「environment」の検索結果

Applies best practices for logging (zerolog/zap), project structure (cmd/internal/pkg), middleware registration order, and environment configuration in Go Fiber v2/v3 applications.

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Orchestrates SDD project initialization — version detection, environment verification, scaffolding, and git setup.

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Orchestrates local Kubernetes development environment management.

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Work with the @upstash/box SDK for sandboxed cloud containers with AI agents, shell, filesystem, and git. Use when building with Upstash Box, creating sandboxed environments, running AI agents in containers, or orchestrating parallel boxes.

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Check whether the knowledge base shelf-index is stale relative to the library files. Reports drifted entries without rebuilding. Designed to be invoked from environment validation or pre-push hooks as an opt-in check. Default mode is warning; strict mode fails with non-zero exit when any drift is detected.

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Deploy, diff, bootstrap, inspect, roll back, or destroy AWS CDK applications with the community CDKD CLI while preserving safe production and state-management boundaries. Use when the user mentions cdkd or CDK Direct, asks for faster CDK deployments in development or test environments, or wants to evaluate whether an existing CDK app can use CDKD. Also use for CDKD import, export, state, events, and deployment troubleshooting. Prefer the upstream AWS CDK CLI for production and for existing CloudFormation-managed stacks unless the user explicitly approves a management migration.

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Comprehensive audit of a user's entire Claude environment — combines Project audit (six-dimension Project Scorecard, seven anti-patterns) with Global audit (six-dimension Global Layer Scorecard) plus Cross-Layer Alignment Check across all nine layers and Evolutionary Recommendations across four pathways. Produces a unified action plan. Use when user says "full audit of everything," "audit my entire Claude setup," "full stack audit," "comprehensive review of my project and preferences," "check everything," or wants the complete health check of both a specific Project AND their global configuration. Also use when a project audit reveals cross-layer issues that require full-stack visibility. Do NOT use for auditing only a Project (use rootnode-project-audit if available) or only global layers (use rootnode-global-audit if available). Do NOT use for single prompt evaluation (use rootnode-prompt-validation if available). Run on Opus 5 or Sonnet 5 at `high` effort (both defaults); depth reduces on legacy models.

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Designs Claude Code prompts and CC environments. Produces CLAUDE.md drafts, agent topologies, scope-authorization frameworks, halt triggers, Skills/hooks/MCP plans, chat-to-CC handoff specs, and EXECUTION_PLAN.md remediation plans. Five modes: DESIGN (new CC deployments), EVOLVE (updates from friction), RESEARCH (evaluate a CC tool/pattern), TEMPLATE (reusable artifacts), REMEDIATE (consume hygiene findings → produce + execute plan). Do NOT use REMEDIATE for direct cleanup (Cat 1–10 — use rootnode-repo-hygiene Phase 2). Do NOT use for hygiene scanning (rootnode-repo-hygiene), chat prompts (rootnode-prompt-validation), or chat Projects (rootnode-project-audit).

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Implement and execute approved research Experiment, Tuning, or Design Cards with reproducible logs, metrics, environment, and artifacts. Use for bounded coding, debugging, and runs; not for changing claims, priorities, budgets, or the Research Spine.

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Review a data analysis for quality, correctness, and reproducibility. Covers data quality assessment, assumption checking, model validation, data leakage detection, and reproducibility verification. Use when reviewing a colleague's analysis before publication, validating an ML pipeline before production deployment, auditing a report for regulatory or business decision-making, or performing a second-analyst review in a regulated environment.

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Provision and manage cloud infrastructure using Terraform with HCL modules, remote state backends, workspaces, and plan/apply workflow. Implement infrastructure as code patterns with variable management, output values, and state locking for team collaboration. Use when provisioning new cloud infrastructure, migrating from ClickOps or CloudFormation to declarative IaC, managing multi-environment infrastructure, versioning infrastructure changes alongside application code, or enforcing standards through reusable modules.

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Perform a Computer Systems Validation (CSV) assessment following GAMP 5 methodology. Covers user requirements, risk assessment, IQ/OQ/PQ planning, traceability matrix creation, and validation summary reporting. Use when a new computerized system is being introduced in a GxP environment, when an existing validated system is undergoing significant change, when periodic revalidation is required, or when a regulatory inspection demands a validation gap analysis.

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Cultivate defensive situational awareness, threat assessment, and mental clarity under pressure. Covers the Cooper color code awareness system, body language reading and intent detection, verbal de-escalation, moving mindfulness in public spaces, combat focus and the OODA loop, rapid grounding techniques for acute stress, context-specific integration, and ongoing review and refinement of awareness skills. Use when entering unfamiliar or potentially hostile environments, needing to assess a situation for safety, de-escalating a verbal confrontation, or integrating awareness practice into daily movement.

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Implement audit trail functionality for R projects in regulated environments. Covers logging, provenance tracking, electronic signatures, data integrity checks, and 21 CFR Part 11 compliance. Use when an R analysis requires electronic records compliance (21 CFR Part 11), when you need to track who did what and when in an analysis, when implementing data provenance tracking, or when creating tamper-evident analysis logs for regulatory submissions.

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Install and configure the putior R package for workflow visualization. Covers CRAN and GitHub installation, optional dependencies (mcptools, ellmer, shiny, shinyAce, logger, plumber2), and verification of the complete annotation-to-diagram pipeline. Use when setting up putior for the first time, preparing a machine for workflow visualization tasks, when a downstream skill requires putior to be installed, or restoring an environment after an R version upgrade or renv wipe.

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Deploy Shiny applications to shinyapps.io, Posit Connect, or Docker containers. Covers rsconnect configuration, manifest generation, Dockerfile creation, and deployment verification. Use when publishing a Shiny app for external or internal users, moving from local development to a hosted environment, containerizing a Shiny app for Kubernetes or Docker deployment, or setting up automated deployment pipelines.

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Deploy applications to Kubernetes clusters using kubectl manifests for Deployments, Services, ConfigMaps, Secrets, and Ingress resources. Implement health checks, resource limits, rolling updates, and Helm chart packaging for production deployments. Use when deploying new applications to EKS, GKE, AKS, or self-hosted clusters, migrating from Docker Compose to container orchestration, implementing zero-downtime rolling updates, or setting up multi-environment deployments across dev, staging, and production.

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Configure the putior MCP server to expose 16 workflow visualization tools to AI assistants. Covers Claude Code and Claude Desktop setup, dependency installation (mcptools, ellmer), tool verification, and optional ACP server configuration for agent-to-agent communication. Use when enabling AI assistants to annotate and visualize workflows interactively, setting up a new development environment with putior MCP integration, or configuring agent-to-agent communication via ACP for automated pipelines.

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Create general-purpose Dockerfiles for Node.js, Python, Go, Rust, and Java projects. Covers base image selection, dependency installation, user permissions, COPY patterns, ENTRYPOINT vs CMD, and .dockerignore. Use when containerizing an application for the first time, creating a consistent build/runtime environment, preparing an app for cloud deployment or Docker Compose, or when no existing Dockerfile is present in the project.

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Set up a Blender scene programmatically via Python (bpy) with objects, materials, lighting, camera, and environment configuration. Use when creating reproducible 3D visualization scenes, automating product or architectural rendering setup, generating multiple scene variations programmatically, building template scenes for batch rendering workflows, or integrating 3D visualization into data pipelines.

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Containerize an R-based MCP (Model Context Protocol) server using Docker. Covers mcptools integration, port exposure, stdio vs HTTP transport, and connecting Claude Code to the containerized server. Use when deploying an R MCP server without requiring a local R installation, creating a reproducible MCP server environment, running MCP servers alongside other containerized services, or distributing an MCP server to other developers.

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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.

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FastAPI web framework conventions: APIRouter with prefix/tags/dependencies, Pydantic v2 schemas (BaseModel, model_config, field_validator, model_validator), dependency injection with Depends, async SQLAlchemy session yielding, OAuth2PasswordBearer + JWT auth, lifespan context manager, pydantic-settings configuration, OpenAPI customization, and HTTPException error handling. Activated automatically by fastapi-plugin/stack.md. Use this skill to: - Structure FastAPI apps with per-feature APIRouter modules and a central app factory. - Write Pydantic v2 request and response schemas with proper validators. - Build a reusable Depends-based dependency chain for DB session, auth, and pagination. - Implement JWT-based authentication with get_current_user dependency. - Configure the app from environment variables via pydantic-settings. Do NOT use this skill for: - SQLAlchemy ORM model configuration and Alembic migrations — see fastapi-plugin:sqlalchemy-patterns. - Python language idioms — see python-foundation:python-conventions. - Testing patterns — see python-foundation:pytest-testing.

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Django web framework conventions: app layout, settings split (base/local/production), URLconf with app namespacing, CBV and DRF ViewSets, DRF serializers and permissions, form validation, signals, Django admin registration, and middleware. Activated automatically by django-plugin/stack.md. Works alongside python-foundation:python-conventions and django-plugin:django-orm-patterns. Use this skill to: - Structure a Django project with multiple apps and correct URLconf hierarchy. - Write CBVs and DRF ViewSets with appropriate permissions and serializers. - Configure settings correctly for different environments. - Use signals for decoupled event handling between apps. - Register models in Django admin with useful list_display and search_fields. Do NOT use this skill for: - Django ORM model field finalization and migration patterns — see django-plugin:django-orm-patterns. - Python language idioms (type hints, dataclasses, enums) — 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。