'caching' 검색 결과

Store conversations, agent activity, and feedback in cognee sessions, then carry them into long-term memory. This skill explains improve(), its processing stages, result statuses, and settings for diagnosing skipped work or controlling automatic runs.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Saving conversations and agent activity by session
• Moving session content into long-term memory
• Investigating skipped or blocked processing stages

Inspect project files to identify languages and build tools, then generate starter GitHub Actions or GitLab CI workflows. Set up automated checks, caching, and deployment stages that reflect the project’s commands and target environments.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Setting up automated checks for a new project
• Reworking fragile pipeline configuration
• Moving between GitHub Actions and GitLab CI

Review Google Cloud workloads using the Performance Optimization pillar of the Well-Architected Framework. Assess performance requirements and architecture, then get actionable recommendations for resource allocation, caching, independent components, automatic scaling, and ongoing monitoring.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review resource capacity for expected peak demand
• Assess automatic scaling for traffic spikes
• Review component design for independent scaling

Check new or updated pull requests in isolated checkouts, run the full test suite, and verify temporary test deployments through their public delivery path. Post pass or fail results with evidence to GitHub.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking newly opened or updated pull requests
• Rechecking after a force-push or base branch change
• Finding failures in routing, caching, or redirects

Helps write and review Nginx configurations for websites and APIs. Covers forwarding requests to application servers, distributing traffic, HTTPS settings, caching, compression, and logs to support performance tuning and investigation of slow responses.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Forward API requests to application servers
• Distribute traffic and handle backend failures
• Review HTTPS settings and access restrictions

Build text, image, and audio features in JavaScript using machine learning models that run in browsers or server runtimes. Covers model selection, execution settings, caching, and memory cleanup without requiring a Python server.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add sentiment analysis to a JavaScript app
• Build image classification in a browser
• Implement audio transcription

Investigate how transformer language models produce predictions with TransformerLens. This skill guides inspection of intermediate values and attention patterns, plus experiments that replace internal values to test their effects and identify components involved in model behavior.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Inspecting attention patterns and intermediate values
• Testing output changes by replacing internal activations
• Analyzing attention head contributions to predictions

Create typed data services for panels using direct or server-proxied API calls. Add caching and a circuit breaker, a mechanism that pauses requests after repeated failures, with cached or default data as fallback results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Separate API fetching from panel components
• Pause API requests after repeated failures
• Configure cached data and fallback values

Build TypeScript services that fetch API data for display panels. Use a circuit breaker, which pauses calls after repeated failures, alongside caching and default values, while keeping API keys on the server through proxy endpoints.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Separating API calls from display components
• Pausing requests after repeated API failures
• Configuring cached data and default values

Build serverless endpoints that relay external API requests for a dashboard while keeping API keys on the server. Includes Vercel examples for input checks, caching, cross-origin access, and consistent JSON responses.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Connect a dashboard to external APIs without exposing API keys
• Create endpoints for stock quotes and news
• Standardize API responses and error handling

Build TypeScript data services that separate API calls from display components. Add caching and a circuit breaker, which pauses calls after repeated failures, while keeping user-triggered requests able to report errors directly.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building data services for automatically refreshed panels
• Pausing repeated calls to a failing API
• Separating generation errors from background refresh handling

Build dashboard panels in vanilla TypeScript with shared loading and error displays, saved panel state, and request handling. Examples show retries with increasing delays and CircuitBreaker integration to pause repeated failures and reuse cached results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building dashboard panels in vanilla TypeScript
• Adding caching and cooldowns to existing service calls
• Retrying requests with increasing delays

Build TypeScript data services with optional query filters, typed results, and caching. Add a circuit breaker, a mechanism that pauses API calls after repeated failures, and keep API keys behind server-side proxy endpoints.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Build API URLs with optional filters
• Pause API calls after repeated failures
• Separate data fetching from panel components

Build Next.js 14+ applications with App Router, covering pages, server-side processing, data fetching, and caching. The skill also guides performance improvements, search engine metadata, and production deployment to Vercel or a self-hosted environment.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Building pages and layouts with App Router
• Implementing form updates with Server Actions
• Configuring data fetching and cache revalidation

Compare two to four viable approaches against your requirements and constraints. See each option’s benefits, drawbacks, effort, risk, and ease of reversal, alongside a reasoned recommendation and next steps for the option you choose.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing between a quick fix and a broader refactor
• Comparing caching approaches
• Deciding between TypeScript and JavaScript

Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, React Query, SWR, error handling, caching, offline support, and Expo Router data loaders (`useLoaderData`).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Provides guidance for mechanistic interpretability research using TransformerLens to inspect and manipulate transformer internals via HookPoints and activation caching. Use when reverse-engineering model algorithms, studying attention patterns, or performing activation patching experiments.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Issue, cancel, and fetch Hungarian invoices via the szamlazz.hu Agent API. Handles VAT calculation, NAV taxpayer lookup, partner caching, and PDF generation. Use when the user mentions számla, számlázás, invoice, sztornó, díjbekérő, proforma, or wants to bill a customer.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Golang performance optimization patterns and methodology - if X bottleneck, then apply Y. Covers allocation reduction, CPU efficiency, memory layout, GC tuning, pooling, caching, and hot-path optimization. Use when profiling or benchmarks have identified a bottleneck and you need the right optimization pattern to fix it. Also use when performing performance code review to suggest improvements or benchmarks that could help identify quick performance gains. Not for measurement methodology (→ See `samber/cc-skills-golang@golang-benchmark` skill) or debugging workflow (→ See `samber/cc-skills-golang@golang-troubleshooting` skill).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

[omh] Context window or token budget at risk: plan compact context, token/cost budgets, summarization checkpoints, and overflow recovery before long agent work. Use when the user says: context-budget-review, context budget review, context budget, token budget review, token budget, prompt budget, prompt caching, prompt cache.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

The reference agents' cache-stable request assembly, covering the static system and per-request context split, the fixed tool list, the rolling conversation breakpoint, which config fields are prompt bytes, and verification. Load when writing or reviewing a commerce agent's prompt assembly, when cache reads are zero, or when a turn's latency or cost is the question.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Configure Azure API Management as an AI Gateway for AI models, MCP tools, and agents. WHEN: semantic caching, token limit, content safety, load balancing, AI model governance, MCP rate limiting, jailbreak detection, add Azure OpenAI backend, add AI Foundry model, test AI gateway, LLM policies, configure AI backend, token metrics, AI cost control, convert API to MCP, import OpenAPI to gateway.

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Azure Identity SDK for Python authentication with Microsoft Entra ID. Use for DefaultAzureCredential, managed identity, service principals, and token caching. Triggers: "azure-identity", "DefaultAzureCredential", "authentication", "managed identity", "service principal", "credential".

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.

Use when implementing or debugging ANY network request, API call, or data fetching. Covers fetch API, React Query, SWR, error handling, caching, offline support, loading/empty/error screen states, and Expo Router data loaders (`useLoaderData`).

한국어 요약은 준비 중입니다. 원문 설명을 표시하고 있습니다.