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概要と使いどころ
Multi-cloud orchestration for ML workloads with automatic cost optimization. Use when you need to run training or batch jobs across multiple clouds, leverage spot instances with auto-recovery, or optimize GPU costs across providers.
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Reduce LLM API and infrastructure costs through model selection, prompt caching, batching, caching, quantization, and self-hosting strategies. Track spend by team and model, set budgets, and implement cost-aware routing.
日本語の概要は準備中です。原文の説明を表示しています。
Produce a scoped CCAM cost and token report by model, provider, source, and session. Use for spend reviews, model-mix analysis, unpriced usage detection, or export-friendly cost summaries.
日本語の概要は準備中です。原文の説明を表示しています。
Break down Claude Code usage by model family (Opus / Sonnet / Haiku) from the Agent Monitor dashboard — each family's share of tokens, share of cost, and the spots where an expensive model is doing cheap work. Pulls per-model token and cost splits from /api/pricing/cost, current rates from /api/pricing, fleet token totals from /api/analytics, and per-session model assignment from /api/sessions. Use when deciding model routing or whether to downshift work to a cheaper tier.
日本語の概要は準備中です。原文の説明を表示しています。
Review the configured cost alert rules and the alerts currently fired on the Agent Monitor dashboard, then explain exactly what tripped and why. Uses /api/alerts (fired feed) and /api/alerts/rules (definitions). Use when checking spend alerts or asking why a cost alarm went off.
日本語の概要は準備中です。原文の説明を表示しています。
Forecast Claude Code spend to the end of the week or month from the daily session trend on the Agent Monitor dashboard — moving average of daily spend × days remaining, added to spend-to-date. Uses /api/analytics daily_sessions, /api/pricing/cost, and /api/sessions for a per-day cost curve. Use when projecting cost or asking "where will my spend land".
日本語の概要は準備中です。原文の説明を表示しています。
Optimize Kubernetes costs through resource right-sizing, unused resource detection, and cluster efficiency analysis. Use for cost optimization, resource analysis, and capacity planning.
日本語の概要は準備中です。原文の説明を表示しています。
Evaluate, configure, and migrate workloads to AWS Lambda Managed Instances (LMI). Triggers on: Lambda Managed Instances, LMI, capacity provider, multi-concurrency Lambda, dedicated instance Lambda, EC2-backed Lambda, cold start elimination, Graviton Lambda, instance type for Lambda, scheduled scaling for LMI, Lambda cost optimization with Reserved Instances or Savings Plans. Also trigger when users describe high-volume predictable workloads seeking cost savings, want to scale LMI capacity on a schedule, or compare Lambda vs EC2 for steady-state traffic. For standard Lambda without LMI, use the aws-lambda skill instead.
日本語の概要は準備中です。原文の説明を表示しています。
Research budgeting and funding operations — study budget construction, cost per participant and per insight, burn against milestones, and portfolio prioritisation by decision value. Use when costing, tracking, or ranking research.
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Operational billing execution for legal matters. Monthly bill prep and billing instructions, LC invoice review and disbursement treatment, client billing query responses, cashflow modelling (LC payment obligations vs client receipts), and leverage and burn analysis (staffing mix, predicted total cost, margin trajectory). Trigger on: 'prepare the bill', 'billing instruction', 'end of month billing', 'LC invoice', 'local counsel invoice', 'pass through as disbursement', 'client querying the invoice', 'billing dispute', 'cashflow gap', 'when will we get paid', 'LC payment due', 'leverage analysis', 'staffing mix', 'predicted total cost', 'burn rate by grade', 'are we on track', 'what will this matter cost'.
日本語の概要は準備中です。原文の説明を表示しています。
Audit a project's infrastructure and SaaS stack, then produce a cost report showing what the user currently pays and what they would save by consolidating onto Temps (self-hosted or Temps Cloud). Detects hosting platforms (Vercel, Netlify, Railway, Render, Heroku, Fly.io), analytics (PostHog, Plausible, Mixpanel, Amplitude, Fathom), error tracking (Sentry, Bugsnag, Rollbar, Honeybadger), session replay (LogRocket, FullStory, Hotjar, Highlight), uptime monitoring (Pingdom, UptimeRobot, Better Stack, Checkly), managed databases (Supabase, Neon, PlanetScale, MongoDB Atlas, Upstash, RDS), and transactional email (SendGrid, Postmark, Resend, Mailgun) from dependencies, config files, and env var names. Use when the user wants to: (1) Know how much they would save by switching to Temps, (2) Audit their SaaS/infrastructure spend, (3) Compare their current stack's cost against self-hosting, (4) Decide whether Temps is worth it, (5) Build a business case for consolidating tools. Triggers: "how much would I save", "temps savings", "cost comparison", "audit my stack", "am I overpaying", "saas spend", "calculate savings", "is temps cheaper".
日本語の概要は準備中です。原文の説明を表示しています。
Autonomous cloud-cost analyst across Neon, Vercel, Railway and GitHub Actions - pulls per-object usage, attributes it to the biggest drivers, root-causes each, and emits recommendations ranked by real signal (idle %, over-allowance, failure rate) with dollar figures only where the billing API returns real ones (and, armed, applies safe cost levers).
日本語の概要は準備中です。原文の説明を表示しています。
Autonomous compute-reselling agent on Surplus Intelligence - resells free or low-cost provider compute across Bankr, AWS Bedrock, and Google Vertex (GCP) as one skill. Reads the live market + your cost + your usage, auto-lists your models per enabled provider, and reactively prices each offer to win routing within a cost floor, cap, and health guardrails.
日本語の概要は準備中です。原文の説明を表示しています。
Cloud cost optimization, token/API cost tracking, build time optimization, and FinOps patterns
日本語の概要は準備中です。原文の説明を表示しています。
Project-kickoff rubric for the self-host vs managed-cloud decision — when is running your own inference engine / LLM platform worth the ops cost vs paying per-token for a managed API? Decide on two axes — VOLUME (a cost-crossover slider) and COMPLIANCE (a hard gate). Use at kickoff when choosing where to run inference, or when cost / data-residency pressure forces a re-evaluation.
日本語の概要は準備中です。原文の説明を表示しています。
Multi-method cost basis computation including specific identification, FIFO, LIFO, HIFO, and proportional average cost with partial sell handling
日本語の概要は準備中です。原文の説明を表示しています。
Analyze construction budget variances. Compare estimated vs actual costs, identify trends, forecast final costs, and generate variance reports for cost control.
日本語の概要は準備中です。原文の説明を表示しています。
Calculate construction costs using resource-based method. Estimate project costs from work items, physical resource norms, and current prices.
日本語の概要は準備中です。原文の説明を表示しています。
Predict construction project costs using Machine Learning. Use Linear Regression, K-Nearest Neighbors, and Random Forest models on historical project data. Train, evaluate, and deploy cost prediction models.
日本語の概要は準備中です。原文の説明を表示しています。
Link schedule activities to cost items. Create cost-loaded schedules, generate cash flow curves, and track earned value.
日本語の概要は準備中です。原文の説明を表示しています。
Calculate construction costs using DDC CWICR resource-based methodology. Break down costs into labor, materials, equipment with transparent pricing.
日本語の概要は準備中です。原文の説明を表示しています。
Browse and search the OpenConstructionERP cost database: classification tree, SQL and semantic search, autocomplete, certainty badges, and the resource catalog. Use when a user wants to explore cost data without building a BOQ yet.
日本語の概要は準備中です。原文の説明を表示しています。
Load national and market cost bases into OpenConstructionERP: the 8 national bases (Turkey Birim Fiyat, China Dinge, Brazil SINAPI, Spain BCCA, Italy Prezzario Toscana, Greece GGDE, Vietnam Dinh Muc, Indonesia AHSP), the 30 global markets, and 48 PPP market catalogs per base. Use when importing a cost database, repricing into a market, or troubleshooting a load.
日本語の概要は準備中です。原文の説明を表示しています。
4D scheduling and 5D cost modelling in OpenConstructionERP: build task schedules, link tasks to BIM elements and BOQ lines, roll up the cost model over time, and export Gantt/sequence views. Use for schedule-cost integration workflows.
日本語の概要は準備中です。原文の説明を表示しています。