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Agent skill

Vector Embed

by ruvnet in ruvnet/ruflo

Generate embeddings via npx ruvector@0.2.25 embed text (ONNX all-MiniLM-L6-v2, 384-dim), normalize, and store in HNSW index

MITAuto-check: notesAI & LLM Engineering

Install Vector Embed

skills CLI
$ npx skills add ruvnet/ruflo --skill vector-embed -a claude-code

Project install by default; add -g for ~/.claude/skills/.

GitHub CLI
$ gh skill install ruvnet/ruflo vector-embed --agent claude-code

Project scope by default; add --scope user for a personal install. Needs GitHub CLI 2.90.0 or later (public preview).

Manual copy
$ git clone --depth 1 https://github.com/ruvnet/ruflo.git skills-src && mkdir -p .claude/skills && cp -r skills-src/plugins/ruflo-ruvector/skills/vector-embed .claude/skills/vector-embed && rm -rf skills-src

Use ~/.claude/skills/ instead of .claude/skills for a personal install. The folder must contain SKILL.md.

Claude Code skills documentation · loads skills from .claude/skills/

Facts

Skill name
vector-embed
GitHub stars
74k
Token cost
~591 tokens
SKILL.md length
241 words
Files
1
Skills in repo
264
Repo updated
First seen
Licence
MIT

At a glance

Generate embeddings via npx ruvector@0.2.25 embed text (ONNX all-MiniLM-L6-v2, 384-dim), normalize, and store in HNSW index

  • Works in 5 steps: Ensure ruvector@0.2.25 is available → Embed the input (use the text… → Adaptive (LoRA) variant: npx -y… → …
  • Tasks that involve Embeddings
  • SKILL.md covers When to use, Steps, MCP alternative and Caveats
  • Calls npx, npm and claude

What it does

Vector Embed is an agent skill from ruvnet/ruflo. Generate embeddings via npx ruvector@0.2.25 embed text (ONNX all-MiniLM-L6-v2, 384-dim), normalize, and store in HNSW index

Its SKILL.md is about 590 tokens, which your agent loads only when the skill is triggered. It is a single SKILL.md file with no bundled scripts.

It sits in AI & LLM Engineering, covering Embeddings and Vector databases. It works with ONNX and Model Context Protocol. The repository describes itself as: 🌊 The original agent harness. Deploy intelligent multi-player swarms, coordinate autonomous workflows, and build conversational AI systems. Features adaptive memory…. The licence is MIT.

When your agent uses it

  • Tasks that involve Embeddings
  • Tasks that involve Vector databases

Example prompts

  • “/vector-embed”

Requirements

  • Node.js
  • Pre-approved tools (allowed-tools): Bash, Read, mcp__plugin_ruflo-core_ruflo__memory_store, mcp__plugin_ruflo-core_ruflo__memory_search

Workflow steps

5 steps, taken from the first numbered list in SKILL.md.

  1. Ensure ruvector@0.2.25 is available
  2. Embed the input (use the text subcommand, with text as a positional arg)
  3. Adaptive (LoRA) variant: npx -y ruvector@0.2.25 embed text "..." --adaptive --domain code
  4. Confirm — report vector dimension (384), norm, and any output path written.
  5. Store metadata in AgentDB if needed

What it can do on your machine

Read from SKILL.md and the folder at commit de590e1. It shows what the files ask for, not the result of running them.

  • Tool permissions

    Pre-approves these tools, so the agent can use them without asking each time:

    • Bash
    • Read
    • mcp__plugin_ruflo-core_ruflo__memory_store
    • mcp__plugin_ruflo-core_ruflo__memory_search

    From allowed-tools in the SKILL.md frontmatter.

  • Runs code

    Shell commands in SKILL.md call:

    • npx
    • npm
    • claude

    From the folder's file list and the shell code blocks in SKILL.md.

  • Network

    No URLs in SKILL.md. Its commands use npx and npm, which can reach the network depending on how they are called.

    From URLs in SKILL.md, links to its own repository left out.

  • Credentials

    Names no API keys, tokens, secrets or passwords.

    From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Vector Embed loads about 591 tokens when it runs. Until then it costs about 34 tokens; SKILL.md has 241 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it
~34
When it runs · the whole SKILL.md, loaded when a task matches
~591

Estimates: characters ÷ 4, the usual rule of thumb; real counts depend on the model's tokenizer. Scripts and assets cost tokens only if the agent reads them.

Safety

Auto-check: notes

The automated check noted patterns worth knowing about, such as sudo or a known installer.

  • NotePre-approves every shell command (allowed-tools: Bash)SKILL.md
    allowed-tools: Bash, Read, mcp__plugin_ruflo-core_ruflo__memory_store, mcp__plugin_ruflo-core_ruflo__memory_search

Automated static check — not a guarantee. Review scripts before installing. It scans the text of SKILL.md for risky patterns (piping downloads into a shell, reading credential files, hidden Unicode, destructive commands); files beside SKILL.md are not scanned.

SKILL.md

The full file from ruvnet/ruflo at commit de590e1, republished under its MIT licence (© ruvnet). 241 words, ~591 tokens.

Download SKILL.mdSave it as .claude/skills/vector-embed/SKILL.md (or your agent's skills folder).
name
vector-embed
description
Generate embeddings via npx ruvector@0.2.25 embed text (ONNX all-MiniLM-L6-v2, 384-dim), normalize, and store in HNSW index
allowed-tools
Bash, Read, mcp__plugin_ruflo-core_ruflo__memory_store, mcp__plugin_ruflo-core_ruflo__memory_search
argument-hint
<text-or-file>

Vector Embed

Generate and store vector embeddings using the ruvector npm package.

When to use

Use this skill to embed text, code, or documents into 384-dimensional vectors for semantic search, similarity comparison, or clustering. ruvector uses ONNX all-MiniLM-L6-v2 with HNSW indexing (52,000+ inserts/sec, ~0.045ms search).

Steps

  1. Ensure ruvector@0.2.25 is available:
    bash
    npm ls ruvector 2>/dev/null | grep '0.2.25' || npm install ruvector@0.2.25
    If embed text later reports ONNX WASM files not bundled, also run:
    bash
    npm install ruvector-onnx-embeddings-wasm
  2. Embed the input (use the text subcommand, with text as a positional arg):
    • Single string: npx -y ruvector@0.2.25 embed text "your text here"
    • With output file: npx -y ruvector@0.2.25 embed text "your text here" -o vec.json
    • For a file: read its content via the Read tool, then pass it as the positional argument.
    • For batch: loop over files in shell — ruvector@0.2.25 has no built-in --batch/--glob flags.
  3. Adaptive (LoRA) variant: npx -y ruvector@0.2.25 embed text "..." --adaptive --domain code
  4. Confirm — report vector dimension (384), norm, and any output path written.
  5. Store metadata in AgentDB if needed: mcp__plugin_ruflo-core_ruflo__memory_store({ key: "embed-SOURCE", value: "VECTOR_METADATA", namespace: "vector-patterns" })

MCP alternative

Register the MCP server once with the pinned version:

bash
claude mcp add ruvector -- npx -y ruvector@0.2.25 mcp start

Then call MCP tools directly: hooks_rag_context (semantic context), brain_search (collective brain), hooks_ast_analyze, hooks_route.

Caveats

  • The embed --batch --glob and embed --file flags do not exist in ruvector@0.2.25; only embed text <text> is supported. Read files yourself and call embed text per file.
  • ONNX runtime is not bundled by default. If embedding fails, install ruvector-onnx-embeddings-wasm or run npx -y ruvector@0.2.25 doctor to diagnose.

© ruvnet, MIT. Rendered from Markdown: HTML in the file is shown as text, images as links, and headings moved down two levels. Raw file

Files

Just SKILL.md in plugins/ruflo-ruvector/skills/vector-embed of ruvnet/ruflo.

Open the folder on GitHubat commit de590e1

Compare with similar skills

Vector Embed next to the 5 skills that share the most tags, products or categories with it. Stars are the repository's; “used in” counts other GitHub owners with a copy.

Vector Embed compared with similar skills
SkillStarsUsed inTokensAuto-checkLicenceRepo updated
Vector Embed this skillruvnet/ruflo74k—~591Automated safety check: NotesMIT
Codebase Managementgiancarloerra/SocratiCode3.3k1 repos~1.8kAutomated safety check: PassAGPL-3.0
Pgvector Semantic Searchtimescale/pg-aiguide1.9k1 repos~3.8kAutomated safety check: PassApache-2.0
Cookbook Aimldatabricks-solutions/databricks-apps-cookbook183—~1.7kAutomated safety check: PassCustom licence
Frontmcp Extensibilityagentfront/frontmcp146—~3.2kAutomated safety check: PassApache-2.0
Cognee Integrations Setuptopoteretes/cognee32k—~1kAutomated safety check: NotesApache-2.0

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Works with

Categories

Questions about Vector Embed

What does Vector Embed do?

Generate embeddings via npx ruvector@0.2.25 embed text (ONNX all-MiniLM-L6-v2, 384-dim), normalize, and store in HNSW index. Vector Embed is an agent skill from ruvnet/ruflo.

When should I use Vector Embed?

Vector Embed fits situations like: tasks that involve Embeddings; tasks that involve Vector databases.

How do I install Vector Embed in Claude Code?

Run `npx skills add ruvnet/ruflo --skill vector-embed -a claude-code`. Or copy the skill folder (plugins/ruflo-ruvector/skills/vector-embed in ruvnet/ruflo) into .claude/skills/vector-embed in your project. Claude Code loads it when a task matches its description.

How do I install Vector Embed in Codex?

Run `npx skills add ruvnet/ruflo --skill vector-embed -a codex`. Or copy the skill folder (plugins/ruflo-ruvector/skills/vector-embed in ruvnet/ruflo) into .agents/skills/vector-embed in your project. Codex loads it when a task matches its description.

Can I use Vector Embed in Cursor, Gemini CLI or GitHub Copilot?

Cursor, Gemini CLI, GitHub Copilot and OpenCode also load SKILL.md folders. With the skills CLI, run `npx skills add ruvnet/ruflo --skill vector-embed -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/vector-embed, .gemini/skills/vector-embed, .github/skills/vector-embed and .opencode/skills/vector-embed in your project.

What does Vector Embed need to run?

Going by SKILL.md and its folder, Vector Embed needs the command-line tools its instructions call (npx, npm and claude). Our summary lists: Node.js. Its frontmatter pre-approves these tools: Bash, Read, mcp__plugin_ruflo-core_ruflo__memory_store, mcp__plugin_ruflo-core_ruflo__memory_search.

Does Vector Embed access the network?

SKILL.md contains no URLs. Its commands use npx and npm, which can reach the network depending on how they are called. This is read from the text; nothing was executed.

Is Vector Embed safe to install?

Our automated static check of SKILL.md found notes only (pre-approves every shell command (allowed-tools: bash)), nothing it rates as a warning. It is not a guarantee. Review the folder before installing.

What licence does Vector Embed use?

Vector Embed is published under the MIT licence (the repository's licence). It allows redistribution, so the full SKILL.md is shown on this page.

How many tokens does Vector Embed use?

About 591 tokens (SKILL.md is roughly 2.4k characters). Agents keep only the skill's name and description in context until a task matches; then they load SKILL.md in full.

What are the alternatives to Vector Embed?

Skills that share tags, products or a category with Vector Embed: Codebase Management (giancarloerra/SocratiCode, 3.3k stars), Pgvector Semantic Search (timescale/pg-aiguide, 1.9k stars), Cookbook Aiml (databricks-solutions/databricks-apps-cookbook, 183 stars) and Frontmcp Extensibility (agentfront/frontmcp, 146 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Vector Embed?

ruvnet (a GitHub user) maintains it in ruvnet/ruflo, which has 74,012 GitHub stars. The repository holds 264 skills in this directory. The repository was last updated on October 7, 2026.

Source: ruvnet/ruflo on GitHub. Facts on this page come from the repository at the commit we read; the author's words are quoted as theirs.