「environment」の検索結果

Abductive reasoning about causes. Takes a phenomenon, separates observations from interpretations, then spawns diagnosticians applying different reasoning lenses (technical, human-factors, process, incentive-structure, environmental, temporal, measurement-artifact, statistical) in isolation. Orchestrator evaluates candidate causes for fit-against-evidence, calibrates confidence honestly, and reports leading candidate(s) with distinguishing evidence needed. Produces feedback only — no code, no tickets, no artifacts.

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Check the local environment for Spec Kit by running `specify check` (and `specify version`). USE FOR: verifying required tools are installed, diagnosing a broken spec-kit setup, reporting CLI version/feature capabilities. DO NOT USE FOR: installing or upgrading the CLI itself (use the speckit-self skill).

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Configures environment variables and secrets protection

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Generates sustainability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify environmental impact requirements, and provide actionable recommendations to build, deploy, and manage the workload sustainably in Google Cloud.

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Plan, create, and configure production-ready Google Kubernetes Engine (GKE) clusters using the golden path Autopilot configuration. Covers Day-0 checklist, Autopilot vs Standard, networking (private clusters, VPC-native, Gateway API), security (Workload Identity, Secret Manager, RBAC hardening), observability, scaling, cost optimization, and AI/ML inference. WHEN: create GKE cluster, provision GKE environment, design GKE networking, secure GKE, optimize GKE cost, GKE autoscaling, GKE inference, GKE upgrade, GKE observability, GKE multi-tenancy, GKE batch, GKE HPC, GKE compute class.

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Guides the usage of the Gemini API on Agent Platform with the Google Gen AI SDK. Use when the user asks about using Gemini in an enterprise environment or explicitly mentions Vertex AI, Google Cloud, or Agent Platform. Covers SDK usage (Python, JS/TS, Go, Java, C#), capabilities like Live API, tools, multimedia generation, caching, and batch prediction.

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Use when morphir-scala work needs environment diagnostics or build/network/sandbox unblocking; reference repository management; branch lifecycle refresh after squash-merging a target branch into main; Morphir IR spec/schema sync or export; or task-tracking configuration and beads mode resolution.

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Unified verification engine for Python data science projects. Covers environment checks, type checking, linting, tests, security scans, code review with DS anti-patterns, and notebook checks. Commands (/verify, /quality-gate) invoke different subsets of this skill.

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Inspired by the ClawIntelligentMemory project, this skill ensures Kim Assistant's environment stays clean and its memory stays dense.

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Query and filter Datadog logs from the shell using the Composio CLI. Run scoped log searches, pivot across services/environments, and export structured JSON for incident investigation and diagnostics.

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Safe deployment workflow for Drupal 10/11 sites: pre-flight checks, backup, the correct update sequence (composer install, database updates, config import, cache rebuild), verification, and rollback plan. Use when deploying to any environment, releasing to production, or when the user asks to "push changes live", "update the server", or run a release. Also use for multisite releases where each site needs its own database update pass.

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Use this skill when authoring or debugging GitLab CI/CD pipelines (.gitlab-ci.yml) — e.g. "add a CI pipeline for this Drupal project", "run phpcs/phpstan/phpunit in GitLab CI", "deploy with drush from a pipeline", "why is my job not running", "cache composer dependencies", or anything involving stages, rules, artifacts, environments, or GitLab runners.

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Use for operational Drupal 11 workflows in DDEV environments, including safe updates, backup-first procedures, and troubleshooting commands.

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Delegate implementation to Codex, grok, or cursor-agent, then review the diff, send it back to iterate, gate on the full test suite, and ship it as a PR. Use this whenever the user wants Codex, the grok 后端, or cursor-agent to write code, mentions handing off / delegating implementation to one of those backends, asks to work through a plan or spec unit-by-unit with an implementation backend doing the coding, or wants a review-and-merge loop wrapped around delegated output — and also when resuming such a loop ("keep going", "next unit", "继续下一个"). It encodes constraints that are expensive to rediscover: the implementer runs in the real environment behind backend-specific git and publication boundaries, must not be pointed at a full test suite by default, and its self-report is a claim rather than evidence. This loop expects an approved plan or an equivalently precise spec; settle an unsolved high-level goal into a plan first, using the engineering-mode skill when it is installed.

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Stay ahead of EPA enforcement at cement plants. Free CementOps Compliance Suite skill. NESHAP Subpart LLL limits, CEMS QA/QC, Title V permits, alternative fuels emissions, exceedance response, and NOV defense procedures.

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Drafts Brownfields Agreements for contaminated-property transactions under CERCLA, EPA brownfields programs, and state voluntary cleanup programs. Structures BFPP liability protections, All Appropriate Inquiries documentation, remediation obligations, institutional controls, cost allocation, and long-term stewardship covenants. Use when drafting brownfields purchase agreements, prospective purchaser agreements, voluntary cleanup MOAs, or environmental covenant frameworks.

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Create inline Mermaid v11 diagram blocks — flowcharts, sequence, class, ER, Gantt, state, timeline, user-journey, and 20+ other types — rendered in markdown files and browser environments. Zero external dependencies; mmdc is optional for CLI export.

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Session-scoped safety guardrails for destructive commands. Warns before rm -rf, DROP TABLE, force-push, git reset --hard, kubectl delete, and similar destructive operations. User can override each warning. Active for the current session only. Use when touching prod, debugging live systems, or working in a shared environment. Use when asked to "be careful", "safety mode", "prod mode", or "careful mode". NOT for scoping edits to a specific directory (see mk:freeze).

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Python Invoke task automation for DTX website. This skill should be used when running repo commands, backend tests via Docker, database migrations, updating invoke tasks, Docker operations, or workflow automation. Supports dev/test/prod environments with run, exec, up, down commands. References docs/development/invoke-tasks.md for complete command reference.

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Initialize or safely upgrade a processor project's root AGENTS.md from a maintained baseline. Use when starting a processor project, adding project-level Agent collaboration rules, or comparing an existing AGENTS.md with the package baseline. This skill only handles AGENTS.md; it does not scaffold documentation, inspect or configure environments, install tools, or modify processor source.

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Use when the user asks about Codex Rules behavior, injected project rules, supported rule file locations, matching, or environment configuration.

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Generate realistic product-in-use lifestyle scenes. Places the product in believable contexts of use (who, where, when, doing what) with natural lighting and real texture, for lifestyle/editorial/ecommerce. Use when the user says "lifestyle shot", "product in use", "scene", "show it being used", "in-context photography", or needs people/environment around the product. Part of the Creative Production set.

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Heuristic search-based temporal planning and scheduling for complex multi-constraint environments

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Decision-theoretic framework for agents embedded within the environments they model and act upon

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。