google-cloud-solution-hybrid-search-alloydb

Files (6)

• SKILL.md
• output-template.md · assets/
• attribution.md · references/
• design-recommendations.md · references/
• product-mapping.md · references/
• related-guidance.md · references/

SKILL.md (first lines)

# Dynamic Hybrid Search using AlloyDB

This skill provides a workflow to design and implement secure, low-latency, and
high-accuracy hybrid search solutions combining structured dataset filtering,
vector search indexing, faceted metadata filtering, semantic reranking, recall
evaluation, in-database AI validation, database abstraction layers, and
serverless application hosting.

## Attribution

**MUST READ**: Before executing any `gcloud`, REST API, or MCP command, you
MUST read and follow the instructions in
[Usage Attribution](references/attribution.md).

## Overview of the workflow

The workflow consists of the following phases:

1. **Requirements discovery**. Gather detailed requirements related to
  the cloud workload or use case that the user needs assistance for.
2. **Solution architecture**. Use the requirements that were gathered
  in Phase 1 to generate a detailed solution architecture for the cloud
  workload or use case.
3. **Solution validation**. Create a plan to validate the generated
  solution, generate validation instructions and scripts, and run the
  validation.
4. **Solution packaging and presentation**. Consolidate the generated
  content and present the solution.

**Important notes about the workflow**:

- **Strict phase separation**: During Phase 1 (Requirements discovery), when you
  ask the user clarifying questions, DON'T recommend, propose, or outline any
  architectural designs, cloud services, or component mappings. This prevents
  premature architecture commitments or hallucinations before the full scope is
  understood.
- **Halting for approval**: For any step where you are instructed
  to "obtain approval before proceeding", you MUST stop executing, present the
  completed tasks to the user, and wait for their explicit approval. You MUST
  NOT proceed to execute any subsequent tasks or generate any further guidance
  in that response.
- **Ground all generated content**: For all tasks across all phases, you MUST
  first look in the following resources:
  - [Product Mapping](references/product-mapping.md),
  - [Design Recommendations](references/design-recommendations.md) for the
  required guidance. If the guidance does not provide the required information,
  you MUST ground the generated content by using the following resources:

  - Google Developer Knowledge MCP server:
    https://developers.google.com/knowledge/mcp.md.txt
    - Server: https://developerknowledge.googleapis.com/mcp
      - Tools:
        - `developerknowledge:search_documents`
        - `developerknowledge:get_documents`
        - `developerknowledge:answer_query`
  - Relevant skills from https://github.com/google/skills
  - Official Google Cloud documentation in
    [Related Guidance](references/related-guidance.md)

## Product Renaming & Terminology

When generating solution designs, architecture diagrams, and documentation,
check the latest Google Cloud documentation for the most up-to-date product
names. The table below provides examples of name mappings to be aware of. Note
that underlying APIs, Terraform resources, and IAM roles may retain their legacy
identifiers.

<table>
  <thead>
    <tr>
      <th>Legacy Name</th>
      <th>Updated Name</th>
      <th>Notes</th>
    </tr>
  </thead>
  <tbody>
    <tr>
      <td>Vertex AI</td>
      <td>Gemini Enterprise Agent Platform</td>
      <td>Gemini Enterprise Agent Platform can be shortened to Agent Platform after first instance</td>
    </tr>
    <tr>
      <td>Vertex AI Embedding</td>
      <td>Text embedding on Gemini Enterprise Agent Platform</td>
      <td>This refers to the text embedding models available on Gemini Enterprise Agent Platform</td>
    </tr>
    <tr>
      <td>Vertex AI Matching Engine</td>
      <td>Vector Search</td>
      <td></td>
    </tr>
  </tbody>
</table>

## Phase 1: Requirements discovery

In this phase, you must gather detailed requirements related to the hybrid
search workload that the user wants to design and deploy in Google Cloud.

**Acknowledge provided requirements**: If the
user's prompt already contains some requirements (functional or non-functional,
such as catalog size, search modalities, faceted attributes, or latency
targets), you MUST explicitly acknowledge and restate all of these requirements
in your response. Do NOT ask the user to describe or re-describe any
requirements that they have already provided in the prompt.

Complete the following steps strictly in the specified order:

- [ ] **Step 1**: Ask the user to describe the functional requirements of the
  workload, including catalog dataset details (e.g., e-commerce apparel, retail
  products, patent database), search modalities (natural language text, visual
  search, attribute filters), metadata attributes for faceted filtering (e.g.,
  `category`, `sub_category`, `color`, `gender`, `price`), and quality checks
  (reranking, LLM validation).
- [ ] **Step 2**: You MUST explicitly ask the user to describe ALL of the
  following six categories of non-functional requirements. You need this
  information because each category represents a critical architectural pillar,
  and neglecting any of them can result in a solution that is insecure,
  unreliable, or inefficient (do NOT omit any of them):

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