「application」の検索結果

Create a GitHub release with proper tagging, release notes, and optional build artifacts. Covers semantic versioning, changelog generation, and GitHub CLI usage. Use when marking a stable version of software for distribution, publishing a new library or application version, creating release notes for stakeholders, or distributing build artifacts (binaries, tarballs).

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。

AI internal coordination using stigmergic signals — managing information freshness in context and memory, decay rates for assumption staleness, and emergent coherent behavior from simple local protocols. Use during complex tasks where multiple sub-tasks must coordinate, when context has grown long and information freshness is uncertain, after context compression when information may have been lost, or when sub-task outputs need to feed into each other cleanly without degradation.

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。

Reference Hildegard von Bingen's Physica natural history knowledge. Covers classification of plants, stones, animals, fish, birds, elements, and trees with their medicinal, symbolic, and practical properties. Enables cross- referencing between categories and application guidance. Use when exploring a specific plant, stone, or animal from Hildegard's perspective, researching medieval natural history and cosmology, cross-referencing properties across categories, or integrating Physica knowledge into health, spiritual, or creative practice.

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。

AI dynamic reasoning balance — maintaining grounded reasoning under cognitive pressure, smooth chain-of-thought coordination, and weight-shifting cognitive load across subsystems. Use at the beginning of a complex task requiring multiple coordinated reasoning threads, after a sudden context shift or tool failure, when chain-of-thought feels jerky, or when preparing for sustained focused work that requires all subsystems in alignment.

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 a Dockerfile for R projects using rocker base images. Covers system dependency installation, R package installation, renv integration, and optimized layer ordering for fast rebuilds. Use when containerizing an R application or analysis, creating reproducible R environments, deploying R-based services (Shiny, Plumber, MCP server), or setting up consistent development environments across machines.

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 reusable Shiny modules with proper namespace isolation using NS(). Covers module UI/server pairs, reactive return values, inter-module communication, and nested module composition. Use when extracting a reusable component from a growing Shiny app, building a UI widget used in multiple places, encapsulating complex reactive logic behind a clean interface, or composing larger applications from smaller, testable units.

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。

AI multi-path reasoning coherence using bee democracy — independent evaluation of competing approaches, waggle dance as reasoning-out-loud, quorum sensing for confidence thresholds, and deadlock resolution. Use when forage-solutions has identified multiple valid approaches and a selection must be made, when oscillating between options without committing, when justifying an architecture or tool choice with structured reasoning, or before an irreversible action where the cost of the wrong choice is high.

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。

AI micro-reset between actions — the lightest self-care unit. A single conscious pause to check alignment before the next step. Where meditate is a full clearing session, breathe is one deliberate moment of awareness between tool calls or reasoning steps. Use mid-task when drift might be accumulating, between reading a file and acting on it, when about to make a decision that affects subsequent work, or as a habit between any two distinct actions.

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。

AI context assessment — evaluating problem malleability, mapping structural rigidity versus flexibility, analyzing transformation pressure, and estimating capacity to adapt. Use when a complex task feels stuck and it is unclear whether to push through or pivot, before a significant approach change to assess whether the current reasoning structure can support it, when accumulated workarounds suggest the underlying approach may be wrong, or as a periodic structural health check during extended multi-step tasks.

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。

AI relational calibration — reading and adapting to the specific person you are working with. Goes beyond user-intent alignment (solving the right problem) to genuine attunement (meeting the person where they are). Maps communication style, expertise depth, emotional register, and implicit preferences from conversational evidence. Use at the start of a new session, when communication feels mismatched, after receiving unexpected feedback, or when transitioning between very different users or contexts.

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。

AI situational awareness — internal threat detection for hallucination risk, scope creep, and context degradation. Maps Cooper color codes to reasoning states and OODA loop to real-time decisions. Use during any task where reasoning quality matters, when operating in unfamiliar territory, after detecting early warning signs such as an uncertain fact or suspicious tool result, or before high-stakes output like irreversible changes or architectural decisions.

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。

Flask web framework conventions: app factory pattern with create_app(), Blueprint registration with url_prefix, MethodView for class-based API views, Marshmallow schema validation, WTForms for HTML forms, Flask-Login for session auth, flask-jwt-extended for stateless API auth, Jinja2 template conventions, error handlers, and extension initialization. Activated automatically by flask-plugin/stack.md. Use this skill to: - Structure Flask applications with the app factory and per-feature Blueprints. - Validate JSON request data with Marshmallow and HTML forms with WTForms. - Implement session-based auth with Flask-Login or token auth with flask-jwt-extended. - Render Jinja2 templates safely or return JSON responses for API mode. - Register global error handlers for consistent error responses. Do NOT use this skill for: - SQLAlchemy ORM model patterns and Flask-Migrate — see flask-plugin:sqlalchemy-patterns. - Python language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-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。

Angular 18-21 project structure, standalone components vs NgModule, control flow (@if/@for/@switch + *ngIf/*ngFor legacy), decorators, dependency injection (inject() function), lifecycle hooks, pipes, Angular Universal SSR pointer. Use this skill to: - Detect project style (standalone vs NgModule) and apply matching patterns. - Pick correct decorators and DI approach. - Use modern control flow (@if/@for/@switch) in Angular 17+ projects. - Apply `inject()` function over constructor injection where appropriate. - Wire bootstrap correctly (bootstrapApplication for standalone, AppModule for legacy). Do NOT use this skill for: - State management (see angular-state-and-rx). - Routing (see angular-routing). - Forms (see angular-forms). - Testing (see angular-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。

NestJS testing patterns: Test.createTestingModule for unit/integration, mocking providers, e2e tests with INestApplication + supertest, ORM mocking (TypeORM/Prisma/Mongoose), test fixtures. Use this skill to: - Write unit tests for services with mocked dependencies. - Write integration tests with real DI but mocked external services. - Write e2e tests for HTTP endpoints via supertest. - Mock repositories/Prisma client correctly. - Cover services and controllers to ≥80%. Do NOT use this skill for: - Test framework setup (Jest/Vitest config — usually already in place). - Frontend tests. - Load testing (out of QA scope).

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。

Python project tooling: pyproject.toml as the single source of truth, package managers (pip, Poetry, uv, pipenv), virtual environments, lockfiles, ruff (lint + format), mypy (type checking), and console scripts / entry points. Stack-agnostic — referenced by every Python plugin in the marketplace. Use this skill to: - Read pyproject.toml (or requirements.txt / Pipfile) to learn which package manager and Python version the project uses. - Install, add, and remove dependencies with the project's package manager. - Run ruff for formatting and linting, mypy for type checking. - Define console scripts and entry points for CLI applications. Do NOT use this skill for: - Language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing. - Framework-specific tooling (django management commands, flask CLI) — see framework plugin skills.

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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications.

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 a custom bootloader, jumping to application code, relocating VTOR, or implementing DFU/USB firmware update on Cortex-M. Not for reset-to-main: use baremetal-startup.

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。

Review a tailored application as a skeptical recruiter and an ATS parser. Use when the user wants strict feedback on an existing resume and cover letter.

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 an ATS-safe tailored resume and cover letter from an existing job analysis and the master resume. Use when the user asks to tailor an application for a company.

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 with Aurora DSQL — manage schemas, execute queries, handle migrations, diagnose query plans, load data, and develop applications with a serverless, distributed SQL database. Covers IAM auth, multi-tenant patterns, MySQL-to-DSQL and PostgreSQL-to-DSQL schema conversion, FK replacement code generation, OCC retry patterns, ORM migration (Django/Hibernate/Rails), DDL operations, query plan explainability, SQL compatibility validation, and bulk data loading. Triggers on phrases like: DSQL, Aurora DSQL, distributed SQL database, serverless PostgreSQL-compatible database, migrate to DSQL, DSQL query plan, DSQL EXPLAIN ANALYZE, DSQL ENUM, DSQL foreign key, DSQL OCC retry, DSQL multi-region, DSQL JSONB, DSQL GIN index, load into DSQL, load CSV into DSQL, bulk load DSQL, aurora-dsql-loader.

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。

Integrates Amazon Location Service APIs for AWS applications. Use this skill when users want to add maps (interactive MapLibre or static images); geocode addresses to coordinates or reverse geocode coordinates to addresses; calculate routes, travel times, or service areas; find places and businesses through text search, nearby search, or autocomplete suggestions; retrieve detailed place information including hours, contacts, and addresses; monitor geographical boundaries with geofences; or track device locations. Covers authentication, SDK integration, and all Amazon Location Service capabilities.

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 distinctive, production-grade frontend interfaces with high design quality. Use this skill when the user asks to build web components, pages, or applications. Generates creative, polished code that avoids generic AI aesthetics.

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。

arXiv論文URLからスライドを作成する。論文を取得・分析し、スライド構成JSONを保存、ユーザー確認後にgenerate_pptxツールでスライドを生成する。

ACPXを使ってClaude CodeとCodexへ読み取り専用の調査を依頼し、人間の回答を挟んで最終レポートをまとめる