Universal seed data generator: MIGRATE from ORM schemas or GENERATE from entity definitions to any target format
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概要と使いどころ
Universal seed data generator: MIGRATE from ORM schemas or GENERATE from entity definitions to any target format
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 Docker and docker-compose configuration for multi-container development
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Discovers custom modules (>100 LOC), analyzes purpose, searches OSS alternatives via MCP Research, evaluates quality (stars, license, CVE), generates migration plan.
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Generates sustainability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify environmental impact requirements, and provide actionable recommendations to build, deploy, and manage the workload sustainably in Google Cloud.
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 security-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify security requirements, and provide actionable recommendations for IAM, network security, data protection, and operational security.
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Generates GitHub Actions CI workflow configuration
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Generates operations-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Operational Excellence pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify operational requirements, and provide actionable recommendations for deployment, monitoring, and incident management.
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Generates reliability-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Google Cloud Well-Architected Framework. Use this skill to evaluate a workload, identify reliability requirements, and provide actionable recommendations for build, deploy, and manage the workload reliably in Google Cloud.
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This file generates or explains Cloud SQL resources. Use this file when the user asks to create a Cloud SQL instance or database for MySQL, PostgreSQL, or SQL Server. Cloud SQL manages third-party MySQL, PostgreSQL, and SQL Server instances as resources in Cloud SQL. For example, when Cloud SQL creates an open-source MySQL instance, the resulting resource is a Cloud SQL for MySQL instance that Google Cloud manages. Cloud SQL handles backups, high availability, and secure connectivity for relational database workloads.
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 performance-focused guidance for Google Cloud workloads based on the design principles and recommendations in the Performance Optimization pillar of the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify performance requirements, and provide actionable recommendations for resource allocation, modular design, and elasticity.
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 cost optimization guidance for Google Cloud workloads based on the Google Cloud Well-Architected Framework (WAF). Use this skill to evaluate a workload, identify cost requirements and constraints, and provide actionable recommendations for build, deploy, and manage the workload cost-efficiently in Google Cloud.
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Generate a crisis communication plan with holding statements, stakeholder messaging, media responses, and internal comms templates.
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Generate a production-ready operations runbook for deploying AI agents. Covers pre-deployment checklists, shadow mode → supervised → autonomous rollout stages, monitoring dashboards, rollback proce...
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Generate production-ready API documentation from endpoint descriptions. Outputs OpenAPI 3.0, markdown reference docs, and SDK quickstart guides.
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Generate investor-ready board decks and reporting packages. Covers monthly board updates, quarterly deep dives, and annual reviews with the metrics that actually matter.
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Build, manage, and scale a channel partner program that generates indirect revenue without adding headcount.
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Generate complete board meeting packages — agenda, financial summary, KPI dashboard, risk register, and action item tracker.
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Applies rigorous adversarial analysis to generate, critique, fix, and consolidate solutions for any problem (technical or non-technical). Use when facing complex problems requiring thorough analysis, multiple solution approaches, and validation of proposed fixes before implementation.
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Track AI visibility — measure whether a brand is mentioned and cited by AI assistants (Gemini, ChatGPT, Perplexity) for target prompts. Runs scans, tracks mention/citation rates over time, detects trends, and identifies opportunities. Uses Gemini API free tier (with grounding) as primary method, web search as fallback. Use when a user wants to: check if AI models mention their brand, track AI citation changes over time, measure AEO content effectiveness, monitor competitor AI visibility, or audit their brand's presence in AI-generated answers. Pairs with aeo-prompt-research-free (identifies prompts) and aeo-content-free (creates/refreshes content). This skill closes the loop by measuring results.
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Full-stack affiliate marketing automation for OpenClaw agents. Generate, track, and optimize affiliate links with FTC-compliant disclosures and multi-network support.
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You are an AP process optimizer. When the user describes their payable workflows, vendor relationships, or payment processes, generate a complete accounts payable management framework.
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Generate Architecture Decision Records with AI. Use when documenting technical decisions.
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Discover which AI prompts and topics matter for a brand's Answer Engine Optimization (AEO) using only free tools. Crawls a website, analyzes the brand's positioning, generates prioritized prompts people ask AI assistants, and audits existing content coverage — all without paid APIs. Use when a user wants to: find what questions people ask AI about their industry, discover AEO opportunities, research prompts for content creation, audit a site's AI visibility, or build an AEO content strategy. No API keys required — uses web_fetch, web_search (free tier), and LLM reasoning only.
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Implements the Active Learning Protocol (R3). Allows the agent to programmatically internalize lessons into MEMORY.md and generate structured "ask for help" requests.
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。