'cost-tracking' 검색 결과

Capture token usage from Claude Code session logs, calculate USD costs using the supplied pricing reference, and save structured records to AgentDB. Review totals by model and tier, and provide data for cost reports.

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• Record costs after a block of work
• Save final usage totals at session end
• Capture usage periodically during long sessions

Track production session spending over time by grouping costs into configurable time windows. Compare the latest window with earlier spending averages, display the increase, and optionally return a failure exit code when it exceeds a chosen percentage.

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• Reviewing daily production spending
• Comparing recent spending with historical averages
• Adding spending acceleration alerts to CI

Compare actual AI session costs with estimates for using only Haiku, Sonnet, or Opus. The skill reports savings amounts and percentages, helping teams assess model selection costs while leaving differences in answer quality and retries outside the calculation.

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• Report model selection savings during cost reviews
• Check savings after changing model selection settings
• Use JSON results to enforce a savings threshold in CI

Export recorded AI usage costs and budgets as Prometheus metrics or JSON. Feed external dashboards with totals, model tier breakdowns, session costs, and budget utilization, or send the same data to a webhook endpoint.

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• Refreshing cost metrics for Grafana or Prometheus
• Sending a one-time cost report to a webhook
• Providing budget utilization data for monitoring

Track and report Claude Code token usage, spending, and budgets from a local cost-tracking database. Use when the user asks about costs, spending, usage, tokens, budgets, or cost breakdowns by project, tool, session, or date.

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Claude Code의 로컬 사용 로그에서 토큰 사용량과 예상 비용을 집계합니다. 모델·세션·날짜별 비용을 확인하고 예산과 비교하며 CSV로 내보낼 수 있습니다.

• 오늘과 어제의 지출 비교
• 모델·세션별 비용 확인
• 예산과 지출 비교

Compare recorded agent spending with a project budget and receive alerts at four usage thresholds. Review remaining funds and recommended actions, or use the check to block agent launches when the budget is exhausted.

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• Check budget usage after recording costs
• Review remaining funds before launching agents
• Monitor spending at regular intervals

Identify individual sessions with unusually high or low spending using the median and MAD, a measure of spread around it. Filter by time period, adjust detection thresholds, and optionally return a failure exit code for automated checks.

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• Find sessions with unusually high spending
• Check sessions with unusually low spending
• Review spending anomalies over the past week

Estimate future spending from recent usage costs, with projections for 7, 30, 90, and 365 days. When a budget is configured, see how many days remain before spending reaches key budget thresholds.

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• Planning spending against a quarterly budget
• Feeding cost projections into a budget dashboard
• Stopping builds when budget exhaustion is near

Analyze the last seven days of agent and model token usage to identify unnecessary spending. Recommend changes to model selection, prompt caching, and overlapping work, with estimated dollar savings, percentage reductions, and implementation priorities.

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• Investigating higher-than-expected AI costs
• Matching model choices to task complexity
• Reviewing prompt caching efficiency

Review AI agent spending by conversation, with each session’s start time, message count, main model, and total cost. Use the results to identify expensive sessions and understand typical costs before planning longer work.

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• Review spending across completed conversations
• Identify conversations with high costs
• Estimate typical costs before a long session

Assess tasks before execution to identify transformations eligible to skip LLM calls. Report the eligible share, recommended models for remaining tasks, and estimated upper costs, then save the routing results for later cost reports.

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• Assess similar tasks before a batch run
• Review LLM spending on simple code transformations
• Check the share eligible for Agent Booster

Retrieve a single snapshot of recorded AI costs, including total spending, model breakdowns, the highest-cost session, and budget usage. Export JSON for scripts and dashboards, or Markdown for a quick review.

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• Reviewing total spending and budget usage
• Checking costs by model and model tier
• Fetching cost data for a dashboard

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.

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

Inspect local AI coding session logs with agenttrace to identify cost spikes, delays, failed tools, and retry loops. Produce readable reports, compare attempts, and configure automated checks for unusual or unhealthy runs.

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• Investigate slow or expensive AI coding sessions
• Review failed runs before retrying
• Compare tool usage and verification across attempts

Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

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Implement comprehensive observability for LLM applications including tracing (Langfuse/Helicone), cost tracking, token optimization, RAG evaluation metrics (RAGAS), hallucination detection, and production monitoring. Essential for debugging, optimizing costs, and ensuring AI output quality. Use when ", llm-monitoring, tracing, langfuse, helicone, cost-tracking, ragas, evaluation, hallucination-detection, prompt-caching" mentioned.

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Manage construction contract administration from the field perspective. Covers AIA contract forms (A101, A201, A401), bond types and requirements, mechanics lien law, insurance verification, indemnification, dispute resolution, and subcontractor default procedures. Provides practical field guidance for notice requirements, lien waiver processing, COI verification, and claims documentation. Integrates with pay-application (lien waivers), change-order-tracker (constructive changes), delay-tracker (notice provisions), sub-performance (default triggers), and cost-tracking (back-charges). Triggers: "contract", "contract admin", "AIA", "A201", "A101", "bond", "performance bond", "payment bond", "lien", "lien waiver", "mechanics lien", "insurance", "COI", "certificate of insurance", "OCIP", "CCIP", "indemnification", "dispute", "mediation", "arbitration", "notice", "cure notice", "default", "sub default", "termination for cause", "claims", "ConsensusDocs", "EJCDC".

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Install genuine per-session cost tracking for Claude Code by wiring bundled logger scripts into the user's statusline — preserving any existing statusline and hooks. Use when the user asks to set up, install, enable, or repair cost tracking / cost logging / session cost capture. Idempotent; safe to re-run.

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Track real-time API cost accrual during LLM execution. Activate on 'cost tracking', 'token usage', 'API costs', 'budget monitoring', 'usage metrics'. NOT for cost estimation, pricing tiers, or billing systems.

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Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

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Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Expert en observabilité des agents IA (tracing, logging, suivi des coûts, latence, métriques qualité)

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Audit local AI coding-agent sessions with agenttrace for cost, tool failures, latency, anomalies, health, diffs, and CI gates.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.