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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.

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。

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.

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。

Monitors, troubleshoots, and manages GKE TPU Dynamic Slices custom resources. Use when checking TPU slice lifecycle states, troubleshooting slice provisioning failures, validating single-slice or multi-slice (JobSet) workload manifests, or safely patching stuck finalizers and disabling the slice controller. Don't use for generic GKE cluster node pool creation or standard non-TPU workload management (use gke-basics or gke-cluster-creation instead).

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。

Guides developers through managing (adding, removing, and clearing) audience members for Google products using the Data Manager API and its associated client libraries. Use this skill when the user wants to upload audience members, remove specific users, or clear/replace an entire audience for Customer Match, mobile device ID audiences, or any other audience use case supported by the Data Manager API. Don't use for uploading events or conversions (use the data-manager-api-event-ingestion skill).

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Deploy open models or custom weights from Model Garden to Agent Platform endpoints, check the status of an in-progress deployment operation, or clean up resources by undeploying models and deleting endpoints. Use when asked to actively deploy a model, list the Model Garden CATALOG of available models, check if a specific model is deployable (`gcloud ai model-garden models list-deployment-config`), query deployment cost, troubleshoot deployment errors (like quota limits), or undeploy/clean up endpoints. Also use when copying and deploying a 1P Tuned Model. Don't use for pure listing/discovery questions of the form "is X deployed?", "list my endpoints", or "which regions have models running?" — for those use `agent-platform-endpoint-management`. Don't use for running model evaluations (use `agent-platform-eval-flywheel` skill).

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。

Manages Google Analytics reporting data, enables the Analytics Data API via the Cloud CLI, and creates reports using the Google Analytics Data API (v1beta). Use when you need to interact with Google Analytics properties, run customized analytics reports, query metrics (like activeUsers, screenPageViews) and dimensions (like city, date), check metrics and dimensions compatibility, or verify API enablement. Don't use for Google Analytics Admin API operations (e.g., creating properties, managing users) or for front-end tracking installation.

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。

Manages Google Analytics account and property settings, enables the Analytics Admin API via the Cloud CLI, lists accounts and properties, and manages data streams, custom dimensions, conversion events, and integrations. Use when you need to programmatically configure Google Analytics accounts, provision properties, manage data retention, configure Measurement Protocol secrets, or manage Firebase and Google Ads links.

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。

Guides developers through Google Ads API quickstart: credential setup, choosing from 6 client libraries/REST, configuring environments, and running a "retrieve campaigns" script. Troubleshoots common setup errors: USER_PERMISSION_DENIED, login_customer_id issues, and DEVELOPER_TOKEN_NOT_APPROVED. Use this skill when: - The user asks how to get started with the Google Ads API. - The user needs to set up Google Ads credentials or developer tokens. - The user wants to write a quickstart/example script for Google Ads. - The user encounters errors like USER_PERMISSION_DENIED or DEVELOPER_TOKEN_NOT_APPROVED.

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Forces the laziest solution that actually works, simplest, shortest, most minimal. Channels a senior dev who has seen everything: question whether the task needs to exist at all (YAGNI), reach for the standard library before custom code, native platform features before dependencies, one line before fifty. Supports intensity levels: lite, full (default), ultra. Use on ANY coding task: writing, adding, refactoring, fixing, reviewing, or designing code, and choosing libraries or dependencies. Also use whenever the user says "ponytail", "be lazy", "lazy mode", "simplest solution", "minimal solution", "yagni", "do less", or "shortest path", or complains about over-engineering, bloat, boilerplate, or unnecessary dependencies. Do NOT use for non-coding requests (general knowledge, prose, translation, summaries, recipes).

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。

Fresh-session security questionnaire response for {{projectName}}. Parses a new inbound questionnaire from {{questionnaire_label}} in Gmail, matches each question to our vetted knowledge base of approved answers and policies, drafts responses in the vendor's own format (SIG, CAIQ, or a custom spreadsheet), flags anything it can't answer confidently, and posts the completed draft to {{security_channel}} — holding it for security to review before it goes back to the prospect.

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。

Aging buckets, reminder tiers, and dunning cadence for chasing overdue invoices. Load this before deciding what reminder an invoice gets so you message consistently and don't over-contact a customer.

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。

Daily runbook for tracking new customer accounts against onboarding milestones in Postgres and HubSpot for {{projectName}}. Covers the milestone framework, stall and overdue detection, nudge drafting, the owning-CSM alert, and the human approval gate before anything sends or changes account state.

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。

Canonical reference for Kortix projects, Apps (sites, servers, backends with volumes) and internal business apps, the CLI, sessions, sandboxes, change requests, triggers, connectors, secrets, system skills, and the two session harnesses, pi and OpenCode. Covers `kortix.yaml` versions 1 and 2, App deployments, harness configuration (`harnesses/pi/`, `harnesses/opencode/`), session identity, credential boundaries, and the complete pi and OpenCode references. Load when the user asks how Kortix works, what Kortix can do, how to deploy an App, how an agent discovers platform instructions, how to customize or configure this project's agents (create or fix an agent, subagent, skill, tool, plugin, extension, pi package, command, MCP server, model or permission rule; edit `opencode.jsonc`), how to edit `kortix.yaml`, how to use the `kortix` CLI, how to land work through a change request, or how to schedule and automate work.

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。

Intakes external content, classifies chunks against LifeOS taxonomy, commits with provenance. Sources: .md/.txt, stdin, LifeOS dirs, CLAUDE.md/Cursor/OpenAI Custom Instructions, Obsidian/Notion/Apple Notes exports. MigrateScan classifies → routing table. MigrateApprove with --approve-all/--approve-target/--review/--dry-run. Confidence ≥70% auto, 40-70% confirm, <40% walk-through. USE WHEN /migrate, migrate content, import from other LifeOS, bring in old notes, import Cursor rules, import CLAUDE.md, bulk import, Obsidian/Notion/Apple Notes import. NOT FOR single-file edits, conversational interviews, identity edits.

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。

Content-adaptive wisdom extraction that reads content first, detects which wisdom domains are present, and builds custom sections around them, with five depth levels and mandatory contrarian takes; pulls YouTube via fabric and articles via WebFetch. USE WHEN extract wisdom, analyze video, analyze podcast, extract insights, key takeaways, summarize interview, distill content. NOT FOR static Fabric extract_wisdom pattern (use Fabric).

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。

Multi-agent collaborative debate producing visible round-by-round transcripts with real intellectual friction — members are topic-briefed custom agents, run as a 3-round DEBATE or a 1-round QUICK check, to find the best path. USE WHEN council, debate, multiple perspectives, weigh options, deliberate, get different views, what would experts say, pros and cons. NOT FOR pure adversarial attack (use RedTeam).

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 registering iii functions, binding triggers, selecting sync/void/enqueue invocation, creating workers, inspecting the live worker registry, installing registry workers, authoring custom triggers, moving channel data, or adapting external HTTP functions across TypeScript, Python, and Rust.

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。

Code generation utilities for json-render. Use when generating code from UI specs, building custom code exporters, traversing specs, or serializing props for @json-render/codegen.

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。

Wren CLI for AI agents — a semantic SQL layer over 22+ databases (Postgres, MySQL, BigQuery, Snowflake, Spark, …). The actual workflow guides live inside the `wren` CLI itself; this is just a discovery stub. Use whenever the user asks a data question (how many, show me, top N, compare, trend, breakdown, metric, revenue, customers, orders), wants to install / set up Wren Engine, connect a new database, connect SaaS data via dlt (HubSpot, Stripe, Salesforce, GitHub, Slack), generate or regenerate an MDL project from a database schema, enrich a project with business context (enum meanings, units, cubes like ARR / DAU / churn), or turn a project's context layer into a shareable GenBI web app / dashboard and deploy it to Vercel or Cloudflare. Triggers: 'install wren', 'set up wren engine', 'connect database to wren', 'connect SaaS to wren', 'load hubspot / stripe / salesforce data', 'generate mdl', 'scaffold wren project', 'enrich wren context', 'augment my project', 'add cubes', 'build a dashboard', 'make a shareable analytics app', 'deploy my context layer as a web app', 'genbi app', 'wren onboarding', 'wren usage', 'wren generate mdl', 'wren dlt connector', 'wren enrich context', 'wren genbi'.

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。

Wren Engine CLI workflow guide for AI agents. Answer data questions end-to-end using the wren CLI: gather schema context, recall past queries, write SQL through the MDL semantic layer, execute, and learn from confirmed results. Use when: user asks a data question, requests a report or analysis, asks about metrics, revenue, customers, orders, trends, or any business data; user says 'how many', 'show me', 'what is the', 'top N', 'compare', 'trend', 'growth', 'breakdown'; user wants to explore, analyze, filter, aggregate, or summarize data from a database; agent needs to query data, connect a data source, handle errors, or manage MDL changes via the wren CLI.

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。

How to build desktop applications with GPUI Kit, the Rust framework published as the gpui-kit crate (GPUI plus gpui_kit::component, gpui_kit::base, gpui_kit::assets). Use when setting up a gpui-kit app, choosing or using a component (Button, Input, Select, Dialog, Sheet, Tabs, Sidebar, List, DataTable, Tree, Chart, etc.), handling component state, theming, or window overlays, and for GPUI mechanics: actions and keybindings, async tasks, contexts, custom elements, entities, events, focus, global state, layout and styling, ElementId, and tests including UI integration testing. Holds the normative Coding Guides: read them before any architecture, state-ownership, public API, naming, or testing decision. Pairs with the gpui-kit-design-guides skill for the Design Guides.

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Use when working with TradingView's lightweight-charts — creating charts, adding series (Line/Area/Bar/Candlestick/Histogram), configuring time and price scales, streaming realtime or historical data, panes, markers, per-bar/per-point colors, tooltips, coordinate conversion, custom plugins or primitives, non-financial horizontal scales, SSR/browser loading, or React/Vue/Web Components wrappers. Covers v5 API conventions and the common time, scale, marker, plugin, and wrapper foot-guns.

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。

External research synthesis from Trail of Bits, SlowMist, ConsenSys, Immunefi, and Cyfrin. Use this for advanced audit methodology, Echidna/Medusa fuzzing setup, Slither custom detector writing, attack pattern deep dives, or the 4-phase learning roadmap.

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。

KubeSphere multi-tenant management Skill. Use when user requests to create users, workspaces, projects, or assign roles/permissions. Supports user lifecycle management, workspace configuration, project creation, role binding. Do not perform any delete operations, do not create custom roles.

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。