How do I install the Agentuity CLI Cloud Vector Upsert skill?

Run npx skillmds add majiayu000/agentuity-cli-cloud-vector-upsert in your terminal (requires Node.js), paste this page's agent-chat prompt into Claude, Cursor, or any MCP-connected agent, or download the SKILL.md file and copy it into your agent's skills directory.

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Is Agentuity CLI Cloud Vector Upsert free to use?

Yes. Installing skills from SkillMD is free. This skill is licensed under Apache-2.

Who published Agentuity CLI Cloud Vector Upsert?

majiayu000 (@majiayu000) published this skill. Their other Agent Skills are listed on their SkillMD profile.

Agentuity CLI Cloud Vector Upsert by majiayu000

Name: Agentuity CLI Cloud Vector Upsert
Rating: 4.666666666666667 (3 reviews)
Author: majiayu000

File contents

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

---name: agentuity-cli-cloud-vector-upsertdescription: Add or update vectors in the vector storage. Requires authentication. Use for Agentuity cloud platform operationslicense: Apache-2.0--- # 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 ```bash 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: ```bash bunx @agentuity/cli vector upsert products doc1 --document "Comfortable office chair" ``` Upsert with metadata: ```bash bunx @agentuity/cli vector upsert products doc1 --document "Chair" --metadata '{"category":"furniture"}' ``` Upsert with pre-computed embeddings: ```bash bunx @agentuity/cli vector upsert embeddings vec1 --embeddings "[0.1, 0.2, 0.3]" ``` Bulk upsert from JSON file: ```bash bunx @agentuity/cli vector upsert products --file vectors.json ``` Bulk upsert from stdin: ```bash cat vectors.json | bunx @agentuity/cli vector upsert products - ``` ## Output Returns JSON object: ```json { "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 |

Frequently asked questions