
- Agents doing simple tasks (formatting, linting) on Sonnet/Opus -> suggest Haiku or Agent Booster
- Agents doing complex tasks (architecture, security) on Haiku -> flag quality risk
Check cache rates -- compute cache hit rate per agent; if below 60%, recommend enabling or improving prompt caching (90% cost reduction on cache reads)
Detect redundancy -- look for multiple agents performing overlapping tasks, or agents being spawned for work that could be batched
Estimate savings -- for each recommendation, calculate: current cost, projected cost after optimization, dollar savings, percentage reduction
Search patterns -- call mcp__claude-flow__agentdb_pattern-search for previously successful optimizations
Store recommendations -- call mcp__claude-flow__agentdb_pattern-store to record optimization recommendations in cost-patterns namespace
Report -- display: ranked recommendations with savings estimate, total potential savings, implementation priority (quick wins first)

CLI alternative

npx @claude-flow/cli@latest memory search --query "cost optimization strategies" --namespace cost-patterns

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Cost Optimize

Analyze recent token usage across agents and models, identify waste, and recommend specific optimizations with estimated dollar savings.

When to use

When costs are higher than expected or you want to proactively reduce spending. Analyzes model selection efficiency, cache utilization, agent redundancy, and prompt efficiency.

Steps

Load usage data -- call mcp__claude-flow__agentdb_hierarchical-recall to fetch recent token usage records from cost-tracking namespace (last 7 days)

Analyze model fit -- for each agent, assess whether the model tier matches task complexity:

Agents doing simple tasks (formatting, linting) on Sonnet/Opus -> suggest Haiku or Agent Booster
Agents doing complex tasks (architecture, security) on Haiku -> flag quality risk

Check cache rates -- compute cache hit rate per agent; if below 60%, recommend enabling or improving prompt caching (90% cost reduction on cache reads)

Detect redundancy -- look for multiple agents performing overlapping tasks, or agents being spawned for work that could be batched

Estimate savings -- for each recommendation, calculate: current cost, projected cost after optimization, dollar savings, percentage reduction

Search patterns -- call mcp__claude-flow__agentdb_pattern-search for previously successful optimizations

Store recommendations -- call mcp__claude-flow__agentdb_pattern-store to record optimization recommendations in cost-patterns namespace

Report -- display: ranked recommendations with savings estimate, total potential savings, implementation priority (quick wins first)

CLI alternative

npx @claude-flow/cli@latest memory search --query "cost optimization strategies" --namespace cost-patterns