「exec」の検索結果

Queries and retrieves active security findings, external exposures, toxic combinations, vulnerabilities, threats, and sensitive data risks from Google Cloud Security Command Center. Use when retrieving details for a security finding by its name, validating finding scope (e.g., verifying findingClass is TOXIC_COMBINATION, VULNERABILITY, EXTERNAL_EXPOSURE, or THREAT), or fetching finding details for triage. Don't use to draft remediations, apply patches, or execute configurations.

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Creates Cloud Storage (Google Cloud Storage, or GCS) buckets. Analyzes the workload (sensitive data, media hosting, ingestion, web hosting, archiving, backup, logging, analytics, AI/ML, or general-purpose), validates project-level security settings, and designs a secure-by-default, cost-effective configuration (location, storage class, uniform bucket-level access, public access prevention, soft delete, lifecycle) before creating it. Use whenever a user wants to create, make, set up, provision, or spin up a bucket, or needs object storage for an app, service, pipeline, or dataset — even a "simple" or "default" bucket, or when bucket creation is one step in a larger workflow. Outputs or executes the creation via gcloud, the JSON/REST API, Terraform, or SDK client libraries (C++, Java, Python, Go). Don't use for anything other than creating new buckets — for uploads, downloads, access changes, or reconfiguring existing buckets, use google-cloud-storage-basics.

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Plans, executes, and validates Google Kubernetes Engine (GKE) cluster upgrades and maintenance operations for both Standard and Autopilot clusters. Produces upgrade plans, pre/post-upgrade checklists, maintenance runbooks with gcloud commands, release channel strategy, and troubleshooting guides. Handles node pool upgrade strategies (surge, blue-green), version compatibility, PDB management, and workload-specific concerns (stateful, GPU, operators). Use this skill whenever the user mentions GKE upgrades, Kubernetes version bumps, node pool maintenance, GKE patching, cluster version management, release channel selection, maintenance windows, surge upgrades, stuck upgrades, or any GKE lifecycle management task — even casual mentions like "we need to upgrade our clusters" or "plan our next GKE maintenance" or "our upgrade is stuck." Don't use for GKE cluster creation, application onboarding, general networking/routing setup, or security policy configurations (use gke-basics or relevant GKE skills instead).

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Guides the usage of Gemini Interactions API on Gemini Enterprise Agent Platform. Use when the user wants to use the stateful, server-managed Interactions API for multi-turn conversations, background execution, streaming, structured output, and function calling on the Agent Platform.

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Configures best-practice, high-signal alerting policies for Google Cloud Run resources (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.

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Manages custom Agent resources on Gemini Enterprise Agent Platform. Use when the user wants to programmatically create, configure, list, update, or delete stateful, server-managed Agent resources (including mounting files, skills, and tools) before executing conversations.

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Provides safety-critical validation, guardrails, and data reduction for gcloud CLI operations across Google Cloud Platform (GCP) services and infrastructure. Use when planning, generating, constructing, proposing, describing, or executing any gcloud CLI commands - including when answering questions about gcloud syntax, or formatting flags. Don't use when writing Google Cloud client library code or raw REST/gRPC API requests.

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Plans and executes GKE cluster creation, provisioning, and production readiness audits using pre-defined templates (Autopilot, Standard Regional, GPU/AI Inference, AI Hypercompute). Use when creating GKE clusters, provisioning GKE environments, selecting cluster modes, or auditing GKE clusters. Don't use for application onboarding or deployment configuration (use gke-app-onboarding instead).

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Connects to and performs inference with Google Cloud Agent Platform GenAI models, including First-Party Gemini models and Third-Party OpenMaaS models (Llama, DeepSeek, Qwen, etc.). Use when asked to perform inference, ask a model a question, run a test prompt, execute chat completions, or generate code for calling Gemini or OpenMaaS models, authenticate with GenAI SDK, OpenAI SDK, or legacy Agent Platform SDK, configure base URLs and global/regional endpoints, or troubleshoot 429 Resource Exhausted (DSQ), 400 User Validation, or 404 Not Found errors. Don't use for deploying models to endpoints or for running model evaluations.

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Analyzes Google Cloud BigQuery slot consumption, query costs, and execution bottlenecks using INFORMATION_SCHEMA. Use when diagnosing slow BigQuery queries, slot starvation, high on-demand query costs, unpartitioned table scans, or join performance issues. Don't use for generic BigQuery administration (use bigquery-basics), BigQuery ML (use bigquery-ai-ml), or DataFrame operations (use bigquery-bigframes).

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Write and harden reusable agent-loop specification documents for biomechanics, data science, and vailá coding work. Use when the user says `/preto-loop`, asks to write/create/forge/specify/document an agent loop, turn an iterative vailá task into an autonomous loop, make an overnight loop, or design a biomechanics, data-pipeline, markerless-tracking, testing, refactoring, or performance loop. Include external verification, scientific validity, GUI/CLI parity, reproducibility, memory, guardrails, and named terminal states. Do not use merely to repeat a fixed scheduled prompt, execute an existing loop, or create unrelated documents.

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Create a machine-readable phased JSON plan bundle from a spec or feature description. Produces a compact master manifest plus per-phase step files for resumable ck:cook execution.

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Implement a feature phase by phase from a phased JSON master or Markdown plan. Before each phase, confirm whether to create/run unit tests and whether to run ck:quality, unless explicit flags supply those choices. Supports token-budgeted execution, resumable state, and TDD handoff to ck:test.

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 machine-readable phased JSON plan bundle from a spec or feature description. Produces a compact master manifest plus per-phase step files for resumable ck:cook execution.

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。

Implement a feature phase by phase from a phased JSON master or Markdown plan. Before each phase, confirm whether to create/run unit tests and whether to run ck:quality, unless explicit flags supply those choices. Supports token-budgeted execution, resumable state, and TDD handoff to ck:test.

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Use this skill when writing, debugging, or optimizing SAQL queries in CRM Analytics — covering pipeline syntax, aggregation, windowing functions (rank, dense_rank, moving_average), cogroup joins, rollup subtotals, piggyback queries, and REST API execution. NOT for SOQL GROUP BY aggregates in Apex — use apex/apex-aggregate-queries. NOT for dashboard JSON steps and bindings — use admin/analytics-dashboard-json.

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Use this skill when designing the human-executable UAT test cases that prove a Salesforce feature works for a specific persona — the per-persona scripts with preconditions, data setup, permission setup, ordered steps, and pass/fail evidence that close out an RTM row. Trigger keywords: UAT test case salesforce, user acceptance test script salesforce, manual test salesforce feature, UAT script per persona, UAT precondition data setup, UAT permission set assignment for testing, negative path UAT case. NOT for high-level UAT planning, defect classification, regression strategy, or sign-off (use admin/uat-and-acceptance-criteria). NOT for the Given/When/Then technique used to write the AC the case is derived from (use admin/acceptance-criteria-given-when-then). NOT for Apex test method generation (use agents/test-class-generator). NOT for test data factory patterns (use templates/apex/tests/TestDataFactory.cls). NOT for performance or load testing.

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Build the executive KPI dashboard for Agentforce: adoption, deflection, latency, cost, quality — KPI definitions, data sources, CRM Analytics lenses, alert thresholds. NOT for the platform's own session tracing, Agent Analytics and health monitoring — use agentforce/agentforce-observability. NOT for scoring agent answer quality offline — use agentforce/agentforce-eval-harness.

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Scheduled Paths in record-triggered Flow: delayed execution, time-offset from field, batch size tuning, monitoring Paused Flow Interviews, async limits. NOT for picking between Scheduled Path, Wait and Scheduled Flow, or migrating time-based workflow rules — use flow/flow-time-based-patterns. NOT for a flow that runs on a recurring schedule — use flow/scheduled-flows.

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Automating post-sandbox-refresh cleanup via the `SandboxPostCopy` interface — the Apex class that runs ONCE after a sandbox refresh or clone completes, before users can log in. Used to mask emails, deactivate users, scrub integration endpoints, disable scheduled jobs, and reapply per-environment configuration the metadata copy doesn't carry. Covers the interface contract (`runApexClass` setting, `SandboxContext` parameter, single-execution semantics), the email-masking pattern that stops sandbox tests emailing production addresses, and the refresh runbook checklist. NOT for choosing sandbox type or refresh cadence — use admin/sandbox-strategy. NOT for re-seeding reference data after a refresh — use data/sandbox-refresh-data-strategies. Trigger keywords: SandboxPostCopy, runApexClass, SandboxContext, Test.testSandboxPostCopyScript, RunAsAutoProcUser, Automated Process user, CronTrigger, System.abortJob, sandbox email masking, post-refresh runbook.

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Use when a report or dashboard is slow, timing out, hitting row limits, or consuming excessive system resources on large-volume objects — covers selective filter strategy, custom report type optimization, async report execution via Analytics API, dashboard refresh scheduling, and grouping/aggregation tuning. Triggers: 'report times out', 'report is slow', 'dashboard not refreshing', 'report row limit hit', 'too many report results'. NOT for CRM Analytics / Tableau CRM performance (separate skill). NOT for sharing-model or visibility issues causing missing rows (use admin/sharing-and-visibility). NOT for building or designing reports from scratch (use admin/reports-and-dashboards-fundamentals).

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Use this skill to define and validate the requirements for a Salesforce Partner Relationship Management (PRM) implementation: deal registration flows, lead distribution models, partner tier hierarchies, MDF budget tracking, and co-marketing content entitlement. Trigger keywords: partner community requirements, PRM deal registration setup, channel partner portal requirements, lead distribution partner, partner tier management, MDF tracking, co-marketing entitlement. NOT for implementing the partner sharing model — use data/partner-data-access-patterns. NOT for building the portal in Experience Builder — use admin/experience-cloud-site-setup. More trigger keywords: partner portal design worksheet, partner tier licence and role depth, PartnerAccountId blank on opportunity, portal role Executive Manager User, sharing set does not support Lead, enable partner user greyed out, offboard a partner firm, PartnerMarketingBudget PartnerFundRequest PartnerFundClaim, ChannelProgramLevel partner tier, deal registration acceptance step.

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Use when executing admin-level cleanup in a Salesforce org: deleting unused fields, removing inactive Flow versions, deactivating legacy automation, running Salesforce Optimizer or Org Check, and performing destructive metadata deploys. Triggers: 'clean up unused fields', 'delete inactive flows', 'run Optimizer', 'org has too many custom fields', 'remove old workflow rules', 'Flow version limit'. NOT for assessing or reporting on technical debt (use architect/technical-debt-assessment). NOT for code-level refactoring or Apex cleanup (use apex/ skills).

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Use when setting up or auditing a dedicated Salesforce integration user — Salesforce Integration user license, API-only profile, permission set layering, MFA waiver, and login monitoring. NOT for creating human users, roles, or login hours — use admin/user-management. NOT for login IP ranges, session lifetime, or OAuth client-credential hardening — use security/api-only-user-hardening. Trigger keywords: service account, API-only user, run-as user, client credentials execution user, LoginHistory, REQUEST_LIMIT_EXCEEDED, integration login failure.

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。