「hig」の検索結果

Provides recommendations for environmental sustainability, carbon footprint reduction, and energy efficiency based on the Sustainability pillar of the Google Cloud Well-Architected Framework (WAF). Use when the user asks to assess, design, or optimize Google Cloud workloads for sustainability—including the shared responsibility model, selecting low-carbon regions (CFE%), reducing resource and AI/ML energy waste, designing efficient software and storage lifecycles, or measuring and tracking emissions using Google Cloud Carbon Footprint. Don't use for financial cost reduction (use google-cloud-waf-cost-optimization), latency and throughput tuning (use google-cloud-waf-performance-optimization), or high availability and disaster recovery (use google-cloud-waf-reliability).

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Audits, configures, and hardens workload-level security controls for Google Kubernetes Engine (GKE) applications and namespaces. Covers running security audits (`audit_cluster.sh`), enforcing Network Policies (default-deny and Dataplane V2 logging), isolating high-risk pods inside GKE Sandbox (`gVisor`), enforcing Pod Security Standards (`restricted` labeling) and pod securityContext, and mounting Secret Manager secrets via CSI (`SecretProviderClass`). Use when auditing workload security posture, isolating namespaces, applying pod security standards, or configuring network policies and secret volume mounts. Don't use for Workload Identity (use gke-workload-identity), cluster-wide control plane security, RBAC hardening, Binary Authorization, Shielded Nodes, or enabling platform-level GKE add-ons (use gke-platform-security instead).

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Diagnoses and prevents vbar_control_agent segfaults, out-of-memory (OOM) errors, and TPU device initialization failures on TPU v6e nodes in GKE caused by race conditions during TPU device resets or high-frequency metrics polling. Use when troubleshooting vbar_control_agent crashes, memory cgroup OOMs in serial console logs, tpu-device-plugin metrics checksum corruption errors, or custom TPU metrics collection conflicts on GKE TPU v6e nodes. Don't use for general non-TPU container OOM troubleshooting or standard GKE node lifecycle operations.

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This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For example, when Cloud SQL creates an open-source MySQL instance, the resulting resource is a Cloud SQL for MySQL instance that Google Cloud manages. Cloud SQL handles backups, high availability, and secure connectivity for relational database workloads.

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Configures best-practice, high-signal alerting policies for Cloud Run resources on Google Cloud (services, jobs, and worker pools) based on seasoned SRE practices. Use when analyzing, recommending, writing, or deploying Terraform PromQL alerting policies to monitor Cloud Run error rates (4xx/5xx), request latency, container instance saturation (warning/critical), container CPU/memory utilization and allocation, billable instance time, job execution status, and worker pool queue backlog. Don't use for GKE workloads (use gke-alert-configuration) or Compute Engine VMs.

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。

Form a committee of two high-reasoning agents to step back, do root cause analysis, and produce a plan. Use when stuck, looping, tunnel-visioning, or facing a hard planning problem.

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The 15-minute escalation-routing runbook for the Plain support queue — detecting SLA breaches against {{sla_targets}}, VIP accounts in {{vip_accounts}}, and high severity, routing each qualifying ticket to the right team, opening a linked issue in {{linear_team}} when engineering is needed, and posting the alert to {{escalation_channel}}. Never closes a ticket or promises a resolution.

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Create, manage, validate, preview, and export slide decks and presentations. Build 1920x1080 HTML slide decks (the default, higher-quality path) and export to PDF or PPTX — or produce/edit a fully native, editable PowerPoint (.pptx) file directly when the user needs a plain PowerPoint deliverable. Load this skill when you need to build a slide deck, presentation, or PowerPoint file, or export/edit/validate one.

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。

Trae-optimized PUA high-agency governance skill for npx skills installs. Use only for explicit PUA requests, repeated failures, user frustration, giving-up/passive behavior, or unverified completion. Do not trigger for normal first-attempt tasks.

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Pi-compatible PUA high-agency governance skill. Use for explicit PUA/PIP requests, repeated failures, passive/giving-up behavior, user frustration, or unverified completion. Pair with /pua-on extension command when persistent pressure is desired.

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。

Trae-compatible PUA high-agency governance skill. Use only for explicit PUA requests, repeated failures, user frustration, giving-up/passive behavior, or unverified completion. Do not trigger for normal first-attempt 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。

Trae-compatible English PUA/PIP high-agency governance skill. Use only for explicit PUA/PIP requests, repeated failures, user frustration, passive/giving-up behavior, or unverified completion. Not for normal first-attempt 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。

Augment a Wren project with business context that DB schema cannot carry — enum value meanings, units (USD vs cents, ms vs sec), NULL semantics, magic sentinels (-1 = unknown), soft-delete default filters, business synonyms, time-grain / TZ conventions, cross-system identifiers, currency rules, canonical-table preferences, AND named aggregation metrics (ARR, churn, DAU, WAU, NRR) proposed as cubes. Runs in one of two modes selected at session start: `grill` (one question at a time, user-driven) or `auto-pilot` (agent infers and applies, escalates only on conflicts and high-blast-radius additions like new cubes / views / relationships). Reads everything under <project>/raw/ (PDFs, glossaries, handbooks, code, data dictionaries) and optionally samples low-cardinality columns from the live DB (grill mode), compares against the current MDL / cubes / knowledge (rules + NL→SQL pairs), then fills gaps via the ten-category gap catalog and the cube proposal flow. Confirmed findings are written back to the right sink. Use when: user says 'enrich context', 'augment my project', 'grill me on this project', 'auto-fill my context', 'agent doesn't understand our docs / enum values / units / null meanings', 'business context is missing', 'what does status=A mean', 'is this amount in USD or cents', 'we keep getting wrong aggregations', 'add cubes for ARR / DAU / churn', 'we have a handbook / glossary / data dictionary the agent should know'; or after generating an MDL and noticing the agent lacks business semantics.

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。

Autonomously improve a generated paper via GPT-6-Astra xhigh review → implement fixes → recompile, for 2 rounds. Use when user says "改论文", "improve paper", "论文润色循环", "auto improve", or wants to iteratively polish a generated paper.

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。

Identifies high-quality leads for your product or service by analyzing your business, searching for target companies, and providing actionable contact strategies. Perfect for sales, business development, and marketing professionals.

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Analyzes job descriptions and generates tailored resumes that highlight relevant experience, skills, and achievements to maximize interview chances

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Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

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Assists in writing high-quality content by conducting research, adding citations, improving hooks, iterating on outlines, and providing real-time feedback on each section. Transforms your writing process from solo effort to collaborative partnership.

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Guide for creating high-quality MCP (Model Context Protocol) servers that enable LLMs to interact with external services through well-designed tools. Use when building MCP servers to integrate external APIs or services, whether in Python (FastMCP) or Node/TypeScript (MCP SDK).

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Polish a published qiankun GitHub Release's aggregated notes into a bilingual (English then Chinese) write-up with an agent. Use after a release goes out — turning the mechanically-aggregated, per-package release notes into a clean, human-readable, English + Chinese write-up (highlights, de-duped cross-package lines, clearer wording) via `gh release edit`. Triggers include "polish the release notes", "clean up the GitHub release", "improve the changelog for the latest release".

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Render the digest for one provider-research date from every report on disk, topped with authored highlight bullets; publishing is scripts/provider-watch/publish.py's job, run outside this skill

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Start up, tear down, and configure the local Kubernetes development environment for OpenShell. Uses k3d (Docker-backed k3s) + Skaffold + Helm. Covers cluster lifecycle, optional add-ons (Keycloak OIDC, Envoy Gateway), HA testing, and port mappings. Trigger keywords - local k8s, local cluster, k3d, skaffold, helm dev, start cluster, stop cluster, tear down cluster, delete cluster, create cluster, helm:k3s, helm:skaffold, local dev environment, dev cluster, k8s dev, envoy gateway local, keycloak local, high availability, HA.

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Reviews animation and motion code against a high craft bar derived from Emil Kowalski's design engineering philosophy. Default to flagging; approval is earned.

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Explain, draft, or validate Obsidian Flavored Markdown syntax: properties, wikilinks, embeds, callouts, tags, comments, highlights, block references, math, and Mermaid. Use when the user explicitly requests Obsidian note formatting or syntax help, not for general Markdown or broad vault operations.

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。