Claude Code Plugins

Community-maintained marketplace

Feedback

agentuity-cli-cloud-vector-upsert

@agentuity/discord-help-agent
1
0

Add or update vectors in the vector storage. Requires authentication. Use for Agentuity cloud platform operations

Install Skill

1Download skill
2Enable skills in Claude

Open claude.ai/settings/capabilities and find the "Skills" section

3Upload to Claude

Click "Upload skill" and select the downloaded ZIP file

Note: Please verify skill by going through its instructions before using it.

SKILL.md

name agentuity-cli-cloud-vector-upsert
description Add or update vectors in the vector storage. Requires authentication. Use for Agentuity cloud platform operations
version 0.0.110
license Apache-2.0
allowed-tools Bash(agentuity:*)
argument-hint <namespace> [key]
metadata [object Object]

Cloud Vector Upsert

Add or update vectors in the vector storage

Prerequisites

  • Authenticated with agentuity auth login
  • Project context required (run from project directory or use --project-id)

Usage

agentuity cloud vector upsert <namespace> [key] [options]

Arguments

Argument Type Required Description
<namespace> string Yes -
<key> string No -

Options

Option Type Required Default Description
--document string Yes - document text to embed
--embeddings string Yes - pre-computed embeddings as JSON array
--metadata string Yes - metadata as JSON object
--file string Yes - path to JSON file containing vectors, or "-" for stdin

Examples

Upsert a single vector with document text:

bunx @agentuity/cli vector upsert products doc1 --document "Comfortable office chair"

Upsert with metadata:

bunx @agentuity/cli vector upsert products doc1 --document "Chair" --metadata '{"category":"furniture"}'

Upsert with pre-computed embeddings:

bunx @agentuity/cli vector upsert embeddings vec1 --embeddings "[0.1, 0.2, 0.3]"

Bulk upsert from JSON file:

bunx @agentuity/cli vector upsert products --file vectors.json

Bulk upsert from stdin:

cat vectors.json | bunx @agentuity/cli vector upsert products -

Output

Returns JSON object:

{
  "success": "boolean",
  "namespace": "string",
  "count": "number",
  "results": "array",
  "durationMs": "number"
}
Field Type Description
success boolean Whether the operation succeeded
namespace string Namespace name
count number Number of vectors upserted
results array Upsert results with key-to-id mappings
durationMs number Operation duration in milliseconds