Claude-skill-registry agentuity-cli-cloud-vector-upsert

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

install

source · Clone the upstream repo

git clone https://github.com/majiayu000/claude-skill-registry

Claude Code · Install into ~/.claude/skills/

T=$(mktemp -d) && git clone --depth=1 https://github.com/majiayu000/claude-skill-registry "$T" && mkdir -p ~/.claude/skills && cp -r "$T/skills/data/agentuity-cli-cloud-vector-upsert" ~/.claude/skills/majiayu000-claude-skill-registry-agentuity-cli-cloud-vector-upsert && rm -rf "$T"

manifest: skills/data/agentuity-cli-cloud-vector-upsert/SKILL.md

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