「ttl」の検索結果

Enforce universal standards for high-performance development. Use when profiling bottlenecks, reducing latency, fixing memory leaks, improving throughput, or optimizing algorithm complexity in any language.

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 test code for quality, design, and completeness after implementing a feature or fixing a bug. Use when the user asks to "review my tests", "check my test quality", "are these tests good enough", "review testing", or after completing a feature implementation that includes tests. Also use when tests feel brittle, flaky, or superficial. Cross-references production code to find coverage gaps.

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。

Redis caching strategies, cache invalidation, write-through/write-behind, TTL management, and cache stampede protection.

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。

When validating system performance under load, identifying bottlenecks through profiling, or optimizing application responsiveness. Covers load testing (k6, Locust), profiling (CPU, memory, I/O), and optimization strategies (caching, query optimization, Core Web Vitals). Use for capacity planning, regression detection, and establishing performance SLOs.

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。

Builds AI chat interfaces and conversational UI with streaming responses, context management, and multi-modal support. Use when creating ChatGPT-style interfaces, AI assistants, code copilots, or conversational agents. Handles streaming text, token limits, regeneration, feedback loops, tool usage visualization, and AI-specific error patterns. Provides battle-tested components from leading AI products with accessibility and performance built in.

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 DNS records, TTL strategies, and DNS-as-code automation for infrastructure. Use when configuring domain resolution, automating DNS from Kubernetes with external-dns, setting up DNS-based load balancing, or troubleshooting propagation issues across cloud providers (Route53, Cloud DNS, Azure DNS, Cloudflare).

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 per-H3 writer context packs (NO PROSE): merge briefs + evidence packs + anchor facts + allowed citations into a single deterministic JSONL, so drafting is less hollow and less brittle.

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 dotnet-diagnostics-mcp for MCP-driven .NET CPU, allocation, GC, and test-host profiling. USE FOR: profiling unit tests or investigating runtime bottlenecks. DO NOT USE FOR: writing test assertions, coverage collection, or precise microbenchmark timing. INVOKES: connect the MCP server, select target processes, collect bounded profiles, and attribute hotspots to 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。

Establish MSBuild/.NET build performance baselines before optimizing. USE FOR: a .NET build or solution that is slow or has build-performance concerns; cold, warm, incremental, or no-op measurements; before/after comparisons; CI build output caching; static graph build decisions; artifacts output; and dependency graph trimming. Start here before build-perf-diagnostics, incremental-build, or build-parallelism. DO NOT USE for webpack, npm, JavaScript bundlers, or other non-MSBuild build systems. For detailed target/task/analyzer bottleneck analysis after baselining, use build-perf-diagnostics.

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。

Applies Qt Canvas2D (QtCanvas2D / Qt Canvas Painter, Qt 6.12+) best practices when producing or working with Canvas2D QML source code. Use whenever Canvas2D, Canvas2DContext, path2d, boxshadow2d, boxgradient2d, gridpattern2d, conicalgradient2d or transform2d is the subject: writing, reviewing, fixing, optimizing, or porting Qt Quick Canvas / HTML5 canvas drawing code to Canvas2D. Also use for GPU-accelerated imperative 2D drawing in QML — gauges, dials, charts, waveforms, oscilloscopes, clocks, freehand drawing — including choosing between Canvas2D and Shape/ShapePath when the renderer has not been decided yet. Do NOT trigger for plain Qt Quick Canvas work that must stay on the old CPU element, or for reviewing existing Shape/ShapePath code where the renderer is already settled.

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。

Conversion funnel analysis with drop-off investigation. Use when analyzing multi-step processes, identifying conversion bottlenecks, comparing segments through a funnel, or optimizing user journeys.

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。

Check refund, complaint, and sensitive customer-service actions against financial-service policy. Use before creating refund work orders, promising settlement times, exposing account data, or responding to complaints.

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 you need to analyze Java profiling data collected during the detection phase — including interpreting flamegraphs, memory allocation patterns, CPU hotspots, threading issues, systematic problem categorization, evidence documentation with profiling-problem-analysis and profiling-solutions markdown files, or prioritizing fixes using Impact/Effort scoring. This should trigger for requests such as Analyze JFR profile; Analyze the profile; Analyze the performance; Analyze the memory; Analyze the threading; Analyze GC logs from profiling; Prioritize Java profiling bottlenecks by impact. Part of Plinth Toolkit

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。

Interview you one question at a time, each with a recommendation, to settle a big outcome before agents work alone. Use when: selected by name.

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。

Settle what domain terms mean per context, and which repository conventions or language standards (Go, Python) apply. Use when: names disagree or a rename is proposed.

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。

Diagnoses why your product team ships slowly and produces a velocity plan with a baseline, a bottleneck map, the top 3 interventions and a stop-doing list. Use it when you say 'we're too slow', 'how do we ship faster', 'projects keep slipping', 'too many meetings', 'approvals take forever', 'our releases are scary', 'velocity', 'cycle time', 'we hired more people and nothing got faster' or 'AI made coding fast but we still ship slowly'. Draws on 226 Lenny's Podcast guests including Farhan Thawar, Nicole Forsgren and Melissa Perri.

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。

Comprehensive performance specialist covering analysis, optimization, load testing, and framework-specific performance. Use when identifying bottlenecks, optimizing code, conducting load tests, analyzing Core Web Vitals, fixing memory leaks, or improving application performance across all layers (application, database, frontend). Includes React-specific optimization 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。

Implement caching strategies using @delon/cache. Use this skill when adding memory cache, LocalStorage cache, SessionStorage cache, or cache interceptors for HTTP requests. Supports TTL-based expiration, cache invalidation, cache grouping, and persistent storage. Optimizes performance by reducing redundant API calls and database queries.

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。

Operating SOP for DSPy (Stanford NLP) — the declarative framework for "programming, not prompting" language models. Activate when the user says any of: "use DSPy", "compile a prompt", "optimize prompts/programs", "MIPRO/MIPROv2", "BootstrapFewShot", "GEPA", "Signatures + Modules", "teleprompter", "auto-tune prompts for a different LM", or whenever a brittle hand-crafted prompt pipeline needs to be turned into a *compiled*, measurable, swappable program. Do NOT activate for one-shot prompt tweaks, no-metric exploratory work, or pipelines where prompts must remain human-authored verbatim — use raw prompting or LangChain templates 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。

Daily temperature high/low bracket and threshold contracts on Kalshi — contract structure, forecast→P(YES) map, settlement rules, cross-venue divergences, and weather-specific pitfalls

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。

Polymarket exchange mechanics — on-chain Polygon CTF, Gamma/CLOB/Data APIs, EIP-712 auth, identifier model, WebSocket, settlement, and geo/KYC constraint

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 a self-contained local prototype at .turbo/prototypes/<slug>.html, drive it, and hand it to the user to settle unknowns that prose cannot answer. Use when the user asks to "prototype this", "build a prototype", "mock this up", "show me what it would look like", "let me try the interaction first", or when a decision waits on seeing a surface or using it firsthand.

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。

Implement distributed tracing with Jaeger and Tempo to track requests across microservices and identify performance bottlenecks. Use when debugging microservices, analyzing request flows, or implementing observability for distributed 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。

Battle-tested Playwright patterns for writing and debugging reliable E2E, API, component, visual, accessibility, and security tests. Use when you need locator strategy, assertions, fixtures, network mocking, auth flows, trace debugging, or framework recipes for React, Next.js, Vue, and Angular. TypeScript and JavaScript.

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。