Agent Platform Rag Engine Management
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using...
Install
npx skills add google/skills --skill agent-platform-rag-engine-management -g -a claude-code -y- Repository
- google/skills21.8k
- Category
- Data and ML
- Updated
- 3d ago
- License
- Apache-2.0
- Context cost
- Mediumabout 2,280 tokens
- Runs scripts
- No, instructions only
What it does
Manage and query Agent Platform RAG Engine Corpora and retrieve grounded contexts using the Google GenAI SDK. Use when listing RAG corpora or files, inspecting a corpus, retrieving contexts, or generating content grounded in a RAG corpus. Do not use for standard database queries (use SQL/Spanner skills), Google Workspace RAG, or other RAG products like gRAG.
Agent Platform RAG Engine Management
This skill provides instructions on how to interact with Agent Platform RAG
Engine using the Agent Platform Python SDK. You MUST use the vertexai Python
SDK to perform RAG Engine operations, rather than raw REST calls or MCP tools,
because this code is intended to be run by external clients.
Safety & Confirmation Tiers (CRITICAL)
Before executing any commands or scripts on behalf of the user, you must adhere to the following safety tiers based on the action requested:
-
Tier R: Read-only (
list_corpora,list_files,get_corpus,retrieval_query)- No confirmation needed. Execute immediately to gather information or retrieve grounded contexts.
-
Tier RC: Read-only but consumes Compute Resources (
client.models.generate_content)- Requires interactive confirmation with 'Yes'/'No' options before executing grounded content generation. The confirmation prompt MUST clearly explain the proposed generation execution and its key parameters (e.g., target corpus ID, query text, target model). Natural-language paraphrases without specifying exact parameters are insufficient, as explicit parameter listing is required to ensure unambiguous user approval of the specific resource and configuration.
- Same-turn restriction: Do not execute the generation code in the same turn as presenting the confirmation prompt. Stop and wait for the user's reply; only execute after explicit 'Yes' / approval.
- Gold Standard Example:
