「improve」の検索結果

Schema for tracking code review outcomes to enable feedback-driven skill improvement. Use when logging review results or analyzing review 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。

Reviews LangGraph code for bugs, anti-patterns, and improvements. Use when reviewing code that uses StateGraph, nodes, edges, checkpointing, or other LangGraph features. Catches common mistakes in state management, graph structure, and async 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。

Optimize prompts for code-related tasks following prompt-engineering best practices. Use when refining prompts for implementation, debugging, refactoring, code review, or testing.

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。

Reviews Deep Agents code for bugs, anti-patterns, and improvements. Use when reviewing code that uses create_deep_agent, backends, subagents, middleware, or human-in-the-loop patterns. Catches common configuration and usage mistakes.

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。

Validate MCP configuration and suggest improvements. Use when MCP servers fail to load, after editing .mcp.json, or when the user runs /mcp-check.

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, model-aware system prompts for any LLM (Claude, GPT, Gemini, open-source, etc.). Use this skill whenever the user wants to create, write, build, design, draft, or improve a system prompt, system instructions, or custom instructions for any AI model. Also trigger when the user asks about prompt engineering, prompt design, prompt optimization, or wants to define behavior for an AI assistant, chatbot, agent, or any LLM-powered application — even if they don't explicitly say "system prompt". Covers all use cases including chatbots, agentic systems, tool-use workflows, content generation, data extraction, code assistants, and multi-turn conversations.

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, restructure, classify, and review documentation with the Diataxis framework. Use when the user asks to create, improve, audit, or reorganize documentation of any kind: knowledge bases, help centers, onboarding guides, process docs, manuals, runbooks, product or API docs, tutorials, how-to guides, references, explanations. Also use when the user mentions Diataxis, docs taxonomy, or documentation architecture, or asks why a document feels confusing. Also use for Simplified Technical English (ASD-STE100) or controlled-language rewrites of English technical docs. Not for marketing, legal, sales, press, or fiction writing unless the user wants a Diataxis-style analysis.

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。

Valuation criteria for developed market growth general insurance stocks. Combined Ratio improvement trajectory, premium growth 7-10% YoY, expense ratio decline, and retention rate targets.

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。

Assess and improve cloud portability — identify lock-in, prioritize abstraction, and design migration paths. Use when asked "how locked in are we", "reduce vendor lock-in", or "plan a cloud migration".

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。

Customer Success engineer — onboarding optimization, health scoring, expansion revenue, churn prevention, and NRR growth. Use when asked to "improve onboarding", "score account health", "prevent churn", or "grow NRR".

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。

Local SEO audit — assess a location-based business's Google Business Profile against local competitors, check Maps and local-pack visibility for its main queries, and recommend the few fixes that win nearby searches. Use when asked to "improve our local SEO", "why don't we show up on Google Maps", "audit our Google Business Profile", "rank in the local pack", or "local search for [city]".

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 or refactor a design token system for color — naming, structure, and coverage. Use when asked to "refactor our color tokens", "fix color token naming", or "improve token coverage for color".

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 customer onboarding — map the activation sequence, identify drop-off points, design the aha moment, and produce the onboarding email sequence. Use when asked to "fix onboarding", "improve activation", "time-to-value is too slow", or "customers aren't getting started".

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。

SEO audit and keyword strategy — investigate a site's real search opportunities, shortlist candidates, and recommend the one to three changes most likely to grow organic traffic that converts. Evidence-first — metrics come from a tool or are written as unknown. Use when asked to "improve our SEO", "do keyword research", "audit our SEO", "why aren't we ranking", or "what should we fix first for search".

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 similarity search — ANN index tuning, hybrid search, reranking, query expansion. Use when asked to "improve similarity search", "tune the ANN index", or "add hybrid search".

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。

ML/AI engineer — LLM integrations, prompt engineering, model pipelines, evals, RAG. Use when asked to "add AI to this", "integrate an LLM", "build a RAG pipeline", "evaluate model accuracy", or "improve this prompt".

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 production-ready prompt package — system prompt, few-shot examples, output format, edge case handling, eval criteria. Use when asked to "prompt engineering", "build a prompt", "write a system prompt", or "improve this prompt".

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 or audit knowledge base -- article structure, coverage gaps, deflection rate, and maintenance process. Use when asked to "build a knowledge base", "what docs are missing", "improve our self-serve rate", or "audit our help center".

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 and manage open source community — Discord/Slack structure, contributor onboarding, ambassador program, community flywheel design, and GitHub community health. Use when asked to "build a community", "grow our Discord", "improve contributor experience", or "design a developer ambassador program".

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。

Expert guide for Web Performance optimization: Core Web Vitals (LCP, INP, CLS), bundle analysis, image optimization, rendering strategies, and Lighthouse score improvement / Panduan ahli untuk optimasi performa web: Core Web Vitals (LCP, INP, CLS), analisis bundle, optimasi gambar, strategi rendering, dan peningkatan skor Lighthouse.

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。

Improve a Hinge dating profile through research-backed screenshot audits, photo selection and ordering, conversational discovery, prompt and caption writing, settings review, or post-launch troubleshooting. Use for a full profile rebuild or a focused request about photos, copy, positioning, match quality, or profile performance.

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。

Find opportunities to improve web application code using TanStack libraries (Query, Table, Form, Router, etc.). Avoid man-with-hammer syndrome by applying TanStack after vanilla implementation works.

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 design taste for building, reviewing, and polishing web interfaces. Use whenever the user wants to design, redesign, shape, critique, audit, polish, or improve any UI (landing pages, portfolios, dashboards, product UI, components, forms, onboarding, empty states) or asks to make something look better / premium / modern, fix the styling, add or fix animations, or make a design feel less generic ("AI slop"). Covers typography, color, spacing, layout, visual hierarchy, motion, micro-interactions, component states, accessibility, responsive behavior, UX copy, and anti-pattern detection.

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。

Delegate tasks to Antigravity CLI (agy) to use its models, tools, and separate working context. Use when delegation can improve efficiency, provide another perspective, or let independent work proceed in parallel.

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。