「usage」の検索結果

Track and analyze US government shutdown liquidity impacts by monitoring TGA (Treasury General Account), bank reserves, EFFR, and SOFR data from FRED API. Use when user wants to (1) analyze current or past government shutdown effects on financial markets, (2) track liquidity conditions during fiscal policy disruptions, (3) assess "stealth tightening" effects, (4) compare shutdown episodes across different monetary policy regimes (QE vs QT), or (5) generate liquidity stress reports with historical context. Recommended usage frequency is weekly on Wednesdays after TGA/reserve data releases.

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。

Alibaba Cloud API reference for developing aero-cli. Use this skill when adding new cloud provider features, fixing API calls, or extending FC/RDS/Redis/OSS/DNS/VPC integrations. Contains SDK usage patterns, API signatures, and error handling conventions specific to this project.

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。

Manage Alibaba Cloud CDN using the @alicloud/cdn20180510 TypeScript SDK. Use when working with CDN domain acceleration, domain configuration, SSL certificates, cache refresh/prefetch, real-time monitoring, traffic analysis, log management, usage/billing, IP tools, Function Compute triggers, delivery tasks, and resource tagging. Covers all 168 APIs of the CDN 20180510 version.

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。

Java coding standards for Spring Boot services: naming, immutability, Optional usage, streams, exceptions, generics, and project layout.

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。

Cost optimization patterns for LLM API usage — model routing by task complexity, budget tracking, retry logic, and prompt caching.

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。

Trigger when: (1) User mentions "manim" or "Manim Community" or "ManimCE", (2) Code contains `from manim import *`, (3) User runs `manim` CLI commands, (4) Working with Scene, MathTex, Create(), or ManimCE-specific classes. Best practices for Manim Community Edition - the community-maintained Python animation engine. Covers Scene structure, animations, LaTeX/MathTex, 3D with ThreeDScene, camera control, styling, and CLI usage. NOT for ManimGL/3b1b version (which uses `manimlib` imports and `manimgl` CLI).

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。

[AUTO-INVOKE] MUST be invoked at the START of each new coding session. Covers context management, task strategies, and Foundry-specific workflows. Trigger: beginning of any new conversation or coding session in a Solidity/Foundry project.

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。

Transcribe audio/video files via MLX Whisper (Apple Silicon). Usage: /transcribe path/to/file.mp3

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 content generation with OpenAI and Claude, callAIWithPrompt usage, prompt storage in app_settings, structured outputs, response format validation, multi-criteria scoring, rate limiting, JSON schema, and AI API best practices. Use when generating content, creating prompts, scoring articles, or working with OpenAI/Claude APIs.

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。

Build stateful AI agents using the Cloudflare Agents SDK. Load when creating agents with persistent state, scheduling, RPC, MCP servers, email handling, or streaming chat. Covers Agent class, AIChatAgent, state management, and Code Mode for reduced token usage.

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 AgentDB performance with quantization (4-32x memory reduction), HNSW indexing (150x faster search), caching, and batch operations. Use when optimizing memory usage, improving search speed, or scaling to millions of vectors.

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。

Designs multi-step agent workflows with tool usage, retry logic, state management, and budget controls. Provides orchestration diagrams, tool execution order, fallback strategies, and cost limits. Use for "AI agents", "agentic workflows", "multi-step AI", or "autonomous systems".

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。

Write effective system prompts for TD AI agents. Covers role definition, constraint specification, output formatting, tool usage instructions, and prompt structure 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。

Track and report agent invocation metrics including usage counts, success/failure rates, and completion times. Use for understanding which agents are utilized, identifying underused agents, and optimizing agent delegation 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。

Real-time cost tracking, budget enforcement, and ROI measurement for AI agent operations. Track token usage, predict costs, enforce budget caps ($50-70/month typical), optimize model selection, cache results, measure cost-to-value. Use when tracking AI costs, preventing budget overruns, optimizing spend, measuring ROI, or ensuring cost-effective AI operations.

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。

Core agent-browser usage guide. Read this before running any agent-browser commands. Covers the snapshot-and-ref workflow, navigating pages, interacting with elements (click, fill, type, select), extracting text and data, taking screenshots, managing tabs, handling forms and auth, waiting for content, running multiple browser sessions in parallel, and troubleshooting common failures. Use when the user asks to interact with a website, fill a form, click something, extract data, take a screenshot, log into a site, test a web app, or automate any browser task.

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。

Answer questions about Voxt — its features, what shipped and when, and how to use it — grounded in three sources: the public "Voxt Announcements" chat, the Landing pages, and the user guide. Use when asked things like "what features shipped this year", "list new features", "how do I use <feature>", "what is Voxt", or any product/usage question about Voxt. Answers are cited to the source.

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。

Working memory protocol — routes to session protocol, memory audit, MCP/URI integration, or storage details based on the current need. Keeps default continuity usage cheap.

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。

Inspect and govern local Skills: inventory, usage evidence, duplicates, broken links, Core/On-demand proposals, Plans, Receipts, Apply, and Undo. Also find a specialized local Skill when the user requests one or the task would benefit from instructions beyond the visible catalog. Ordinary work can proceed with the Agent's existing capabilities. Not for installing third-party Skills or migrating, distributing, synchronizing, or repairing shared Skill-manager directories.

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。

Index local coding-agent sessions into a searchable SQLite-backed view so you can inspect usage, compare failures, and recover prior context quickly.

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。

Run CodeBurn locally or as an MCP server so agents can inspect token usage, cost, model mix, project spend, and budget waste across coding tools.

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。

Generates Ansible playbook YAML with proper module usage, handler chains, and role structures using ansible-core built-in modules. Supports Jinja2 template rendering and vault-encrypted variable files.

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。

Validates Ansible playbooks using ansible-lint and the Ansible Galaxy API. Performs check-mode dry runs, validates role dependencies, and detects deprecated module usage across collections.

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。

Validates Ansible playbooks and roles using ansible-lint and yamllint APIs. Enforces best practices for idempotency, variable naming, and handler usage with custom rule profiles.

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。