「lab」の検索結果

Set up your bio-research environment and explore available tools. Use when first getting oriented with the plugin, checking which literature, drug-discovery, or visualization MCP servers are connected, or surveying available analysis skills before starting a new project.

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。

Maintain the supported LLM model list: add a new model, or run routine maintenance to verify availability and discover new models worth adding. Use when the user asks to add/support a model, update the model list, or check model availability.

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。

Re-review a GitLab merge request after new commits and reconcile the previous review

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。

Review a GitLab merge request for a Factory work item using brokered source-control tools

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。

Triage GitHub issues by applying type, effort, priority, and area labels. Runs in an isolated context to avoid polluting the main conversation with issue details. Delegates to a specialized triage agent with label validation hooks.

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。

Generates guidance for reliability, resilience, availability, redundancy, fault-tolerance, and disaster recovery (DR) for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use when the user asks to evaluate, design, or improve the reliability, resilience, availability, or disaster recovery capabilities of Google Cloud workloads.

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Diagnoses GKE HorizontalPodAutoscaler (HPA) failures — metrics showing as <unknown>, FailedGetResourceMetric / FailedGetScale / FailedComputeMetricsReplicas events, missing Pod resource requests, custom/external metrics-pipeline breakage (FailedGetExternalMetric / FailedGetCustomMetric, unavailable metrics adapter, control-plane firewall blocking the adapter), HPA that won't scale up or down (tolerance / stabilization window / unavailable rate metrics), scale-to/from-zero problems, and slow HPA reaction on large clusters. Use when an HPA isn't scaling a workload as expected or reports metric errors. Don't use for configuring or authoring new HPA/VPA objects or scaling best practices (see the gke-workload-scaling skill), or for Cluster Autoscaler / node-pool sizing.

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。

The pull request loop for this repo: branch → commit → verify in your own box (local tests + local stack) → PR into main → demo video recorded with agent-browser on the local stack → `gh --attach` → self-merge → verify on dev. A PR into main runs no CI unless a person adds the `test` or `preview` label (one run each). Load when opening, updating, or finishing a pull request; when writing a PR body; when asking what CI runs where; when adding or explaining PR labels or the per-PR preview environment; or when attaching an image or video to a PR, issue, or comment.

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。

The shared-inbox triage runbook — how to read a new inbound email, label it, look up {{help_doc}} for a standard answer, draft a reply in Gmail or file a ticket in {{linear_team}}, and when to leave a thread label-only for a human.

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。

Triage an incoming verdaccio/verdaccio GitHub issue against the codebase, the affected release line, and related issues, then choose the labels from the repository's existing taxonomy. Use whenever the user asks to triage, classify, assess, reproduce, prioritize, or label an issue, especially when an issue URL or number is supplied.

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。

Complete Foundry PoC writing guide + all cheatcodes + DeFiHackLabs reproduction patterns. Use this when building a proof of concept exploit, setting up a fork test, using Foundry cheatcodes, or reproducing a known DeFi hack for learning.

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。

When you need a browser, read this Skill by default. Use it to open and operate websites, fill forms, click buttons, take screenshots, extract page data, sign in, and perform other browser automation tasks, as well as web app testing, dogfooding, QA, bug investigation, and app-quality review. ego-browser (ego-lite) is a Chromium browser designed for both human users and AI Agents. Agents can use the user's logged-in websites and personal context to complete tasks and collaborate smoothly with the user through the browser interface. Therefore, prefer ego-browser over built-in browsers or other web tools.

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。

Automate API Labz tasks via Rube MCP (Composio). Always search tools first for current schemas.

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。

Loads, reloads, and reshapes the map on a running CARLA server via the Python API — get_available_maps, load_world and reload_world (with or without resetting world settings), generate a world from an OpenDRIVE .xodr, and load/unload map layers. Use when the user asks to "load a map", "change the town", "reload the world", "list available maps", "load an xodr/opendrive map", or "load/unload map layers", and when settings (sync mode, fixed delta) must survive the switch.

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。

Track ML experiments with automatic logging, visualize training in real-time, optimize hyperparameters with sweeps, and manage model registry with W&B - collaborative MLOps platform

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。

Reserved and on-demand GPU cloud instances for ML training and inference. Use when you need dedicated GPU instances with simple SSH access, persistent filesystems, or high-performance multi-node clusters for large-scale training.

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。

Scalable data processing for ML workloads. Streaming execution across CPU/GPU, supports Parquet/CSV/JSON/images. Integrates with Ray Train, PyTorch, TensorFlow. Scales from single machine to 100s of nodes. Use for batch inference, data preprocessing, multi-modal data loading, or distributed ETL pipelines.

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 designing new high-level system architecture, reviewing existing designs, or making architectural decisions. Invoke to create architecture diagrams, write Architecture Decision Records (ADRs), evaluate technology trade-offs, design component interactions, and plan for scalability. Use for system design, architecture review, microservices structuring, ADR authoring, scalability planning, and infrastructure pattern selection — distinct from code-level design patterns or database-only design 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。

Scan open issues and discussions. Dedupe, prioritize, and propose labels. Updates issue-triage-state.md. L1 propose-only — never auto-label or close.

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。

Build the visual layer of a holaOS dashboard app — TanStack Start + @holaboss/ui + workspace tokens. Use when an app has SDK primitives wired (via app-builder-sdk) AND needs a `src/client/` UI surface. NOT for marketing pages, NOT for snapshot HTML reports.

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。

Build a new holaOS app using @holaboss/app-builder-sdk (5 backend primitives + optional shadcn dashboard UI). The canonical path for vibe-coded apps — integration modules AND dashboard apps both live here.

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。

Technical SEO audit with GEO-specific checks — crawlability, indexability, security, performance, SSR, and AI crawler access

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。

Trigger: contributing to Gentleman-Programming/gentle-ai as an external collaborator. Strict issue-first workflow, honest PR bodies, contributor-vs-maintainer scope, chained-PR strategy, verification protocol, docstring coverage. Load whenever the active repo is Gentleman-Programming/gentle-ai and any part of the contribution flow is in scope: opening an issue, drafting or editing a PR body, splitting a change into chained/stacked PRs, or auditing a PR before requesting review.

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。

Authoring guide for the Native markup (.native) view tier of native-rendered Native SDK apps. TypeScript cores are the default and use this skill together with ts-core; Zig cores are an explicit alternative and this guide labels their lower-level UiApp recipes. Use when building or modifying native UI (widgets, layout, bindings, messages), writing .native files, wiring views to Model/Msg/update, testing markup views, or verifying a native app through the automation harness.

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。