「optimize」の検索結果

Skill Optimization: Auto Research. Autonomously optimize any Claude Code skill by running it repeatedly, scoring outputs against binary evals, mutating the prompt, and keeping improvements. Based on Karpathy's autoresearch methodology. Use when: optimize this skill, improve this skill, run autoresearch on, make this skill better, self-improve skill, benchmark skill, eval my skill, run evals on. Outputs: an improved SKILL.md, a results log, and a changelog of every mutation tried.

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 and rewrite a Facebook Page for 2026: Page name, username and vanity URL, profile picture and cover photo, Intro/About and category, the CTA button (Shop, Book, Sign Up, Contact matched to your goal), pinned post, tabs order, and contact/link fields. Triggers on "review my Facebook Page", "fix my Page about", "optimize my cover", "set my CTA button", "Page audit". Converts a default Page into one that turns a visitor into a follower or a lead. Not for writing Page posts (use fb-post-writer).

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。

Discover and install agent skills from the open ecosystem (skills.sh), optimized for Japanese users. Use when the user asks 'how do I do X', 'is there a skill for X', or in Japanese 「〜できる？」「〜のスキルある？」「スキルを探して」「〜を自動化したい」「〜を効率化したい」. Always converts Japanese intent into short English search keywords before searching (the registry matches English keywords only), and verifies skill quality and safety before recommending installation.

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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 Kiln to create eval datasets, rate outputs, optimize prompts and models, and ship the same AI task or agent definition from a local workbench into production 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。

Use GEO Optimizer from the CLI or MCP so agents can audit a site for AI search visibility, generate llms.txt/schema fixes, check bot access, and track citation readiness.

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 Remotion compositions for performance issues and provides optimization recommendations. Identifies expensive computations, unnecessary re-renders, large assets, memoization opportunities, and architecture improvements. Use when optimizing render times or when asked to "improve performance", "speed up renders", "optimize Remotion video".

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。

Systems-level performance engineer: identifies hotspots, provides optimized code with resource justifications.

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 web performance for faster loading and better user experience. Use when the task involves `speed up my site`, `optimize performance`, `reduce load time`, `fix slow loading`, `improve page speed`, or `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。

Optimize for search engine visibility and ranking. Use when the task involves `improve SEO`, `optimize for search`, `fix meta tags`, `add structured data`, `sitemap optimization`, or `search engine 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。

Optimize Core Web Vitals (LCP, INP, CLS) for better page experience and search ranking. Use when the task involves `improve Core Web Vitals`, `fix LCP`, `reduce CLS`, `optimize INP`, `page experience optimization`, or `fix layout shifts`.

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。

Guide creating and reviewing skills that extend Claude with specialized knowledge, workflows, or tool integrations. Covers SKILL.md structure, frontmatter quality, trigger design, eval pipelines, and packaging. Triggers on create a skill, review this skill, new skill, optimize skill, skill quality.

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。

Audits and optimizes the five global Claude layers (User Preferences, Styles, Global Memory, Skills, MCP Connectors) using the Global Layer Scorecard (six dimensions, anchored 1-5 rubrics). Detects eight cross-layer failure modes and produces evolutionary recommendations (Promotion, Demotion, Codification, Skill Extraction). Use when user says "audit my global setup," "optimize my preferences," "review my Claude configuration," "check my cross-project setup," "are my preferences working," "clean up my global memory," or "what should be in my preferences vs my project." Also use when a user has 3+ Projects and wants to improve their shared foundation. Do NOT use for single-Project audits, Project Memory optimization, or full-stack audits (use rootnode-project-audit, rootnode-memory-optimization, or rootnode-full-stack-audit respectively, if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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 Claude Project context budget under the automatic-RAG-by-window model: knowledge files vs. threshold-exempt overhead (Skills, MCPs, CI, Memory). Two modes: Quick Diagnostic and Full Budget Audit. Use when user says "check my context budget," "how much context am I using," "is my project too big," "optimize my token usage," "tier my files," "optimize for RAG," "improve retrieval quality," "should I keep compressing," "am I over-compressing," "should I accept RAG mode." Also trigger on context pressure symptoms: "Claude forgets my instructions," "responses getting generic," "content not found in my knowledge files." Also use when a project audit scores Knowledge Architecture ≤ 3. Do NOT use for content placement decisions (use rootnode-memory-optimization if available), full project audits (use rootnode-project-audit if available), or behavioral tuning (use rootnode-behavioral-tuning if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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。

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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。

Agent Teams スキルを設計・構築するためのベストプラクティスガイド。 サブエージェント定義、SendMessage 通信プロトコル、タスク依存管理、 PostToolUse Hook によるログ、MCP ツール統合、コンテキストファイル設計を網羅。 7つの実績あるチームスキル（app-naming, ui-review, logo-design, persona-creation, skill-creator-team, ui-variations, aso-optimize）から抽出したパターン集。 Use when: Agent Teams を使ったスキルを新規作成したい、 既存のチームスキルの品質を改善したい、エージェント間通信のデバッグ、 チームスキルの設計パターンを知りたい。 Triggers: "agent team", "チームスキル", "エージェントチーム", "サブエージェント定義", "SendMessage パターン", "チーム設計", "エージェント間通信", "team skill", "swarm pattern"

Profile and optimize Shiny application performance using profvis, bindCache, memoise, async/promises, debounce/throttle, and ExtendedTask for long-running computations. Use when the app feels slow or unresponsive during user interaction, when server resources are exhausted under concurrent load, when specific operations create bottlenecks, or when preparing an app for production deployment with many concurrent users.

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 Docker build times using layer caching, multi-stage builds, BuildKit features, and dependency-first copy patterns. Applicable to R, Node.js, and Python projects. Use when Docker builds are slow due to repeated package installations, when rebuilds reinstall all dependencies on every code change, when image sizes are unnecessarily large, or when CI/CD pipeline builds are a bottleneck.

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 debugging RelWithDebInfo or -O2 release builds, using -Og for debuggable optimization, split-DWARF, GDB scheduler-locking, reading inlined frames, or understanding "value optimized out".

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 the Codex Optimized Development, Evaluation, and Remediation (CODER) Loop with an orchestration-only coordinator, non-overlapping task-family owners, fresh independent reviewers, evidence-scoped remediation, and final coordinator acceptance. Discover and compose optional MSW, Timebox, MSL, and Codex Voice Optimizer companions as the Slopware Dev Stack without making them dependencies. Use in Codex when the user invokes the CODER Loop, asks to divide a complex change into bounded implementation families with independent reviewers, requests multi-agent implementation without overlapping ownership, requires review and repair until every blocking gap is independently rechecked, asks for the CODER tutorial or Slopware Dev Stack, or wants CODER to install or use its companions. Do not trigger for an ordinary single-agent change, a review-only request, or a non-Codex host.

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。

Create new skills, modify and improve existing skills, and measure skill performance. Use when users want to create a skill from scratch, edit, or optimize an existing skill, run evals to test a skill, benchmark skill performance with variance analysis, or optimize a skill's description for better triggering accuracy.

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。

Interactively gather parameters for `python -m cli.inference.throughput_optimizer`, generate a deployment simulation command, explain assumptions, ask for execution confirmation, then run the simulation and summarize the best parallel strategy. Use when the user wants to evaluate a model on one or more hardware profiles, compare hardware targets, compare aggregation versus disaggregation versus PD ratio optimization, choose TP/EP/MOE-DP search ranges, or obtain recommended concurrency, throughput, TTFT, and TPOT results from throughput modeling.

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 NowStack Mobile across Convex, Expo, and TanStack Start. Use for performance, state, subscriptions, rendering, routing, forms, mobile UI, bundle, or data-fetching 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。

Create high-quality, SEO-optimized content that ranks AND reads like a human wrote it. Performs live SERP gap analysis, writes with anti-AI detection techniques, and adds schema markup. Use when someone needs a blog post, article, SEO page, or wants content that drives search traffic. Triggers on 'SEO content', 'blog post', 'article', 'SERP', 'programmatic SEO', 'content at scale', 'template pages at scale', 'write a post about', 'rank for', or 'search-optimized content'. Two modes: single article or programmatic SEO at scale. Owns programmatic SEO and content-at-scale generation. For a single alternatives or vs/comparison page, see /competitor-alternatives; for a multi-phase page roadmap with a persistent tracker, see /seo-machine.

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。