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cost-optimize

Analyze token usage patterns and recommend cost optimizations with estimated savings

DeepseekModel Curated skill Quality Excellent · 90 v1.0.0

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Download .skill Standard format with system_prompt and model_config, ready for any agent framework
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name cost-optimize description Analyze token usage patterns and recommend cost optimizations with estimated savings argument-hint allowed-tools mcp__plugin_ruflo-core_ruflo__memory_search mcp__plugin_ruflo-core_ruflo__memory_list mcp__plugin_ruflo-core_ruflo__memory_store mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search mcp__plugin_ruflo-core_ruflo__agentdb_pattern-store mcp__plugin_ruflo-core_ruflo__agentdb_semantic-route mcp__plugin_ruflo-core_ruflo__hooks_model-outcome 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__plugin_ruflo-core_ruflo__memory_search on the cost-tracking namespace (last 7 days). The memory_* tools route by namespace; use them — not agentdb_hierarchical-* (which routes by tier). 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 prior optimization patterns -- call mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search (ReasoningBank-routed; don't pass a namespace argument — pattern-* tools ignore it). Store the optimization pattern -- two paths: Pattern store (typed, recommended) : mcp__plugin_ruflo-core_ruflo__agentdb_pattern-store with type: 'cost-optimization' . Don't pass a namespace arg — ReasoningBank routes it; on bridge unavailability the fallback writes to the reserved pattern namespace with controller: 'memory-store-fallback' (see ruflo-agentdb ADR-0001). Plain store (namespace-routable) : mcp__plugin_ruflo-core_ruflo__memory_store --namespace cost-patterns — this DOES respect the cost-patterns namespace because memory_* is namespace-routed. Close the routing feedback loop — auto-emit hooks_model-outcome -- for each downgrade recommendation, format the outcome-emit command as part of the recommendation table so it can be run directly: # success path (downgrade worked) node plugins/ruflo-cost-tracker/scripts/outcome.mjs "<task-description>" <model> success # escalated path (had to upgrade after downgrade attempt) node plugins/ruflo-cost-tracker/scripts/outcome.mjs "<task-description>" <model> escalated The script wraps npx @claude-flow/cli hooks model-outcome -t ... -m ... -o ... with explicit-argv spawnSync so quoting is safe. Without this signal the router does not learn from cost-tracker's recommendations and the booster bypass rate (see cost-booster-route skill) does not improve over time. This is the typed equivalent of the legacy routing-outcomes namespace (see ruflo-intelligence ADR-0001 §"Neutral"). Report -- display: ranked recommendations with savings estimate, total potential savings, implementation priority (quick wins first), and any model-outcome events emitted in step 8 CLI alternative npx @claude-flow/cli@latest memory search --query "cost optimization strategies" --namespace cost-patterns npx @claude-flow/cli@latest memory store --key "opt-2026-05-04" --value '{...}' --namespace cost-patterns
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Field Description
formatFormat tag (skill/v1)
skill_idUnique skill ID
nameSkill name
versionVersion
descriptionDescription
categoryCategories (array)
trigger_wordsTrigger words
tagsTags
sourceSource
source_urlSource URL (this page)
exported_atExported at (set per download)
system_promptSystem prompt body
model_configModel config: provider / model / temperature / max_tokens / top_p
examplesExamples
install_guideImport guide for Coze / Dify / Claude / custom frameworks
The same skill can be exported in different platform formats.
.skill Standard format with system_prompt and model_config, ready for any agent framework Download
.skillpro Enhanced format with scripts, tools, dependencies and hooks Download
.json Plain JSON export with system_prompt and model parameters only Download
Coze Markdown with frontmatter, for Coze platform import Download
Dify Dify DSL, import directly after creating an app Download

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