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Google CloudKnown publisherGoogleCloudPlatform/data-agent-kit-plugin/skills/cloud-databases-onboarding/SKILL.md

cloud-databases-onboarding

Skill240 starsChanged 5 months agoApache-2.0View on GitHub

Guides users through discovering their database requirements, recommends a Google Cloud database product or migration destination 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', asks which Google Cloud database to migrate or onboard a workload to, or wants to create a new database on Google Cloud. Don't use for general Google Cloud maintenance, managing existing databases, or troubleshooting active Database Migration Service (DMS) jobs.

3 other projects use a version of this, 3 of them edited.

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Most recently taken up by

The file

We split this skill into the rules it gives an agent

7 rules. 2 are common, 0 are distinctive, and 5 are very specific to this project.

  • 2

    Common

    Most of the 3 edited versions we read keep these.

  • 0

    Distinctive

    This author's own choices. Worth a look.

  • 5

    Very specific

    Tied to their project's names, files or tools. Probably skip.

  • Common
  • Distinctive
  • Very specific
  1. Common:

    Reading / Progressive Disclosure: When interacting with a user during a conversation, load reference files progressively.

    line 27
  2. Very specific:

    When a user asks "What database should I use?" or requires guidance on Google Cloud database selection without providing sufficient source …

    line 41
  3. Very specific:

    Load Discovery Instructions (JiT): Read the complete contents of references/onboarding_prompts.md using view_file.

    line 45
  4. Very specific:

    Consult Matrix & Formulate Recommendation (JiT): Follow the Phase 2 instructions in references/onboarding_prompts.md (or, when the user's …

    line 59
  5. Common:

    When the user accepts the recommendation and requests to provision or modify cloud resources, you must initiate the Implementation & …

    line 75
  6. Very specific:

    Load Provisioning Instructions (JiT): Read the Phase 3 section of references/onboarding_prompts.md (if not already loaded) using view_file.

    line 78
  7. Very specific:

    Execute Plan-Validate-Execute Workflow: Follow the detailed Phase 3 instructions in references/onboarding_prompts.md to analyze the …

    line 81

“Common” is measured: kept by at least 6 in 10 of the 3 edited versions of this file we could read. “Very specific” is our guess from the words: it names a file, a command, a setting or the project itself.

Keep what fits and drop the rest. Your version, ready for your agents.
Files
SKILL.md

Google Cloud Database Onboarding Skill

This skill provides domain instructions, decision matrices, and Infrastructure-as-Code workflows to guide users through discovering their exact database requirements, selecting an optimal Google Cloud database service, and drafting starter resource provisioning code for user review.

Progressive Disclosure

  • Reading / Progressive Disclosure: When interacting with a user during a conversation, load reference files progressively. Follow the Just-in-Time (JiT) loading instructions outlined in the phases below.

Workflow & Just-in-Time (JiT) Instructions

This workflow operates in three distinct sequential phases. Evaluate the active conversation history to determine the current phase and follow the corresponding instructions:

Phase 1: Requirement Discovery & Information Gathering

When a user asks "What database should I use?" or requires guidance on Google Cloud database selection without providing sufficient source or workload context, you must initiate the Discovery phase.

  1. Load Discovery Instructions (JiT): Read the complete contents of references/onboarding_prompts.md using view_file.
  2. Execute Discovery: Optionally check get_active_gcp_connection and get_active_editor_context (when available in the IDE) to prefill context, and follow the detailed Phase 1 instructions in onboarding_prompts.md to gather core requirements (data model, workload, scale, and migration context) using user-friendly phrasing and enforcing constraints (such as the 90% confidence rule) before proposing any recommendation.

Phase 2: Recommendation Analysis & Matrix Consultation

Once you have gathered sufficient explicit discovery context, you must determine the optimal Google Cloud database recommendation.

  1. Consult Matrix & Formulate Recommendation (JiT): Follow the Phase 2 instructions in references/onboarding_prompts.md (or, when the user's prompt already specifies the source database and workload requirements, skip reading references/onboarding_prompts.md and read only the matching source section in references/recommendation_matrix.txt via view_file StartLine/EndLine — MySQL: 44-118, PostgreSQL: 119-236, SQL Server: 237-305, Oracle: 306-463, HBase/DynamoDB/Cassandra: 464-616, Redis/Valkey/Memcached/Aerospike: 617-751, MongoDB/DocumentDB/CosmosDB: 752-797, Neo4j/Neptune/Graph: 798-836 — to formulate a single primary recommendation).
  2. Deliver Recommendation: Deliver the recommendation to the user, mapping destination codes to plain English, explaining the reasoning, and offering to help with provisioning.

Phase 3: Implementation & Provisioning (Plan-Validate-Execute Pattern)

When the user accepts the recommendation and requests to provision or modify cloud resources, you must initiate the Implementation & Provisioning phase.

  1. Load Provisioning Instructions (JiT): Read the Phase 3 section of references/onboarding_prompts.md (if not already loaded) using view_file.
  2. Execute Plan-Validate-Execute Workflow: Follow the detailed Phase 3 instructions in references/onboarding_prompts.md to analyze the workspace, confirm target file paths with the user, draft and validate Terraform or gcloud provisioning scripts according to the required formatting and tagging rules, and prepare a Change List (CL) or Pull Request for user review without applying live infrastructure changes directly.

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