Cost Optimize

When to use

Steps

1. Load usage data -- call

   mcp__claude-flow__agentdb_hierarchical-recall

   to fetch recent token usage records from

   cost-tracking

   namespace (last 7 days)
2. 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
3. Check cache rates -- compute cache hit rate per agent; if below 60%, recommend enabling or improving prompt caching (90% cost reduction on cache reads)
4. Detect redundancy -- look for multiple agents performing overlapping tasks, or agents being spawned for work that could be batched
5. Estimate savings -- for each recommendation, calculate: current cost, projected cost after optimization, dollar savings, percentage reduction
6. Search patterns -- call

   mcp__claude-flow__agentdb_pattern-search

   for previously successful optimizations
7. Store recommendations -- call

   mcp__claude-flow__agentdb_pattern-store

   to record optimization recommendations in

   cost-patterns

   namespace
8. 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