開発のスキル

Implements, adopts, and reviews iOS 26+ Liquid Glass in SwiftUI: glassEffect, GlassEffectContainer, correctness, performance, and design fit. Use when adding Liquid Glass to a SwiftUI app or refactoring existing UI to the new design language.

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Grounds every implementation decision in official documentation. Use when you want to verify an approach against the official docs before implementing it, or when you want authoritative, source-cited code free from outdated patterns. Use when building with any framework or library where correctness matters.

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Use when turning GitHub issues or bug reports into reproducible coding-agent repair loops with sandboxed execution, focused tests, patch generation, and regression verification.

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。

Explains and designs Microsoft Fabric Lakehouse solutions: Delta tables, the SQL analytics endpoint, shortcuts, and AI functions. Use when building, optimizing, or documenting a Fabric Lakehouse.

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Migrates Oracle PL/SQL stored procedures to PostgreSQL PL/pgSQL. Translates Oracle-specific syntax, preserves method signatures and type-anchored parameters, leverages orafce where appropriate, and applies COLLATE "C" for Oracle-compatible text sorting. Use when converting Oracle stored procedures or functions to PostgreSQL equivalents during a database 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。

Skill for using the command-line tool pdftk (PDFtk Server) for working with PDF files. Use when asked to merge PDFs, split PDFs, rotate pages, encrypt or decrypt PDFs, fill PDF forms, apply watermarks, stamp overlays, extract metadata, burst documents into pages, repair corrupted PDFs, attach or extract files, or perform any PDF manipulation from the command line.

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 a coding agent (Claude Code, Cursor, Codex, Copilot CLI) burns through tokens or usage limits, sessions get slow or hit context limits, or the user asks to cut agent cost. Measures where the tokens go, then applies levers in order: session hygiene, always-loaded context (CLAUDE.md, skills, MCP), tool-output filtering, subagent delegation, output verbosity, and model/effort choice.

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 explicitly asks to map, document, or onboard into an existing codebase. Trigger for prompts like "map this codebase", "document this architecture", "onboard me to this repo", or "create codebase docs". Do not trigger for routine feature implementation, bug fixes, or narrow code edits unless the user asks for repository-level discovery.

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 and reviews dbt projects targeting Snowflake: models, schema.yml metadata, sources, tests, macros, and project structure. Use when building or reviewing dbt models, generating dbt YAML, or applying dbt best practices.

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Runs an 11-step data cleaning and variable screening pipeline for pre-loan credit risk models: sample analysis, OOS split, missing-rate, IV, PSI, and correlation filters. Use when preparing raw credit data for scorecard or default-prediction 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。

Use when unsure which engineering-workflow skill applies to the task at hand. Routes from development phase — idea, spec, plan, implement, test, review, ship — to the right skill, and shows how they chain together across a feature or bugfix.

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。

Refactors and reviews SwiftUI views: consistent layout ordering, subview extraction, dependency injection, Observation, and MV versus view-model patterns. Use when SwiftUI views have grown large or inconsistent.

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。

Structured decision-making framework for technical proposals and trade-off analysis. When the user faces a choice between multiple approaches (architecture decisions, tool selection, refactoring strategies, migration paths), this skill produces a 1-3-1 format: one clear problem statement, three distinct options with pros/cons, and one concrete recommendation with definition of done and implementation plan. Use when the user asks for a "1-3-1", says "give me options", or needs help choosing between competing approaches.

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This skill should be used when the user asks to "diagnose context problems", "fix lost-in-middle issues", "debug agent failures", "understand context poisoning", or mentions context degradation, attention patterns, context clash, context confusion, or agent performance degradation. Provides patterns for recognizing and mitigating context failures.

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 all projects in a .NET solution, classifies each for Oracle-to-PostgreSQL migration eligibility, and produces a persistent master migration plan. Use at the start of an Oracle-to-PostgreSQL migration of a multi-project .NET solution.

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 PostgreSQL logical replication slots retain WAL, become orphaned or invalid after switchover, or must be proven synchronized and usable before failover.

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Creates structured bug reports for defects found during Oracle-to-PostgreSQL migration. Use when documenting behavioral differences between Oracle and PostgreSQL as actionable bug reports with severity, root cause, and remediation steps.

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Discovers and integrates third-party APIs using the context-matic MCP server. Uses `fetch_api` to find available API SDKs, `ask` for integration guidance, `model_search` and `endpoint_search` for SDK details. Use when the user asks to integrate a third-party API, add an API client, implement features with an external API, or work with any third-party API or SDK.

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。

Visual whiteboard collaboration for Copilot CLI. Creates an interactive whiteboard that opens in your browser — draw, sketch, add sticky notes, then share everything back with Copilot. Copilot sees your drawings and text, and responds with analysis, suggestions, and ideas. Use in Copilot CLI when an idea is easier to sketch than to describe in text.

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 before writing code on anything non-trivial: a new project or feature, ambiguous or incomplete requirements, a change spanning multiple modules, an architectural decision, or work over ~30 minutes. Runs a gated Specify → Plan → Tasks → Implement workflow with human review at each phase. Skip for single-line fixes.

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。

Interactive onboarding tour for the context-matic MCP server. Walks the user through what the server does, shows all available APIs, lets them pick one to explore, explains it in their project language, demonstrates model_search and endpoint_search live, and ends with a menu of things the user can ask the agent to do. USE FOR: first-time setup; "what can this MCP do?"; "show me the available APIs"; "onboard me"; "how do I use the context-matic server"; "give me a tour". DO NOT USE FOR: actually integrating an API end-to-end (use integrate-context-matic instead).

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。

Makes the agent list the files it needs to see before answering a question about the codebase, instead of guessing. Use when a question depends on code the agent has not read yet, or when earlier answers were confidently wrong about the 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。

Step-by-step guide for capturing key application requirements for NoSQL use-case and produce Azure Cosmos DB Data NoSQL Model design using best practices and common patterns, artifacts_produced: "cosmosdb_requirements.md" file and "cosmosdb_data_model.md" file. Use when designing a new Azure Cosmos DB for NoSQL data model or reviewing partition keys and document shapes.

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Document analysis with inline source screenshots. When you ask Copilot to analyze a document, Eyeball generates a Word doc where every factual claim includes a highlighted screenshot from the source material so you can verify it with your own eyes.

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。