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cost-report

Generate a spending report from recorded AI usage, with token counts and USD costs grouped by model, agent, and processing tier. Check budget utilization, remaining funds, and alerts for a selected period.

OriginalShow the original description

Generate a cost report showing token usage and USD costs by agent and model

See how to install

Good for

  • Reviewing today's AI spending
  • Comparing costs across models and agents
  • Checking budget utilization and alerts
  • Reviewing spending by processing tier

Files included (1)

  • SKILL.md3.3 KB

SKILL.md (original)

Review the instructions the agent will receive before you install.

Cost Report

Generate a comprehensive cost report showing token usage, USD costs, and budget utilization for the specified period.

When to use

When you need to understand current spending -- how much each agent costs, which models consume the most budget, and whether you're on track to stay within budget.

Steps

  1. Retrieve usage -- call mcp__plugin_ruflo-core_ruflo__memory_search (or _list / _retrieve) on the cost-tracking namespace for the specified period (default: today). The memory_* tools route by namespace string; the agentdb_hierarchical-* tools do not (they route by tier working|episodic|semantic), so don't use them here. See ruflo-agentdb ADR-0001 §"Namespace convention" for the routing contract. 1a. Read measured booster data -- if docs/benchmarks/runs/latest.json exists, load it via Bash-shelled node -e 'console.log(JSON.stringify(JSON.parse(require("fs").readFileSync("docs/benchmarks/runs/latest.json")).summary))'. This provides Tier 1 measured values — booster cost/edit ($0), avg latency, win rate, plus any LLM baseline that was run (Gemini, Sonnet 4.6, Opus 4.7 latencies and per-edit costs). Use these in step 4 for the measured Tier breakdown rather than estimated.
  2. Compute costs -- for each record, calculate cost using model pricing:
    • Haiku: $0.25/M input, $1.25/M output
    • Sonnet: $3.00/M input, $15.00/M output
    • Opus: $15.00/M input, $75.00/M output
    • Include cache write/read costs where applicable
  3. Aggregate by model -- sum costs per model, compute percentage share
  4. Aggregate by tier -- classify each record as Tier 1 / Tier 2 / Tier 3 using three signals (in priority order): (a) bench data from step 1a — for any record that maps to a measured booster intent, use $0 / measured-latency directly; (b) the [AGENT_BOOSTER_AVAILABLE] flag stored by the cost-booster-route skill in cost-tracking; (c) the model name as fallback (haiku → Tier 2; sonnet/opus → Tier 3). Sum costs per tier, compute share, and count Tier 1 bypasses. The tier breakdown is the most actionable single line — it tells the user what fraction of Sonnet/Opus spend was Tier 1-eligible.
  5. Aggregate by agent -- sum costs per agent, include the model each agent used
  6. Check budget -- recall budget configuration via memory_retrieve and compute utilization percentage, check alert thresholds (50%/75%/90%/100%)
  7. Report -- display: total cost, budget remaining, tier breakdown (Tier 1 / Tier 2 / Tier 3), model breakdown, agent breakdown, active alerts. See REFERENCE.md §"Cost report shape" for the canonical layout.

CLI alternative

npx @claude-flow/cli@latest memory search --query "cost report for today" --namespace cost-tracking
npx @claude-flow/cli@latest memory list --namespace cost-tracking

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