1,283 件 ・ 関連度順
概要と使いどころ
Observability and SRE expert. Use when setting up monitoring, logging, tracing, defining SLOs, or managing incidents. Covers Prometheus, Grafana, OpenTelemetry, and incident response best practices.
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。
Diagnose slow or freezing VS Code-compatible editors with evidence-first, zero-hardcoded-assumption workflow. Use when the user reports editor lag, typing delay, UI freezes, extension host stalls, file watcher noise, high editor CPU/RSS, uses VS Code/Cursor as a file browser over a large folder, or wants a safe editor performance audit.
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。
Safely diagnose and improve local network speed, latency, jitter, DNS, Wi-Fi, Ethernet, macOS network services, and bufferbloat. Use this skill whenever the user asks to optimize internet/network speed, make the network faster, diagnose slow Wi-Fi, latency, packet loss, DNS delay, unstable Codex/AI tool connectivity, or asks about the viral Codex network optimization workflow. Always protect VPN/proxy tools such as Clash Verge, Mihomo, Shadowrocket, Tailscale, V2Ray, Surge, and corporate VPNs; do not modify or disable them unless the user explicitly asks for that specific change.
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。
Plan, produce, or diagnose evidence-backed product demo videos and screen-recorded promotional walkthroughs. Use when the user asks to make a product demo, launch video, feature showcase, app walkthrough, demo reel, or polished recording; wants every important capability shown without a slow feature tour; asks to remove dead time or fix narration-to-action pacing; or needs a repeatable script, capture plan, and verified final media. Do not use for fictional commercials with no real product proof, general-purpose video editing, or documentation-only tutorials that do not need a promotional narrative.
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 Codex feels slow, bloated, or heavy after heavy use. Provides safe session hygiene, archive strategy, and handoff discipline to keep daily Codex usage responsive and low-friction. Always pairs with comprehensive handoffs before archiving active work.
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。
Fix NDK (Nostr Dev Kit) operations hanging indefinitely when relay connections stall. Use when: (1) App freezes during fetchEvents or publish calls, (2) No timeout errors despite network issues, (3) Relay connection appears stuck, (4) Using NDK with unstable or slow relays. NDK operations have no built-in timeout - wrap with Promise.race.
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。
Fix slow Flutter app startup caused by blocking network operations during initialization. Use when: (1) App takes several seconds to show first frame, (2) Startup logs show sequential network operations (WebSocket connections, API calls), (3) Services initialize during startup that aren't needed until user authenticates. Covers: converting sequential network ops to parallel with Future.wait(), deferring service initialization until actually needed (lazy init), and identifying blocking operations in Riverpod/provider initialization chains.
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。
Fix Node.js pg-pool not reconnecting after CloudSQL connection reset (ECONNRESET). Use when: (1) Retries fail with same ECONNRESET error despite retry logic, (2) "Connection terminated" or "connection already closed" errors persist across retries, (3) "remaining connection slots are reserved" errors in CloudSQL, (4) High-concurrency Node.js app with pg-pool and CloudSQL/managed PostgreSQL. The pool caches dead connections - you must recreate the pool, not just retry.
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。
Debug and fix infinite widget rebuild loops in Flutter apps using Riverpod state management. Use when: (1) Logs show "RAPID REBUILD" warnings or 50+ rebuilds in seconds, (2) UI becomes unresponsive or shows same content repeatedly, (3) Bug only affects slower devices or poor network conditions, (4) Provider watching creates circular dependencies with router/URL state. Covers ref.watch() overuse, watch+listener redundancy, and transitive dependency chains.
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 slow PostgreSQL inserts in Python using psycopg2. Use when: (1) Row-by-row inserts are taking too long over network, (2) executemany() isn't providing speedup, (3) Migrating large datasets to PostgreSQL, (4) Network latency making individual INSERT statements impractical. The key is using execute_values() from psycopg2.extras instead of executemany() or individual execute() calls.
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 Nostr relay queries using NDK batch fetching. Use when: (1) Checking existence of many events one-by-one is slow, (2) Loop with individual fetchEvents calls causing N+1 query problem, (3) Need to verify multiple addressable events (Kind 30000+) exist. NDK's fetchEvents accepts arrays for tag filters (#d, #p, #e, authors), enabling batch queries that reduce hundreds of round-trips to a single request.
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。
Profile programs at the function/method level to identify performance hotspots, bottlenecks, and optimization opportunities. Records execution time, memory usage, and call frequency for each interval. Generates actionable recommendations and visualizations. Use when users need to (1) analyze program performance, (2) identify slow functions or bottlenecks, (3) optimize execution time or memory usage, (4) profile Python, Java, or C/C++ programs with test cases or workload scenarios, or (5) generate performance reports with flame graphs and recommendations.
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。
Analyzes and optimizes code for better performance, memory usage, and efficiency. Use when code is slow, memory-intensive, or inefficient. Supports Python and Java optimization including execution speed improvements, memory reduction, database query optimization, and I/O efficiency. Provides before/after examples with detailed explanations of why optimizations work, complexity analysis, and measurable performance improvements.
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 correct, performant SQL across all major data warehouse dialects (Snowflake, BigQuery, Databricks, PostgreSQL, etc.). Use when writing queries, optimizing slow SQL, translating between dialects, or building complex analytical queries with CTEs, window functions, or aggregations.
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 and improve business processes. Trigger with "this process is slow", "how can we improve", "streamline this workflow", "too many steps", "bottleneck", or when the user describes an inefficient process they want to fix.
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 a month of social media post ideas for SMBs. Takes brand context, platforms, and goals and produces a structured content calendar with post topics, formats, angles, and visual direction for each slot. Output saves to context/content-calendar.md for use by /caption-writer and /social-creative-designer. Supports Instagram, LinkedIn, Facebook, TikTok, and X.
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。
Cloudflare Workers performance optimization with CPU, memory, caching, bundle size. Use for slow workers, high latency, cold starts, or encountering CPU limits, memory issues, timeout errors.
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 polished, intentional UIs with concrete CSS/Tailwind values — typography, color, layout, spacing, dark mode, accessibility, animations, components. Encodes specific, opinionated rules with exact values, not vague advice. Covers buttons, cards, forms, tables, navigation, dashboards, landing pages, onboarding, and more. Triggers on "absolute ui", "design a UI", "style this component", "make this less like AI slop", "fix the spacing/typography/color", "dark mode", "design a pricing page", "make this look better".
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。
Schedules meetings with internal and external stakeholders by parsing natural language requests, resolving time zones, checking calendar availability, proposing optimal slots, and managing invitations and RSVPs. Use when the user requests meeting scheduler or provides relevant inputs for this workflow.
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 structured, engaging chatbot conversations with robust intent handling, slot filling, disambiguation, error recovery, and graceful fallback strategies. Use when the user requests chatbot conversation design or provides relevant inputs for this workflow.
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。
Diagnose and optimize existing slow SQL queries using execution plans, indexing strategies, query rewriting, and ORM tuning. Use when the user provides a query, performance symptom, or EXPLAIN plan; use sql-query-generation when creating a new query from requirements.
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 SQL queries from natural-language requirements using SELECT, JOIN, GROUP BY, window functions, CTEs, and subqueries. Use when the user needs a new query from a business question or schema; use query-optimization when an existing query or execution plan is slow.
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。
Think and work like an expert Mathematical Modeler. Use when a task calls for Mathematical Modeler judgment. Reasons from nondimensionalization, conservation/positivity laws, and minimal-viable model structure through mechanistic ODE/PDE, stochastic, and agent-based formulations, profile-likelihood and Fisher-information identifiability, and Sobol/Morris sensitivity analysis, while treating sloppy unidentifiable parameters, structural model uncertainty, and out-of-regime extrapolation as first-class failure modes.
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。
SwiftUI frontend visual design skill. Creates beautiful, distinctive iOS/macOS interfaces that avoid generic AI slop patterns. Covers design direction, layout systems, typography, color, spacing, brand integration, and design review. Use when designing new SwiftUI views, reviewing UI quality, creating iOS prototypes, choosing visual styles, improving app aesthetics, or when the UI looks generic or AI-generated.
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。