25 skills · sorted by relevance
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.
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.
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.
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.
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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Summarize Claude Code token usage and estimated spending from the local ECC metrics log. Review costs by model, session, or date, compare spending with budgets, and export records to CSV while avoiding duplicate counting of session totals.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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Expert en observabilité des agents IA (tracing, logging, suivi des coûts, latence, métriques qualité)
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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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