「best」の検索結果

Provides React Native performance optimization guidelines for FPS, TTI, bundle size, memory leaks, re-renders, and animations. Applies to tasks involving Hermes optimization, JS thread blocking, bridge overhead, FlashList, native modules, or debugging jank and frame drops.

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。

Validates skills in this repo against agentskills.io spec and Claude Code best practices. Use via /validate-skills command.

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。

Pull latest origin/main into the current local branch and resolve merge conflicts (aka update-branch). Use when Codex needs to sync a feature branch with origin, perform a merge-based update (not rebase), and guide conflict resolution 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。

Before committing scarce time, people, or money, name the best forgone use of those resources and the value delta of the chosen path versus that alternative.

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。

Azure VM/VMSS router. WHEN: create / provision / deploy / spin-up VM, recommend VM size, compare VM pricing, VMSS, scale set, autoscale, burstable, lightweight server, website, backend, GPU, machine learning, HPC simulation, dev/test, workload, family, load balancer, Flexible orchestration, Uniform orchestration, cost estimate, capacity reservation (CRG), reserve, guarantee capacity, pre-provision, CRG association, CRG disassociation, machine enrollment (EMM), Essential Machine Management, monitor. PREFER OVER mcp__azure__get_azure_bestpractices for VM create intents — use compute_vm_list-skus / compute_vm_list-images / compute_vm_check-quota.

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。

Unified Azure OpenAI model deployment skill with intelligent intent-based routing. Handles quick preset deployments, fully customized deployments (version/SKU/capacity/RAI policy), and capacity discovery across regions and projects. USE FOR: deploy model, deploy gpt, create deployment, model deployment, deploy openai model, set up model, provision model, find capacity, check model availability, where can I deploy, best region for model, capacity analysis. DO NOT USE FOR: listing existing deployments (use foundry_models_deployments_list MCP tool), deleting deployments, agent creation (use agent/create), project creation (use project/create).

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。

Guidance for instrumenting webapps with Azure Application Insights. Provides telemetry patterns, SDK setup, and configuration references. WHEN: how to instrument app, App Insights SDK, telemetry patterns, what is App Insights, Application Insights guidance, instrumentation examples, APM 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。

Discovers available Azure OpenAI model capacity across regions and projects. Analyzes quota limits, compares availability, and recommends optimal deployment locations based on capacity requirements. USE FOR: find capacity, check quota, where can I deploy, capacity discovery, best region for capacity, multi-project capacity search, quota analysis, model availability, region comparison, check TPM availability. DO NOT USE FOR: actual deployment (hand off to preset or customize after discovery), quota increase requests (direct user to Azure Portal), listing existing deployments.

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 proven testing patterns — Arrange-Act-Assert (AAA), Given-When-Then, Test Data Builders, Object Mother, parameterized tests, fixtures, spies, and test doubles — to help write maintainable, reliable, and readable test suites. Use when the user asks about writing unit tests, integration tests, or end-to-end tests; structuring test cases or test suites; applying TDD or BDD practices; working with mocks, stubs, spies, or fakes; improving test coverage or reducing flakiness; or needs guidance on test organization, naming conventions, or assertions in frameworks like Jest, Vitest, pytest, or similar.

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 researched, fit-checked journalist list for a specific PR campaign. Prefer Medialyst's asynchronous media-list research workflow when available, with explicit approval before credit spend; otherwise produce a best-effort local list without guessed contacts.

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。

Foundational Python best practices, idioms, and code quality fundamentals

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 2 of the video editing pipeline. Finds and removes spoken mistakes — stutters, repeated words, false starts, and retakes (re-recorded lines) — from a talking-head recording. Use after cut-silences, when asked to cut mistakes, remove stutters / repeats / filler restarts, clean up flubs, or keep the best take. Works review-gated: it proposes every cut with context and a reason for approval, then renders only the approved cuts via ffmpeg. Requires a word-level transcript.

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 2 of the video editing pipeline. Finds and removes spoken mistakes — stutters, repeated words, false starts, and retakes (re-recorded lines) — from a talking-head recording. Use after cut-silences, when asked to cut mistakes, remove stutters / repeats / filler restarts, clean up flubs, or keep the best take. Works review-gated: it proposes every cut with context and a reason for approval, then renders only the approved cuts via ffmpeg. Requires a word-level transcript.

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。

Drive structured autoresearch iteration after evo:discover and the baseline commit. Use when the user invokes /evo:optimize or asks to try ideas, try variants, run experiments, use available GPUs, improve the current best/frontier, continue an evo search, or compare candidate changes in an evo workspace. The orchestrator plans and spawns optimization subagents; candidate edits/runs belong to those subagents. Width is set via subagents=N (1 for serial workloads, larger for parallel); the loop's structural value applies at any width.

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。

Read-only evo run reporting. Use when the user invokes /evo:report, asks what happened overnight, asks what improved recently, asks for the best/frontier candidates, asks for a quick score chart without opening the dashboard, or wants the scatter plot in chat output. Never run benchmarks, gates, Slurm commands, evo run, or ad-hoc verification scripts for report requests.

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。

Optimizes or restructures CLAUDE.md/AGENTS.md with progressive disclosure and zero information loss. Use when the user asks to optimize, audit, 精简/瘦身/重构, or split instruction files, asks for their best practices (最佳实践), sees Memory files taking a large share of /context, reports rules in instruction files being ignored, or a task starts moving instruction sections. Not for generic task drift unless instruction files are in scope; not for moving memory entries into docs (use claude-code-ops-router).

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。

Converts DOCX/PDF/PPTX and saved HTML/HTM to high-quality Markdown with automatic post-processing. Fixes pandoc grid tables, simple tables, image paths, CJK bold spacing, attribute noise, and code blocks; for PDFs also strips OCR garbage blocks, repeated headers/footers/watermarks, and absolute image paths from pymupdf4llm output. Benchmarked best-in-class (7.6/10) against Docling, MarkItDown, Pandoc raw, and Mammoth. Trigger on "convert document", "docx to markdown", "parse word", "doc to markdown", "解析word", "转换文档", "HTML to Markdown".

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。

Writes educational Teams channel posts about Claude Code features and best practices, using templates emphasizing concrete examples and underlying principles (e.g. context engineering). Use when writing a Teams post or announcement to teach colleagues Claude Code usage, announce a feature, share a tip, or document a lesson learned.

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。

Extract pixel-level data from an image of a chart or graph and produce a structured data table. Use when asked to extract data from a chart image, transcribe numbers from a graph, digitise a chart, or turn a screenshot of data into a table. Produces a structured table with extracted values, confidence levels, and a reconstructed chart source. Best used with Claude Opus 4.7 or newer for reliable chart data extraction.

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 clearly about whether bankruptcy is the right move, or whether another path fits better — without shame and without a sales pitch. Use when asked should I file for bankruptcy, is bankruptcy my best option, alternatives to bankruptcy, or what happens if I file. Produces an honest read on whether your situation is the kind bankruptcy actually helps, the main types and what each does (and doesn't) discharge, the real trade-offs (what you keep, the credit impact and its recovery, what's not dischargeable), the alternatives to weigh first (negotiation, debt management, doing nothing on time-barred debt), and a strong push to consult a bankruptcy attorney. Not legal advice.

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。

Publish 'how to work with me' as a literal API spec — endpoints (what to ask me for and what you'll get back), rate limits (meeting and interrupt tolerance), error codes (what happens when you surprise me Friday 5pm), auth (how to earn trust), and a changelog. Use when onboarding to a new team, when a new manager or report arrives, for a team working-styles session, or 'write my README/user manual'. Produces a personal API spec that's genuinely funny and secretly the best onboarding doc on the team.

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。

Figure out which AI tool actually fits the task in front of you — chatbot, coding assistant, image model, agent, or none — instead of forcing one tool onto everything. Use when asked which AI tool should I use for, what's the best AI for, do I even need AI for this, or should I use ChatGPT or something else. Produces a match between your task and the right kind of AI tool (with why), the trade-offs that matter for your case, when the answer is a non-AI tool or plain human effort, and how to try it cheaply before committing — so you pick by fit, not by hype or habit.

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。

Manages Git workflows including branching, commits, and pull requests. Use when working with Git, creating commits, opening PRs, managing branches, resolving conflicts, or when asked about version control 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。

Implements authentication, authorization, encryption, secrets management, and security hardening patterns. Use when designing auth flows, managing secrets, configuring CORS, implementing rate limiting, or when asked about JWT, OAuth, password hashing, API keys, RBAC, or security 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。