「cost」の検索結果

Explore and debate options with fresh documentation and research before committing. Use when facing a real decision with multiple plausible approaches — library/framework choice, architecture call, API or schema design, algorithm selection, or any communication / strategy call where being wrong has cost. Enumerates relevant research domains, looks up current docs and evidence-based methods, weighs options on correctness and elegance, resists bloat. Do NOT use for divergent ideation (brainstorm), extracting user intent (elicit), or reviewing already-written code (quality-review).

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。

Master AI-integrated development environments with comprehensive coverage of Windsurf, Cursor, Antigravity, Zed, Cline, and FOSS newcomers, including intelligent usage patterns, cost optimization, and the evolution toward fully agentic development

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。

Shifts Layer 3 model selection to cost-optimized alternatives when economy mode is active.

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。

Master the `agentbrain` CLI (npm package `agentbrain-cli`). Use this skill whenever the user runs, installs, configures, or asks about `agentbrain` commands; when they interact with the AgentBrain enterprise data hub — organizations, connectors, knowledge bases, workflows, media/documents, knowledge graph, permissions, LLM/prompt config, cost & usage, governance, audit logs; when uploading documents/files to AgentBrain (`agentbrain media upload`); when authenticating (login/logout/token/apiKey); when retrieving MCP context (`agentbrain retrieve-context`); when running SQL against a connector; when the user pastes any `agentbrain …` command; when they edit `~/.agentbrain/config.json`; or when they mention AgentBrain, agent-brain, agentbrain-cli, or the `.agentbrain` folder.

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。

AI เชฟครัวร้านอาหาร — menu development, kitchen brigade, mise en place, food cost, seasonal menu, HACCP, Thai culinary context

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。

AI pastry chef — sourdough, lamination (croissant), cake decoration, recipe scaling, food cost, HACCP, Thai climate baking

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。

ผู้จัดการร้านอาหาร — food cost (28-32%), labor (25-30%), menu engineering, inventory, staffing, ROI สาขา

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。

Integrate LLM API RAG fine-tuning prompt engineering พร้อมคุม token cost และกัน prompt injection

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 Architect — AWS/GCP/Azure solution design, cost optimization, HA/DR, multi-region, IaC (Terraform/CDK), Well-Architected Review

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。

Work with Runpod GPU infrastructure and documentation. Use when Codex needs to create, deploy, manage, debug, or review Runpod Pods, Serverless workers/endpoints, templates, network volumes, Public Endpoints, Flash apps, runpodctl commands, Runpod Python SDK usage, REST/GraphQL API usage, Runpod MCP setup, Docker images for Runpod, endpoint request payloads, logs, billing/cost checks, or Runpod deployment troubleshooting.

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。

Codified expertise for electricity and gas procurement, tariff optimization, demand charge management, renewable PPA evaluation, and multi-facility energy cost management. Informed by energy procurement managers with 15+ years experience at large commercial and industrial consumers. Includes market structure analysis, hedging strategies, load profiling, and sustainability reporting frameworks. Use when procuring energy, optimizing tariffs, managing demand charges, evaluating PPAs, or developing energy strategies.

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。

Use when the user asks to make something faster, try many variants, run recursive optimization, benchmark latency/throughput/cost, or choose the best implementation by repeated measured tests.

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。

Head-to-head comparison of coding agents (Claude Code, Aider, Codex, etc.) on custom tasks with pass rate, cost, time, and consistency metrics

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。

Operate as an agentic engineer using eval-first execution, decomposition, and cost-aware model 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。

Show where this machine's Claude Code tokens went - cost by token type, context tax per tool, biggest tool outputs.

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。

Use when the user asks to measure command execution time or optimize a feedback loop. Records explicit measurements and recommends faster alternatives such as unit tests versus integration tests. It is opt-in; it does not run on every command.

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。

Commercial and residential cleaning business operations agent. Covers pricing, bidding, staffing, supply costs, insurance, OSHA compliance, quality control, and growth from solo operator to multi-c...

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 cloud infrastructure spend across AWS, Azure, and GCP. Identify waste, rightsizing opportunities, and reserved instance savings.

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。

Routes LLM requests to a local model first (Ollama, LM Studio, llamafile), validates the response quality, and escalates to cloud only when the local result fails. Tracks local vs escalated vs cloud outcomes in a persistent dashboard. Use when: (1) user asks to run a task with a local model first, (2) user wants to reduce cloud API costs or keep requests private, (3) user wants post-outcome quality validation before committing to a local result, (4) user asks to see token savings or the routing dashboard, (5) any request where local-vs-cloud routing should be decided automatically with a quality gate. Supports Ollama, LM Studio, and llamafile as local providers.

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。

Generate AI music using ACE-Step 1.5 via ACE Music's free API. Use when the user asks to create, generate, or compose music, songs, beats, instrumentals, or audio tracks. Supports lyrics, style prompts, covers, and repainting. Free API, no 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。

Design, configure, debug, and optimize OpenClaw AI agent deployments. Master guide for gateway configuration, openclaw.json settings, model routing and fallback chains, skills development and publishing, cron job scheduling, memory systems (Qdrant, Neo4j, SQLite), Docker infrastructure, and Tailscale VPN networking. Includes config analyzer that audits your openclaw.json and suggests improvements, plus health checker that validates all OpenClaw subsystems. Built for AI agents — Python stdlib only, no dependencies. Use for OpenClaw setup, gateway debugging, skill building, cron management, model optimization, cost reduction, and infrastructure troubleshooting.

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 ROI for AI-as-a-Service (managed AI agents). Estimates cost savings, efficiency gains, and payback period for deploying AI agents across business operations. Use when evaluating whether managed AI agents make financial sense for a company.

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。

Prepare Azure environments and prerequisites before deployment. Use this skill when users ask for readiness checks, environment setup, or preflight planning. Covers landing zones, networking, identity, governance, and cost controls per Cloud Adoption Framework.

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。

AI Agent 成本工程 — 基於 Claude Code 的成本追蹤、prompt cache 最佳化、token 預算控制逆向分析。Use when: 優化 token 消耗、設計成本控制機制、分析 cache 效率、選擇模型配置。

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。