3,189 件 ・ 関連度順
概要と使いどころ
Builds real-time incident response dashboards in Splunk, Elastic, or Grafana to provide SOC analysts and leadership with situational awareness during active incidents, tracking affected systems, containment status, IOC spread, and response timeline. Use when IR teams need unified visibility during incident coordination and post-incident reporting.
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。
Executive leadership guidance for strategic decision-making, organizational development, and stakeholder management. Includes strategy analyzer, financial scenario modeling, board governance frameworks, and investor relations playbooks. Use when planning strategy, preparing board presentations, managing investors, developing organizational culture, making executive decisions, or when user mentions CEO, strategic planning, board meetings, investor updates, organizational leadership, or executive strategy.
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 the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.
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。
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit
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。
Add a monitoring dashboard to NanoClaw. Installs @nanoco/nanoclaw-dashboard and a pusher that sends periodic JSON snapshots.
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。
Board meeting preparation for the adversarial scenario, not the friendly one. Forces numbers-cold mastery, anticipates hard questions, builds a narrative that acknowledges weakness without losing the room. Use when preparing for a board meeting, an investor update, fundraising presentation, or any high-stakes adversarial review where every number must live in your head not just on a slide.
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 the user wants to create or optimize an email sequence, drip campaign, automated email flow, or lifecycle email program. Also use when the user mentions "email sequence," "drip campaign," "nurture sequence," "onboarding emails," "welcome sequence," "re-engagement emails," "email automation," or "lifecycle emails." For in-app onboarding, see onboarding-cro.
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。
/cs:boardroom <brief> — 6-phase multi-role deliberation across the C-suite with Phase 2 isolation, critic pre-screen, and synthesis. Outputs a board memo. Use when a decision spans multiple executive domains — e.g. a pricing change touching finance, positioning, and product, or a raise-vs-cut runway call.
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 building a quarterly bookings forecast, ARR projection, pipeline forecast, NRR projection, or commit/best-case/pipe-only board number — especially when the CRO needs to walk the board through funnel math + cohort ARR + per-stage conversion assumptions without the theatre of a single undefended number. Decomposes pipeline into commit, best-case, and pipe-only tiers; projects cohort-level NRR/GRR to surface leaky cohorts before they show up in the consolidated number; scores per-stage funnel confidence so soft-floor stages get treated differently from high-confidence ones. Every output explicitly names the conversion rate used, the data window, and the weighting choice. For Head of Commercial, RevOps, VP Sales, and CRO at quarterly forecast or board prep. NOT financial close (see finance/financial-analysis). NOT strategic CRO hiring/territory (see c-level-advisor/cro-advisor). NOT pricing (see sibling pricing-strategist).
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。
Assembles comprehensive board and investor update decks by pulling perspectives from all C-suite roles. Use when preparing board meetings, investor updates, quarterly business reviews, or fundraising narratives. Covers structure, narrative framework, bad news delivery, and common mistakes.
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。
Two-layer memory architecture for board meeting decisions. Manages raw transcripts (Layer 1) and approved decisions (Layer 2). Use when logging decisions after a board meeting, reviewing past decisions with /cs:decisions, or checking overdue action items with /cs:review. Invoked automatically by the board-meeting skill after Phase 5 founder approval.
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。
Define and design a product metrics dashboard with key metrics, data sources, visualization types, and alert thresholds. Use when creating a metrics dashboard, defining KPIs, setting up product analytics, or building a data monitoring plan.
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。
Query and manage Grafana dashboards and Prometheus metrics for Happy infrastructure. Covers grafanactl CLI usage, direct Prometheus queries through Grafana proxy, and dashboard-as-code workflows. Use when user asks about metrics, dashboards, monitoring, Grafana, Prometheus, or wants to add/modify panels.
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 GKE application onboarding, covering containerization, deployment manifests, and migration. Use when onboarding or deploying an application to GKE for the first time, or containerizing an app for GKE. Don't use for general GKE cluster administration or upgrades (use gke-basics or gke-upgrades 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。
Generates Cloud Monitoring Server-Driven UI (SDUI) Widget and XyChart Protocol Buffer textprotos on Google Cloud from resolved PromQL or ListTimeSeries queries. Use when: - Generating valid google.monitoring.dashboard.v1.Widget textprotos, containing PrometheusQuery or TimeSeriesFilter datasets, for use with the Cloud Monitoring Dashboards API, gcloud CLI, or declarative dashboard definitions. - Synthesizing Server-Driven UI (SDUI) widget titles, axis labels, and plot types for Prometheus or ListTimeSeries queries. Don't use for: - Metric discovery or PromQL query generation. For those tasks, use the cloud-monitoring-metric-selection or cloud-monitoring-promql-query skills.
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。
New-hire onboarding runbook for {{projectName}}. Detects new-hire records via the {{new_hire_group}} group in Google Workspace, then works one scoped case per hire — preparing the Workspace account and group memberships, adding them to the right Slack channels, and filing a first-week checklist in the {{onboarding_project}} Linear project — holding account creation and group membership for a human approval gate and posting the result to {{notify_channel}}.
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 and post the weekly ENG/PRODUCT shipping brief to Slack — a compact summary of what shipped, a ranked merged-PR count per person with week-on-week delta and shipping streaks, and an async standup thread prompt. Load this when you are the `leaderboard` agent (the `weekly-leaderboard` cron), or when someone asks for a weekly contributor/shipping summary.
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。
Read, create, and edit tldraw .tldr canvas files deterministically — sketch hand-drawn-register diagrams (boxes, arrows, sticky notes, frames, text) directly into a canvas file the user opens in any tldraw surface, and read a rough canvas back as structured data to organize it. USE WHEN tldraw, .tldr file, whiteboard, canvas, sketch a diagram, hand-drawn diagram, draw this on a canvas, put this on the whiteboard, structure my canvas, organize my whiteboard, read my canvas, cluster my sticky notes. NOT FOR polished static images, infographics, or mermaid diagrams (use Art), web UI design (use Webdesign), programmatic video (use Remotion).
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。
Creates and edits CARLA Leaderboard route files — placing waypoints and scenario trigger points interactively from the spectator camera (route_creator, scenario_creator), visualising an existing route in the simulator (route_displayer), summarising it as a table (route_summarizer), capturing the current weather in route format (weather_creator), sorting scenarios by route position (scenario_orderer) and converting 1.0-format routes to 2.x (route_bridge). Use when the user asks to "make a new route", "add a scenario to a route", "visualise/debug a route", "see what's in this route file", or "convert old leaderboard routes".
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。
Runs a route through ScenarioRunner's RouteScenario mode (--route / --route-id) with an autonomous agent driving the ego — the same mechanism the CARLA Leaderboard uses, and the only way to reach the ~34 route-only scenario classes (Accident, ParkedObstacle, HazardAtSideLane, InvadingTurn, HardBreakRoute, YieldToEmergencyVehicle, junction and actor-flow scenarios). Inspects route files, lists route ids and their scenarios, and runs one or all of them. Use when the user asks to "run a route", "drive a route with my agent", "run leaderboard scenarios without the leaderboard", or names a route-only scenario type.
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。
Visualize training metrics, debug models with histograms, compare experiments, visualize model graphs, and profile performance with TensorBoard - Google's ML visualization toolkit
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。
Verify the Omnigent CLI's setup/onboarding flow, terminal UI/UX, and critical user journeys in a completely isolated, reproducible loop. Drives the real `omnigent` binary through a PTY (pexpect) inside a throwaway OMNIGENT_CONFIG_HOME / OMNIGENT_DATA_DIR sandbox that never touches the user's real ~/.omnigent, captures ANSI-stripped frames for UX inspection, and proves a change is verifiable via a before→fix→after baseline diff. Load when developing or reviewing a CLI setup/onboarding/REPL/picker change (omnigent/cli.py, omnigent/onboarding/*, omnigent/repl/*, scripts/install_oss.sh), reproducing a cold-start/first-run UX bug, or confirming a fix actually lands. Several agents can run it concurrently on separate worktrees.
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。
Draft a unanimous written consent of the board or a committee in house format, with precedent search from the consents repository. Handles multi-resolution consents, director conflict flags, state-law notice requirements, and signatory tracking, with a built-in scope warning for major one-off actions. Use when user says "written consent", "unanimous consent", "board consent", "consent in lieu", "UWC", or describes an action needing board approval without a meeting.
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。