agentdb-advanced
Master advanced AgentDB features including QUIC synchronization, multi-database management, custom distance metrics, hybrid search, and distributed systems…
Analyze token usage patterns and recommend cost optimizations with estimated savings
$ npx -y skills add ruvnet/ruflo --skill cost-optimize --agent claude-codeHow it fires
How this skill gets triggered: by you, by Claude, or both.
/cost-optimizeContext preview
The summary Claude sees to decide when to auto-load this skill.
Analyze token usage patterns and recommend cost optimizations with estimated savings
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
Analyze recent token usage across agents and models, identify waste, and recommend specific optimizations with estimated dollar savings.
When costs are higher than expected or you want to proactively reduce spending. Analyzes model selection efficiency, cache utilization, agent redundancy, and prompt efficiency.
1. **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). 2. **Analyze model fit** -- for each agent, assess whether the model tier matches task complexity:
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 prior optimization patterns** -- call `mcp__plugin_ruflo-core_ruflo__agentdb_pattern-search` (ReasoningBank-routed; **don't** pass a `namespace` argument — pattern-* tools ignore it). 7. **Store the optimization pattern** -- two paths:
8. **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"). 9. **Report** -- display: ranked recommendations with savings estimate, total potential savings, implementation priority (quick wins first), and any model-outcome events emitted in step 8
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-patternsAn agent meta-harness for Claude Code and Codex. 📖 RuFlo Explained — Build an AI Team That Plans, Remembers, Tests, and Improves A 14-chapter guide: from the basic idea to a first useful task, then memory, agent teams, plugins, cost and verification.
Repo: ruvnet/ruflo
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