「transform」の検索結果

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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 and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through 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。

Transform clarified user requests into structured delegation prompts optimized for specialist agents (cto-architect, strategic-cto-mentor, cv-ml-architect). Use after clarification is complete, before routing to specialist agents. Ensures agents receive complete context for effective work.

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 or edit raster images when the task benefits from AI-created bitmap visuals such as photos, illustrations, textures, sprites, mockups, or transparent-background cutouts. Use when Codex should create a brand-new image, transform an existing image, or derive visual variants from references, and the output should be a bitmap asset rather than repo-native code or vector. Do not use when the task is better handled by editing existing SVG/vector/code-native assets, extending an established icon or logo system, or building the visual directly in HTML/CSS/canvas.

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。

Transform research into Opportunity Solution Tree (Teresa Torres method). Map outcomes, opportunities, solutions, and experiments.

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。

Neo4j Visualization Library (NVL) — framework-agnostic graph rendering for the browser. Covers @neo4j-nvl/base (NVL class, nodes/relationships, Canvas vs WebGL renderer), @neo4j-nvl/interaction-handlers (ZoomInteraction, PanInteraction, DragNodeInteraction, ClickInteraction, HoverInteraction, BoxSelectInteraction, LassoInteraction, KeyboardInteraction), and @neo4j-nvl/react (InteractiveNvlWrapper, BasicNvlWrapper, StaticPictureWrapper). Use when rendering a Neo4j graph in a browser, feeding driver results through nvlResultTransformer, choosing Canvas vs WebGL, wiring node/relationship click/hover/drag handlers, or embedding NVL in React, Vite, or vanilla JS apps. Does NOT handle Cypher query authoring — use neo4j-cypher-skill. Does NOT handle driver lifecycle, sessions, or executeQuery setup — use neo4j-driver-javascript-skill. Does NOT handle GraphVisualization/Needle default embed — use @neo4j-ndl/react.

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 writing tests for data or ML code — what to test at each layer (transforms, schemas, properties, pipeline smoke, model-quality thresholds, determinism and parity), how to build small synthetic fixtures, and what not to test

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 building or changing features, preprocessing, encoders, resampling or train/validation/test splits — keep every fitted transform inside a Pipeline fitted on training folds only, and build time and group features without seeing the future or the same entity twice

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。

Transform raw data from CSVs, Google Sheets, or databases into executive-ready reports with visualizations, key metrics, trend analysis, and actionable recommendations. Creates data-driven narratives for leadership. Use when users need to turn spreadsheets into executive summaries or board reports.

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。

Godot 4.x .tscn 场景文件纯文本格式规范与 AI 操作指南 — 文件结构、资源引用、 Transform 变换、属性值格式、信号连接，以及 AI 直接读写 .tscn 文件的操作方法。

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。

Transform an output-focused roadmap (feature list) into an outcome-focused one. Rewrites initiatives as outcome statements reflecting user and business impact. Use when a roadmap lists features instead of results, when making a roadmap more strategic, or when communicating what success looks like vs what will be built.

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, compose, migrate, and review TypeScript runtime type guards with is-kit. Use when adding reusable guards; replacing typeof, null checks, or handwritten type predicates; narrowing unknown values; validating JSON or API responses; building collection or object schemas with struct or typedStruct; or reviewing existing is-kit usage. Do not use for one-off environment checks or validation that requires data transformation or rich error reporting.

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。

Transform any internship experience into resume-ready, interview-ready expressions — for all roles: dev, product, operations, design, sales, finance.

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 this skill when the user wants intellectual understanding — learning how or why something works, not getting a task done or soliciting Claude's judgment. Trigger for: - Explicit learning requests: teach, explain, ELI5, walk me through, quiz me, flashcards, "I'm rusty on"; definitions ("what is X") - Terse concept names implying "help me understand this": "Galois theory," "transformers, from scratch" - Confusion signals: "won't stick," "keep mixing these up," "not getting it" - Learning-path questions: prerequisites, sequencing, what to study before X - Conceptual questions about mechanisms, causes, or dynamics Don't trigger for: - Tasks: coding, writing, calculation, translation, factual lookup, news updates - Personal troubleshooting; resource/textbook recommendations - Claude's evaluative verdict: opinion prompts ("do you think X", "settle this", "honest take", "is X dead / still taken seriously") and interpretive takes ("was X really as harsh as people say")

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 Connection Auth Rules for a Monte Carlo connection type. Fetches live connector schemas and transform steps from the apollo-agent repo.

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。

First-time repo setup for new projects. Transforms the cloned OCGS template into a clean, ready-to-use game project with your own identity.

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 and train AI learning plugins with AgentDB's 9 reinforcement learning algorithms. Includes Decision Transformer, Q-Learning, SARSA, Actor-Critic, and more. Use when building self-learning agents, implementing RL, or optimizing agent behavior through 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。

Stream-JSON chaining for multi-agent pipelines, data transformation, and sequential workflows

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 this when performing DataFrame operations — including loading, filtering, joining, aggregating, transforming, or reshaping tabular data with polars or pandas.

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。

Define the scope and purpose of a complex inquiry before mapping or futures work begins. Use when a class or group needs to agree what they are investigating, who it matters to, and at what scale.

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 a learning sequence teaching prompt quality — comparing vague vs. refined prompts to show why specificity and context transform AI output. Use when students use AI without understanding why output quality varies.

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。

Transform ideas into detailed visual specifications through scenario-driven 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。

Craft Cloud — Pixel & Tonic's serverless hosting platform for Craft CMS. Covers craft-cloud.yaml configuration, the Build → Migrate → Release deploy pipeline, the craftcms/cloud extension package, edge image transforms via Cloudflare, edge static caching with cache.rules + ESI, Cloud-managed S3 filesystem, MySQL 8 / Postgres 15 databases (no MariaDB, no tablePrefix), Console-based command runner and scheduled cron (once-per-hour minimum), auto-handled queue jobs, custom domains and SSL, preview environments per branch, Cloud limitations (ephemeral filesystem, no SSH, no .htaccess, no built-in mail), plugin development requirements for Cloud compatibility, and self-hosted → 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。

Servd (servd.host) — Craft-specialised managed hosting for Craft CMS. Covers git push-to-deploy with the optional servd.yaml build config, local → staging → production environments with uni-directional Project Config sync, the servd/craft-asset-storage plugin (S3-backed Flysystem volumes on the svdcdn.com CDN, off-server image transforms, Imager-X/ImageOptimize integrations), Servd's static caching (full vs tag-based purge, {% dynamicInclude %}, CSRF injection, cache-busting) and running Blitz alongside it in reverse-proxy mode, MariaDB/MySQL databases over an SSH tunnel, automatic + manual backups, the Dedicated Queue Runner, environment variables and secrets, the ephemeral load-balanced filesystem (Redis + remote volumes for runtime files), plugin/feature constraints, and Servd-vs-Craft-Cloud differences.

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。