Agent skill

Keirouter Embeddings

Generate vector embeddings via KeiRouter /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia embedding models for RAG, semantic search, similarity.

MITAuto-check passedAI & LLM Engineering

Install Keirouter Embeddings

skills CLI

$ npx skills add mydisha/keirouter --skill keirouter-embeddings -a claude-code

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

GitHub CLI

$ gh skill install mydisha/keirouter keirouter-embeddings --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/mydisha/keirouter.git skills-src && mkdir -p .claude/skills && cp -r skills-src/skills/keirouter-embeddings .claude/skills/keirouter-embeddings && 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/

Paste into Claude Code

Install the "keirouter-embeddings" agent skill from https://github.com/mydisha/keirouter/tree/main/skills/keirouter-embeddings into .claude/skills/keirouter-embeddings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keirouter-embeddings", then confirm the skill loads.

Claude Code copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

$skill-installer

$skill-installer install https://github.com/mydisha/keirouter/tree/main/skills/keirouter-embeddings

Type this inside Codex. $skill-installer <name> installs a curated skill from openai/skills. The installer writes to $CODEX_HOME/skills (default ~/.codex/skills). Restart Codex if the skill does not show up.

skills CLI

$ npx skills add mydisha/keirouter --skill keirouter-embeddings -a codex

Project install goes to .agents/skills/; add -g for ~/.codex/skills/.

GitHub CLI

$ gh skill install mydisha/keirouter keirouter-embeddings --agent codex

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mydisha/keirouter.git skills-src && mkdir -p .agents/skills && cp -r skills-src/skills/keirouter-embeddings .agents/skills/keirouter-embeddings && rm -rf skills-src

Use ~/.agents/skills/ instead of .agents/skills for a personal install.

Codex skills documentation · loads skills from .agents/skills/

Paste into Codex

Install the "keirouter-embeddings" agent skill from https://github.com/mydisha/keirouter/tree/main/skills/keirouter-embeddings into .agents/skills/keirouter-embeddings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keirouter-embeddings", then confirm the skill loads.

Codex copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add mydisha/keirouter --skill keirouter-embeddings -a cursor

Project install goes to .agents/skills/; add -g for ~/.cursor/skills/.

GitHub CLI

$ gh skill install mydisha/keirouter keirouter-embeddings --agent cursor

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mydisha/keirouter.git skills-src && mkdir -p .cursor/skills && cp -r skills-src/skills/keirouter-embeddings .cursor/skills/keirouter-embeddings && rm -rf skills-src

Use ~/.cursor/skills/ instead of .cursor/skills for a personal install.

Cursor skills documentation · loads skills from .cursor/skills/, .agents/skills/, .claude/skills/, .codex/skills/

Paste into Cursor

Install the "keirouter-embeddings" agent skill from https://github.com/mydisha/keirouter/tree/main/skills/keirouter-embeddings into .cursor/skills/keirouter-embeddings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keirouter-embeddings", then confirm the skill loads.

Cursor copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

gemini skills install

$ gemini skills install https://github.com/mydisha/keirouter.git --path skills/keirouter-embeddings

--scope user (default) or --scope workspace; --path is the subfolder of the repo that holds the skill; --consent skips the security confirmation prompt.

skills CLI

$ npx skills add mydisha/keirouter --skill keirouter-embeddings -a gemini-cli

Project install goes to .agents/skills/; add -g for ~/.gemini/skills/.

GitHub CLI

$ gh skill install mydisha/keirouter keirouter-embeddings --agent gemini-cli

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mydisha/keirouter.git skills-src && mkdir -p .gemini/skills && cp -r skills-src/skills/keirouter-embeddings .gemini/skills/keirouter-embeddings && rm -rf skills-src

Use ~/.gemini/skills/ instead of .gemini/skills for a personal install, then run /skills reload.

Gemini CLI skills documentation · loads skills from .gemini/skills/, .agents/skills/

Paste into Gemini CLI

Install the "keirouter-embeddings" agent skill from https://github.com/mydisha/keirouter/tree/main/skills/keirouter-embeddings into .gemini/skills/keirouter-embeddings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keirouter-embeddings", then confirm the skill loads.

Gemini CLI copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

GitHub CLI

$ gh skill install mydisha/keirouter keirouter-embeddings

Installs for Copilot at project scope by default; add --scope user for a personal install. Preview a skill first with gh skill preview. Needs GitHub CLI 2.90.0 or later (public preview).

skills CLI

$ npx skills add mydisha/keirouter --skill keirouter-embeddings -a github-copilot

Project install goes to .agents/skills/; add -g for ~/.copilot/skills/.

Manual copy

$ git clone --depth 1 https://github.com/mydisha/keirouter.git skills-src && mkdir -p .github/skills && cp -r skills-src/skills/keirouter-embeddings .github/skills/keirouter-embeddings && rm -rf skills-src

Use ~/.copilot/skills/ instead of .github/skills for a personal install. Commit .github/skills so cloud agent and code review can use it.

GitHub Copilot skills documentation · loads skills from .github/skills/, .claude/skills/, .agents/skills/

Paste into GitHub Copilot

Install the "keirouter-embeddings" agent skill from https://github.com/mydisha/keirouter/tree/main/skills/keirouter-embeddings into .github/skills/keirouter-embeddings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keirouter-embeddings", then confirm the skill loads.

GitHub Copilot copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

skills CLI

$ npx skills add mydisha/keirouter --skill keirouter-embeddings -a opencode

OpenCode documents no install command of its own. Project install goes to .agents/skills/; add -g for ~/.config/opencode/skills/.

GitHub CLI

$ gh skill install mydisha/keirouter keirouter-embeddings --agent opencode

Project scope by default (.agents/skills/); add --scope user for a personal install.

Manual copy

$ git clone --depth 1 https://github.com/mydisha/keirouter.git skills-src && mkdir -p .opencode/skills && cp -r skills-src/skills/keirouter-embeddings .opencode/skills/keirouter-embeddings && rm -rf skills-src

Use ~/.config/opencode/skills/ instead of .opencode/skills for a personal install.

OpenCode skills documentation · loads skills from .opencode/skills/, .claude/skills/, .agents/skills/

Paste into OpenCode

Install the "keirouter-embeddings" agent skill from https://github.com/mydisha/keirouter/tree/main/skills/keirouter-embeddings into .opencode/skills/keirouter-embeddings/ in this project. Copy the whole folder (SKILL.md and every file beside it), keep the folder name "keirouter-embeddings", then confirm the skill loads.

OpenCode copies the folder itself, the same result as the manual copy. Check what it changed before you commit it.

Facts

Skill name: keirouter-embeddings
GitHub stars: 147
Token cost: ~577 tokens
SKILL.md length: 93 words
Files: 1
Skills in repo: 8
Repo updated: Sep 11, 2026
First seen: Oct 7, 2026
Licence: MIT

At a glance

Generate vector embeddings via KeiRouter /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia embedding models for RAG, semantic search, similarity.

The user wants embeddings
SKILL.md covers Discover, Endpoint, Examples and Response shape, plus 1 more section
Calls curl and jq; needs KEIROUTER_KEY
Semantic search

What it does

Keirouter Embeddings is an agent skill from mydisha/keirouter. Generate vector embeddings via KeiRouter /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.

Its SKILL.md is about 580 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. It works with OpenAI, Mistral AI and NVIDIA AI Platform. The repository describes itself as: Your friendly, blazing-fast, self-hostable AI gateway. The licence is MIT.

When your agent uses it

The user wants embeddings
Semantic search

Example prompts

“/keirouter-embeddings”

Requirements

A credential in KEIROUTER_KEY

What it can do on your machine

Read from SKILL.md and the folder at commit 3d8b702. It shows what the files ask for, not the result of running them.

Tool permissions
Pre-approves nothing: there is no allowed-tools line, so your agent's usual permission prompts apply.
From allowed-tools in the SKILL.md frontmatter.
Runs code
Shell commands in SKILL.md call:
- curl
- jq
From the folder's file list and the shell code blocks in SKILL.md.
Network
No URLs in SKILL.md. Its commands use curl, 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 these keys or tokens, usually read from environment variables:
- KEIROUTER_KEY
From names ending in _API_KEY, _TOKEN, _SECRET, _KEY or _PASSWORD in SKILL.md.

Context cost

Keirouter Embeddings loads about 577 tokens when it runs. Until then it costs about 67 tokens; SKILL.md has 93 words of instructions outside code blocks.

Always · name and description, kept in context so the agent knows when to use it: ~67
When it runs · the whole SKILL.md, loaded when a task matches: ~577

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 passed

The automated check found no risky patterns in SKILL.md.

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 mydisha/keirouter at commit 3d8b702, republished under its MIT licence (© mydisha). 93 words, ~577 tokens.

Download SKILL.mdSave it as .claude/skills/keirouter-embeddings/SKILL.md (or your agent's skills folder).

name: keirouter-embeddings
description: Generate vector embeddings via KeiRouter /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.

KeiRouter — Embeddings

Requires KEIROUTER_URL (and KEIROUTER_KEY if auth enabled). See https://raw.githubusercontent.com/mydisha/keirouter/main/skills/keirouter/SKILL.md for setup.

Discover

bash

curl $KEIROUTER_URL/v1/models/embedding | jq '.data[].id'
# Per-model dimensions
curl "$KEIROUTER_URL/v1/models/info?id=openai/text-embedding-3-small"

Endpoint

POST $KEIROUTER_URL/v1/embeddings

Field	Required	Notes
`model`	yes	from `/v1/models/embedding`
`input`	yes	string OR array of strings
`encoding_format`	no	`float` (default) / `base64`
`dimensions`	no	OpenAI v3 only

Examples

bash

curl -X POST $KEIROUTER_URL/v1/embeddings \
  -H "Authorization: Bearer $KEIROUTER_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"openai/text-embedding-3-small","input":["hello","world"]}'

JS:

const r = await fetch(`${process.env.KEIROUTER_URL}/v1/embeddings`, {
  method: "POST",
  headers: { "Authorization": `Bearer ${process.env.KEIROUTER_KEY}`, "Content-Type": "application/json" },
  body: JSON.stringify({ model: "gemini/text-embedding-004", input: "RAG chunk text" }),
});
const { data } = await r.json();
console.log(data[0].embedding.length);  // dimension

Response shape

json

{ "object": "list", "model": "openai/text-embedding-3-small",
  "data": [
    { "object": "embedding", "index": 0, "embedding": [0.0123, -0.045, ...] },
    { "object": "embedding", "index": 1, "embedding": [...] }
  ],
  "usage": { "prompt_tokens": 5, "total_tokens": 5 } }

Provider quick reference

Provider	Notes
OpenAI, Mistral, Voyage, Fireworks, Together, Nebius, NVIDIA, Jina	Native OpenAI shape — `dimensions` works only on OpenAI v3 (`text-embedding-3-*`)
Gemini	Server auto-converts to `embedContent`/`batchEmbedContents` — send OpenAI shape
Custom OpenAI	Custom `baseUrl` from credentials

Batch (input as array) is faster; some providers cap batch size.

Files

Just SKILL.md in skills/keirouter-embeddings of mydisha/keirouter.

Open the folder on GitHubat commit 3d8b702

Compare with similar skills

Keirouter Embeddings 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.

Keirouter Embeddings compared with similar skills
Skill	Stars	Used in	Tokens	Auto-check	Licence	Repo updated
Keirouter Embeddings this skillmydisha/keirouter	147	—	~577	Automated safety check: Pass	MIT	28 days ago
Embeddings via 9Routerdecolua/9router	30k	—	~604	Automated safety check: Pass	MIT	8 days ago
Ax AIdosco/aithy	107	—	~8.2k	Automated safety check: Pass	Apache-2.0	1 mo ago
Golem Add LLM Moonbitgolemcloud/golem	1.5k	—	~1.5k	Automated safety check: Pass	Custom licence	yesterday
AI SDKvercel-labs/ai-facts	168	21 repos	~1.2k	Automated safety check: Pass	None	5 mo ago
Chroma Vector DatabaseOrchestra-Research/AI-Research-SKILLs	13k	8 repos	~2.3k	Automated safety check: Pass	MIT	3 mo ago

Similar skills

Embeddings via 9Router
decolua/9router
Generates vector embeddings through the 9Router /v1/embeddings endpoint, using models from providers such as OpenAI, Gemini, Mistral and Voyage for RAG and semantic search.
30k GitHub stars~604 tokensUpdated 8 days ago
AI & LLM EngineeringAuto-check passed
Ax AI
dosco/aithy
This skill helps an LLM generate correct AI provider setup and configuration code using @ax-llm/ax.
107 GitHub stars~8.2k tokensUpdated 1 mo ago
AI & LLM EngineeringAuto-check passed
Golem Add LLM Moonbit
golemcloud/golem
Adding LLM and AI capabilities to a MoonBit Golem agent. An agent skill from golemcloud/golem.
1.5k GitHub stars~1.5k tokensUpdated yesterday
AI & LLM EngineeringAuto-check passed
AI SDK
vercel-labs/ai-facts
Official
Answer questions about the AI SDK and help build AI-powered features.
168 GitHub starsUsed in 21 repos~1.2k tokens
AI & LLM EngineeringAuto-check passed
Chroma Vector Database
Orchestra-Research/AI-Research-SKILLs
Shows how to store documents and embeddings in Chroma, query them by similarity with metadata filters, and persist them to disk for RAG and semantic search projects.
13k GitHub starsUsed in 8 repos~2.3k tokens
AI & LLM EngineeringAuto-check passed
Codebase Management
giancarloerra/SocratiCode
Set up, index, and manage SocratiCode codebase indexing. An agent skill from giancarloerra/SocratiCode.
3.3k GitHub starsUsed in 1 repo~1.8k tokens
AI & LLM EngineeringAuto-check passed

Questions about Keirouter Embeddings

What does Keirouter Embeddings do?

Generate vector embeddings via KeiRouter /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia embedding models for RAG, semantic search, similarity. Keirouter Embeddings is an agent skill from mydisha/keirouter. Generate vector embeddings via KeiRouter /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia embedding models for RAG, semantic search, similarity.

When should I use Keirouter Embeddings?

Keirouter Embeddings fits situations like: the user wants embeddings; semantic search.

How do I install Keirouter Embeddings in Claude Code?

Run `npx skills add mydisha/keirouter --skill keirouter-embeddings -a claude-code`. Or copy the skill folder (skills/keirouter-embeddings in mydisha/keirouter) into .claude/skills/keirouter-embeddings in your project. Claude Code loads it when a task matches its description.

How do I install Keirouter Embeddings in Codex?

Run `npx skills add mydisha/keirouter --skill keirouter-embeddings -a codex`. Or copy the skill folder (skills/keirouter-embeddings in mydisha/keirouter) into .agents/skills/keirouter-embeddings in your project. Codex loads it when a task matches its description.

Can I use Keirouter Embeddings 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 mydisha/keirouter --skill keirouter-embeddings -a cursor` (or -a gemini-cli, github-copilot or opencode for the others). To copy it by hand, put the folder in .cursor/skills/keirouter-embeddings, .gemini/skills/keirouter-embeddings, .github/skills/keirouter-embeddings and .opencode/skills/keirouter-embeddings in your project.

What does Keirouter Embeddings need to run?

Going by SKILL.md and its folder, Keirouter Embeddings needs the command-line tools its instructions call (curl and jq) and credentials named KEIROUTER_KEY. Our summary lists: A credential in KEIROUTER_KEY.

Does Keirouter Embeddings access the network?

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

Is Keirouter Embeddings safe to install?

Our automated static check of SKILL.md found no risky patterns, such as piping downloads into a shell, reading credential files or hidden Unicode. It is not a guarantee. Review the folder before installing.

What licence does Keirouter Embeddings use?

Keirouter Embeddings 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 Keirouter Embeddings use?

About 577 tokens (SKILL.md is roughly 2.3k 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 Keirouter Embeddings?

Skills that share tags, products or a category with Keirouter Embeddings: Embeddings via 9Router (decolua/9router, 30k stars), Ax AI (dosco/aithy, 107 stars), Golem Add LLM Moonbit (golemcloud/golem, 1.5k stars) and AI SDK (vercel-labs/ai-facts, 168 stars). The comparison table on this page puts their stars, adoption, token cost, safety result and licence side by side.

Who maintains Keirouter Embeddings?

mydisha (a GitHub user) maintains it in mydisha/keirouter, which has 147 GitHub stars. The repository holds 8 skills in this directory. The repository was last updated on September 11, 2026.

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

Keirouter Embeddings

Install Keirouter Embeddings

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

KeiRouter — Embeddings

Discover

Endpoint

Examples

Response shape

Provider quick reference

Files

Compare with similar skills

Similar skills

Embeddings via 9Router

Ax AI

Golem Add LLM Moonbit

AI SDK

Chroma Vector Database

Codebase Management

More from mydisha/keirouter

Keirouter

Keirouter Chat

Keirouter Image

Keirouter Stt

Keirouter Tts

Keirouter Web Fetch

Questions about Keirouter Embeddings

Install Keirouter Embeddings

Facts

At a glance

What it does

When your agent uses it

Example prompts

Requirements

What it can do on your machine

Tool permissions

Runs code

Network

Credentials

Context cost

Safety

SKILL.md

KeiRouter — Embeddings

Discover

Endpoint

Examples

Response shape

Provider quick reference

Files

Compare with similar skills

Similar skills

More from mydisha/keirouter

Related

Questions about Keirouter Embeddings