「rfi」の検索結果

สร้าง Dockerfile CI/CD yaml และ monitoring config ที่ production-ready ไม่พัง

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。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, passive voice, negative parallelisms, and filler phrases.

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。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer

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。

Auto-activate for Dockerfile, compose, Railway, Cloud Run, GKE, systemd, Kubernetes, Terraform, deploy scripts, or granian/litestar run at runtime. Not for packaging artifacts.

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 deployment configuration files (Dockerfile, vercel.json, wrangler.toml, etc.) based on target type.

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。

AutoResearch-inspired self-evolution loop for ANY Claude Code skill. Finds flaws, fixes them, benchmarks against a diverse prompt pool (anti-overfitting), and uses blind A/B judging. Fully automated — no human input needed during the loop.

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。

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

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。

Remove signs of AI-generated writing from text. Use when editing or reviewing text to make it sound more natural and human-written. Based on Wikipedia's comprehensive "Signs of AI writing" guide. Detects and fixes patterns including: inflated symbolism, promotional language, superficial -ing analyses, vague attributions, em dash overuse, rule of three, AI vocabulary words, negative parallelisms, and excessive conjunctive phrases. Credits: Original skill by @blader - https://github.com/blader/humanizer

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 Amazon Ads search terms ready for exact-match harvesting from auto, broad, phrase, or other discovery campaigns. Use when Codex needs standalone or Rocketcart MCP-aware search-term harvesting: classify terms by harvest readiness, resolve live IDs, choose safe destination campaigns/ad groups, preflight duplicates/current negatives/destination feasibility, decide whether source negatives are justified, execute only explicitly approved rows, and read back/monitor Sponsored Products or Sponsored Brands actions without unsafe negatives, duplicate routing, stale approvals, brand-defense cuts, own-ASIN-defense cuts, launch/rank mistakes, or low-sample overfitting.

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。

Call this skill when faced with "wicked problems", complex challenges, or when a user asks for strategic innovation, root-cause analysis, or long-term problem solving. Do not use for simple, linear tasks. This skill forces the agent to bypass superficial symptoms, map the entire ecosystem, and anticipate second-order consequences before proposing an intervention.

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。

Metal/wgpu/WGSL shader surfaces for native Rust gpui apps (Zed-family, pd-console), stockpiled with beautiful copy-pasteable shader-toy examples. Use for custom GPU fragment passes behind/around gpui panes: ocean/water shaders, pixelated waves and boats, a living harbor, dithered chrome borders, sonar sweeps, aurora/starfields, CRT/scanline post. Trigger on: wgsl, wgpu, metal shader, gpui shader, shadertoy, fragment shader, SDF, noise/fbm, ordered dithering, pixelation, render-to-texture, "pixelated waves and boats", living harbor water. NOT for: web/GLSL/three.js shaders (use a web tool), non-shader gpui motion (use rust-gpui-motion), general GUI layout/color (use beautiful-gui-design), CLI/TUI (use beautiful-cli-design).

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。

Multi-stage Docker build optimizer for minimal, secure production images. Activate on: Dockerfile optimization, multi-stage build, distroless image, container size reduction, Docker security scanning, BuildKit features. NOT for: container orchestration (use kubernetes-manifest-generator), CI/CD pipelines (use github-actions-pipeline-builder), runtime container config (use environment-config-manager).

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 writing/changing tests, mocks, or test-only methods on production classes — mocking-the-mock, production pollution, overfit assertions; for order, `test-driven-development` wins.

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 working with Docker — Dockerfile edits, docker-compose services, containers, or the dual-container (fast + Xdebug) setup — even when the user just says 'my container won't start'.

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。

Especialista em containerização Docker com conhecimento profundo de multi-stage builds, otimização de imagens, segurança em containers, orquestração com Docker Compose e padrões de deploy em produção. Use PROATIVAMENTE para otimização de Dockerfile, problemas em containers, problemas de tamanho de imagem, hardening de segurança, networking e desafios de orquestração.

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 quando o usuário quer integrar com a API do X (Twitter) via Xquik para buscar tweets, consultar perfis de usuários, extrair seguidores, executar sorteios, monitorar contas ou acessar tópicos em tendência. Também use quando o usuário menciona 'Xquik', 'Twitter API', 'X API', 'tweet scraper', 'extração de seguidores' ou 'monitoramento de Twitter'. Cobre REST API, webhooks e configuração de servidor MCP.

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。

Visualize métricas de treinamento, depure modelos com histogramas, compare experimentos, visualize grafos de modelos e perfil de desempenho com TensorBoard - kit de visualização de ML do Google

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。

HTCMC PCHSystem 专用 skill——指导如何在 git worktree 中正确启动/迁移开发栈 （根 docker-compose 的 postgres+backend、TestServer 的 mc-test、前端 Vite dev）。 PCHSystem 的栈路径锚定主仓（bind mount / external 网络 / MCDR 挂载 / 根 .env 插值）， worktree 的目录隔离与之天然冲突，常踩「端口对不上 / token 对不上 / 配置在别的分支」三类坑。 本 skill 给出按「worktree 改了什么」选择的迁移策略 + 端口/token/网络对齐清单 + 红线陷阱。 当用户在 worktree 里要起栈测试、提到「worktree 跑后端/前端/mc-test」「worktree 端口冲突」 「token 对不上 / 401」「主仓有 WIP 没法 checkout 分支」「MCDR reload 看不到 worktree 改动」， 或要在 worktree 改了 Dockerfile / pyproject / 端口 / .env 后验证时，就应使用本 skill。 不用：纯文档或单文件编辑、不涉及运行栈的常规开发、或仅在主仓主线本地开发（不起 worktree）。

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。

Especialista para todo el proceso de solicitud de empleo. Analiza ofertas de trabajo, optimiza perfiles (LinkedIn/CV) y genera cartas de presentación personalizadas. Genera CVs en ASCII a partir de una base de datos SQLite y una estructura de carpetas. cv_generator.py está adaptado de forma independiente -- no requiere la ejecución de BACH.

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。

Protocolo para crear, publicar, lanzar, auditar y mantener repositorios de GitHub de forma segura: verificar reglas locales y bloqueos, crear .gitignore antes del primer git add, realizar verificaciones de privacidad, preparar README/i18n/banner/metadatos, verificar etiquetas de release y lanzamientos de GitHub, y actualizar perfiles de organización, archivos llms.txt y enlaces a registros.

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 working with Checkov — checkov infrastructure-as-code security scanning. Covers Terraform, CloudFormation, Kubernetes, and Dockerfile scanning, policy management, custom checks, compliance frameworks, and suppression management. Use when scanning IaC for security misconfigurations, evaluating compliance, managing custom policies, or reviewing scan results.

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。

Autonomously improve a real artifact (code, training recipe, agent harness, data pipeline, prompt) against an objective and an evaluator, using Hypothesis Tree Refinement (HTR) from the Arbor paper. Use this whenever someone wants to iteratively optimize something over many experiments without overfitting — e.g. "get my model's eval score up", "improve this agent/harness", "tune this pipeline", "beat the baseline on this benchmark", "run a search over approaches and keep the best", "do an MLE-bench / Kaggle-style optimization", or any long-horizon "make this artifact better and don't just memorize the dev set" task. Trigger it even when the user doesn't say "Arbor" or "hypothesis tree" but describes repeated experiment-and-evaluate loops, branching exploration of competing ideas, or worries about a dev/test gap. Runs Claude itself as the coordinator with subagent executors in isolated git worktrees; for the standalone `arbor` CLI tool see references/arbor-upstream.md.

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。

Migrate a .NET 9 project or solution to .NET 10 and resolve all breaking changes. USE FOR: upgrading TargetFramework from net9.0 to net10.0, fixing build errors after updating the .NET 10 SDK, resolving source and behavioral changes in .NET 10 / C# 14 / ASP.NET Core 10 / EF Core 10, updating Dockerfiles for Debian-to-Ubuntu base images, resolving obsoletion warnings (SYSLIB0058-SYSLIB0062), adapting to SDK/NuGet changes (NU1510, PrunePackageReference), migrating System.Linq.Async to built-in AsyncEnumerable, fixing OpenApi v2 API changes, cryptography renames, and C# 14 compiler changes (field keyword, extension keyword, span overloads). DO NOT USE FOR: .NET Framework migrations, upgrading from .NET 8 or earlier (use migrate-dotnet8-to-dotnet9 first), greenfield .NET 10 projects, or cosmetic modernization. LOADS REFERENCES: csharp-compiler, core-libraries, sdk-msbuild (always); aspnet-core, efcore, cryptography, extensions-hosting, serialization-networking, winforms-wpf, containers-interop (selective).

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。

Migrate a .NET 10 project or solution to .NET 11 and resolve all breaking changes. This is a MIGRATION skill — use it when upgrading from .NET 10 to .NET 11, NOT for writing new programs. USE FOR: upgrading TargetFramework from net10.0 to net11.0, fixing build errors after updating the .NET 11 SDK, resolving source-breaking and behavioral changes in .NET 11 runtime, C# 15 compiler, and EF Core 11, adapting to updated minimum hardware requirements (x86-64-v2, Arm64 LSE), and updating CI/CD pipelines and Dockerfiles for .NET 11. DO NOT USE FOR: .NET Framework migrations, upgrading from .NET 9 or earlier, greenfield .NET 11 projects, or cosmetic modernization unrelated to the upgrade. NOTE: .NET 11 is in preview. Covers breaking changes through Preview 3.

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。