812 件 ・ 関連度順
概要と使いどころ
/cs:aims-audit <scope> — ISO/IEC 42001 AIMS internal-audit 6-question forcing interrogation. Use before certification stage 1, before annual internal audit cycles, or when onboarding a new AI system into an existing AIMS.
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 a Head of Ops, Knowledge Manager, or TPM-Internal needs to author, validate, or clean up company SOPs and internal runbooks (procurement intake, vendor offboarding, incident-comms cascade, employee onboarding) — including 5W2H completeness checks (Who-What-When-Where-Why-How-HowMuch), cross-link and orphan-page validation across a sprawling Notion/Confluence/Obsidian wiki, KB ingestion + hygiene reporting, and runbook step verification (named owner, expected duration, observable success signal, rollback path, escalation contact). Pairs Ishikawa's 5W2H method, Gawande's *The Checklist Manifesto*, ISO 9001, ITIL v4, and Google SRE Workbook runbook discipline with deterministic stdlib-only Python tools that score completeness, detect anti-patterns, and emit prioritized cleanup lists (e.g., "validate this runbook before it goes into rotation", "audit our Confluence wiki for stale and orphaned SOPs").
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。
Founder onboarding interview that captures company context across 7 dimensions. Invoke with /cs:setup for initial interview or /cs:update for quarterly refresh. Generates ~/.claude/company-context.md used by all C-suite advisor skills. Use when setting up the C-suite advisors for the first time, or when company context is missing or more than 90 days old — e.g. after a fundraise or pivot.
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 an end-to-end customer journey map with stages, touchpoints, emotions, pain points, and opportunities. Use when mapping the customer experience, identifying friction points, improving onboarding, or visualizing the user journey.
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。
First-time onboarding — asks where you are, then guides you to the right workflow.
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。
Onboarding doc for a new contributor or agent — project state, conventions, priorities relevant to the specified role.
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。
Set up, repair, or check a NemoClaw contributor checkout. Also handles requested development CLI exposure, runtime onboarding, and pinned-agent launch.
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 a developer's first steps on Google Cloud, covering account creation, billing setup, project management, and deploying a first resource. Use when a new developer wants to initialize their first Google Cloud project, configure billing, and verify deployment. Don't use for enterprise organization setup (use Google Cloud Setup guided flow for that instead). Don't use for complex multi-project architectures.
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。
Interactively discovers requirements and designs holistic, multi-product system architectures, solution blueprints, and deployment recommendations for complex workloads on Google Cloud. Use when designing end-to-end cloud solutions, selecting and integrating Google Cloud services, generating architecture diagrams, or conducting requirements discovery for new cloud workloads or migrations. Don't use for single-product tasks (use product-specific skills), initial onboarding or authentication (use google-cloud-recipe-*), Well-Architected Framework reviews or audits (use google-cloud-waf-*), or workloads covered by specialized solution 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。
Plans and configures multi-tenancy on GKE. Covers namespace isolation, RBAC planning for teams, resource quotas, LimitRanges, network isolation, and cost allocation. Use when designing GKE multi-tenancy, configuring GKE namespaces, setting up resource quotas, or isolating GKE teams. Don't use for single-tenant cluster configuration or general deployment instructions (use gke-basics or gke-app-onboarding 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。
Runs batch and HPC workloads on GKE, utilizing job queues and parallel processing. Use when running GKE batch jobs, configuring GKE HPC, or setting up GKE job queues. Don't use for standard web application deployments (use gke-app-onboarding 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。
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).
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 users through discovering their database requirements, recommends a Google Cloud database based on a recommendation matrix, and assists in database creation. Use when a user asks 'What database service should I use?', 'Help me pick a database', or when a user wants to create a new database on Google Cloud. Don't use for general Google Cloud maintenance, managing existing databases, or database migrations.
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 vendor-onboarding intake for {{request_label}}. Validates the W-9, banking form, and signed contract for every new vendor request against a fixed checklist, records every vendor's status in {{vendor_register}}, drafts a follow-up for anything missing or invalid, and posts the batch to {{review_channel}}. Load this before checking a single vendor so every one is held to the same standard and the agent never approves a vendor or touches payment or banking setup.
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。
Guide a new Kortix user through their first session: set expectations about what Kortix is, turn a vague ask into a strong first prompt, deliver one real result, then surface deeper capabilities (connectors, memory, triggers, subagents, marketplace) and plant a retention hook. Use when the user is new, asks 'what can you do / how does this work / where do I start', sends a vague or exploratory first message, or has no prior history in this project. Do NOT use when they arrive with a specific, well-formed task — just do it.
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。
Install and onboard a user into LifeOS — the Life Operating System (current state → ideal state via TELOS + the Algorithm). The agentic installer detects your OS + harness, wires hooks with permission, scaffolds your USER tree, pulls in sources you provide, and runs the TELOS / current→ideal interview that seeds your Pulse dashboard. USE WHEN install LifeOS, set up LifeOS, lifeos setup, lifeos-setup, lifeos interview, onboard me, run the interview, integrate LifeOS into my harness, update LifeOS, uninstall LifeOS, first-time setup, lifeos doctor, check my install, what capabilities are broken. NOT FOR building or cutting a LifeOS release (private release tooling), editing TELOS after onboarding (use Telos / Interview), or LifeOS system maintenance (use the private maintenance 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。
This skill should be used to explain or reason about the foundational concepts of context engineering: what context is, the anatomy of a context window, how attention mechanics work, the U-shaped attention curve, why context quality matters more than quantity, and the mental models needed to interpret every other context-engineering decision. Use this for conceptual explanation, onboarding, and background reading. Route operational work to the specialized skills: debugging attention failures goes to context-degradation, token-efficiency work goes to context-optimization, conversation summarization goes to context-compression, and project-shape decisions go to project-development.
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。
Connect a new user's accounts, learn their real work, choose a voice, and set up concrete help.
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。
Persistent local memory for OpenClaw agents. Use when users say: - "install memos" - "install MemOS" - "setup memory" - "add memory plugin" - "openclaw memory" - "memos onboarding" - "memory not working" - "configure memory" - "enable memory" - "upgrade MemOS" - "update memory plugin"
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。
Spin up a live local Omnigent server and exercise the Antigravity (Gemini) SDK harness end-to-end — build antigravity agents, run real turns, smoke-test, and bug-bash. Load when developing, testing, or debugging the antigravity harness (omnigent/inner/antigravity_executor.py, antigravity_harness.py, omnigent/onboarding/antigravity_auth.py) or its auth / model / tool-bridge behavior.
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。
Spin up a live local Omnigent server and exercise the GitHub Copilot SDK harness end-to-end — build copilot agents, run real turns, smoke-test, and bug-bash. Load when developing, testing, or debugging the copilot harness (omnigent/inner/copilot_executor.py, copilot_harness.py, omnigent/onboarding/copilot_auth.py) or its auth / model / tool-bridge behavior.
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。
Generate a comprehensive project summary from milestone artifacts for team onboarding and 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。
Guide existing codebase onboarding through mapping, doc ingest, and planning setup
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。