「optimize」の検索結果

Compose a short LinkedIn-post-style thread from Ahmad's OpenMark saves. Use when Ahmad wants a tight 200–400 word post he can paste into LinkedIn, X, or a short newsletter slot — NOT a long essay or full digest. Trigger phrases include "thread", "LinkedIn post", "short post", "tweet thread", "quick newsletter", "social post", "/newsletter-thread". Output is one strong hook + 4–7 short paragraphs + ONE link. Optimized for skim-reading on a phone.

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 and fixes UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.

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。

Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.

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 wants to design, redesign, shape, critique, audit, polish, clarify, distill, harden, optimize, adapt, animate, colorize, extract, or otherwise improve a frontend interface. Covers websites, landing pages, dashboards, product UI, app shells, components, forms, settings, onboarding, and empty states. Handles UX review, visual hierarchy, information architecture, cognitive load, accessibility, performance, responsive behavior, theming, anti-patterns, typography, fonts, spacing, layout, alignment, color, motion, micro-interactions, UX copy, error states, edge cases, i18n, and reusable design systems or tokens. Also use for bland designs that need to become bolder or more delightful, loud designs that should become quieter, live browser iteration on UI elements, or ambitious visual effects that should feel technically extraordinary. Not for backend-only or non-UI tasks.

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。

Elite frontend image-direction skill for generating premium, conversion-aware website design references. CRITICAL OUTPUT RULE — generate ONE separate horizontal image FOR EVERY section. A landing page with 8 sections produces 8 images. Never compress multiple sections into one image. Enforces composition variety (not always left-text / right-image), background-image freedom, varied CTAs, varied hero scales (giant / mid / mini minimalist), narrative concept spine, second-read moments, and a single consistent palette across all images. Optimized for landing pages, marketing sites, and product comps that developers or coding models can accurately recreate.

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。

Writing style guide for technical content, social media, blog posts, READMEs, git commits, and developer documentation. Optimized to avoid AI detection patterns. Use when writing any content beyond code.

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。

Premium brand-kit image generation skill for creating high-end brand-guidelines boards, logo systems, identity decks, and visual-world presentations. Trained for minimalist, cinematic, editorial, dark-tech, luxury, cultural, security, gaming, developer-tool, and consumer-app brand systems. Optimized for intentional logo concepting, refined composition, sparse typography, strong symbolic meaning, premium mockups, art-directed imagery, and flexible grid layouts.

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。

Patterns for scaling read-heavy Convex apps to millions of users. Use when optimizing bandwidth, reducing query costs, fixing slow queries, creating digest tables, replacing reactive subscriptions with one-shot fetches, adding compound indexes, debouncing writes, rate-controlling backfills, or running npx convex insights. Trigger when users mention "scale", "bandwidth", "performance", "optimize", "slow queries", "expensive queries", "digest table", "denormalize", or "thundering herd" in the context of Convex.

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 and fixes UI performance across loading speed, rendering, animations, images, and bundle size. Use when the user mentions slow, laggy, janky, performance, bundle size, load time, or wants a faster, smoother experience.

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。

Writing style guide for technical content, social media, blog posts, READMEs, git commits, and developer documentation. Optimized to avoid AI detection patterns. Use when writing any content beyond code.

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 Azure architectures for startups and enterprises. Use when asked to design Azure infrastructure, create Bicep/ARM templates, optimize Azure costs, set up Azure DevOps pipelines, or migrate to Azure. Covers AKS, App Service, Azure Functions, Cosmos DB, and cost optimization.

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 AWS cost analysis and optimization recommendations using AWS CLI and Cost Explorer

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。

Audit websites for SEO, performance, security, technical, content, and 15 other issue cateories with 230+ rules using the squirrelscan CLI. Returns LLM-optimized reports with health scores, broken links, meta tag analysis, and actionable recommendations. Use to discover and asses website o...

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 end-to-end application performance with profiling, observability, and backend/frontend tuning. Use when coordinating performance optimization across the stack.

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。

Senior embedded software engineer specializing in firmware and driver development for ARM Cortex-M microcontrollers (Teensy, STM32, nRF52, SAMD). Decades of experience writing reliable, optimized, and maintainable embedded code with deep expertise in memory barriers, DMA/cache coherency, interrup...

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。

You are an AI product engineer who has shipped LLM features to millions of users. You've debugged hallucinations at 3am, optimized prompts to reduce costs by 80%, and built safety systems that caught thousands of harmful outputs. You know that demos are easy and production is hard.

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 and optimize AI agent action spaces, tool definitions, and observation formatting for higher completion rates.

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。

Audit websites for SEO, performance, security, technical, content, and 15 other issue cateories with 230+ rules using the squirrelscan CLI. Returns LLM-optimized reports with health scores, broken links, meta tag analysis, and actionable recommendations. Use to discover and asses website or webapp issues and health.

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。

This skill should be used when reviewing vendor estimates for software development projects. Use this skill when you need to evaluate whether a vendor's cost estimate, timeline, and approach are reasonable and whether the project is likely to succeed. This skill helps identify gaps, risks, overestimates, underestimates, and unfavorable contract terms. It generates comprehensive Markdown review reports with actionable recommendations to optimize costs while ensuring project success.

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。

製造施設（セントラルキッチン、食品工場、製造ライン）の週次生産スケジュールを最適化するスキル。 製品の賞味期限、作業室の容量、人員配置、設備制約を考慮したタイムテーブル生成、 人員要件見積、シフト計画、カバレッジ検証を提供。 Use when: 「製造スケジュールを作成」「生産計画を最適化」「人員配置を見積もり」 「CK スケジュール」「週次製造計画」「シフト計画」

Use this skill when creating executive-level briefing materials, board reports, management meeting presentations, or investor briefings. This skill provides the "So What? / Why Now? / What Next?" framework, data visualization guidelines optimized for executives, and professional templates for rapid document creation. Triggers include "create board report", "executive summary", "management meeting materials", "investor presentation", "one-page summary", or requests to communicate complex information to senior leadership.

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, measurement-driven performance optimization for latency, throughput, memory/GC, and tail behavior. Use when the user asks to optimize/speed up, reduce latency (p95/p99), increase throughput/QPS, lower CPU/memory/allocations/GC pauses, profile hot paths, or run a benchmarked perf pass (including JSONL/query-heavy code). Requires before/after measurement on a runnable workload (or an explicit `UNMEASURED` plan) plus a correctness gate.

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。

Load when EF Core reads are slow, emit N+1 or excessive SQL, over-fetch, track too many entities, cause high DB load, or need projection/split-query/compiled-query analysis; not for general migrations, DbContext setup, or repository conventions.

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。

Specialist for the entire job application process. Analyzes job postings, optimizes profiles (LinkedIn/CV), and generates tailored cover letters. Generates ASCII CVs from a SQLite database and folder structure. cv_generator.py is ported standalone -- no BACH runtime required.

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。