Flagshiprouter Embeddings

Community

theRizwan

flagshiprouter-embeddings

Generate vector embeddings via FlagshipRouter /v1/embeddings using OpenAI / Gemini / Mistral / Voyage / Nvidia / GitHub embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.

Overview

Publisher	theRizwan
Repository	`FlagshipRouter`
Skill name	`flagshiprouter-embeddings`
Stars	199
Forks	82
Bundled files	Instructions only
License	MIT
Links	Skill source Repository

Markdown instructions
A SKILL.md file the model loads on demand, so it only costs tokens when a request actually matches.
Works with any LLM
AI skills are plain Markdown, not provider-specific code, so this works with GPT, Claude, Gemini, Grok, or a local model.
Self-contained
Everything the model needs lives in the instructions — no extra files to sync.
Open source
Published by theRizwan on GitHub. Read the source before you install it.

Installation

Install the Flagshiprouter Embeddings AI skill in TypingMind to use it with any LLM, or drop it into another agent that reads SKILL.md.

Install in TypingMind

TypingMind installs a skill straight from its GitHub folder — it reads SKILL.md, bundles the resource files, and stores the result locally.

Open the app and go to Plugins → Skills.
Choose "Install from GitHub".
Paste the skill folder URL below and confirm.
https://github.com/theRizwan/FlagshipRouter/tree/main/skills/flagshiprouter-embeddings
Enable the skill in any chat where you want it available.

Plugins → Skills → Add skill → From GitHub URL, then paste the folder URL and press Continue.

Install in another agent

Any agent that reads the Agent Skills format can use this skill — copy the folder into that agent's skills directory.

Claude Code — .claude/skills

git clone --depth 1 https://github.com/theRizwan/FlagshipRouter.git /tmp/FlagshipRouter
mkdir -p .claude/skills
cp -r /tmp/FlagshipRouter/skills/flagshiprouter-embeddings .claude/skills/flagshiprouter-embeddings

Restart Claude Code after copying so it picks up the new skill.

Use it in TypingMind

Enable Flagshiprouter Embeddings in any TypingMind chat and the model takes it from there. Its name and description sit in the system prompt, and the moment a request matches, the model loads the full instructions itself — you never invoke it by hand, and it costs no tokens until it is actually used.

The model loads Flagshiprouter Embeddings on its own as soon as a request matches it.

Works with any AI model

AI skills are plain Markdown instructions rather than provider-specific code, so Flagshiprouter Embeddings is not tied to the model it was written for. Install it once in TypingMind and use it with GPT-5, Claude, Gemini, Grok, DeepSeek, Mistral, Llama, or a local model you run yourself — all on your own API keys.

Loaded only when it is needed
The system prompt carries just the name and description. The instructions are fetched on the first matching request, so an idle skill costs nothing.
Switch models mid-chat
Because the skill is instructions rather than code, changing model does not break it — the next model reads the same SKILL.md.

Skill instructions

This is the SKILL.md content the model loads. Read it before installing — a skill is instructions your model will follow.

FlagshipRouter — Embeddings

Requires FLAGSHIPROUTER_URL (and FLAGSHIPROUTER_KEY if auth enabled). See https://raw.githubusercontent.com/theRizwan/FlagshipRouter/refs/heads/main/skills/flagshiprouter/SKILL.md for setup.

Discover

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

Endpoint

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

JS:

js
const r = await fetch(`${process.env.FLAGSHIPROUTER_URL}/v1/embeddings`, {
  method: "POST",
  headers: { "Authorization": `Bearer ${process.env.FLAGSHIPROUTER_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 quirks

Provider	Notes
`openai`, `openrouter`, `mistral`, `voyage-ai`, `fireworks`, `together`, `nebius`, `github`, `nvidia`, `jina-ai`	Native OpenAI shape — `dimensions` works only on OpenAI v3 (`text-embedding-3-*`)
`gemini`, `google_ai_studio`	Server auto-converts to `embedContent`/`batchEmbedContents` — send OpenAI shape
`openai-compatible-`, `custom-embedding-`	Custom `baseUrl` from credentials

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

Frequently asked questions

What does the Flagshiprouter Embeddings AI skill do?

Why use Flagshiprouter Embeddings on TypingMind?

Because you install it once and use it with any model. Flagshiprouter Embeddings is plain Markdown rather than provider-specific code, so the same skill runs on GPT-5, Claude, Gemini, Grok, or a local model — and you can switch model mid-chat without it breaking. TypingMind runs on your own API keys, so you pay providers directly instead of a per-seat subscription, and your skills and chats stay in your own storage.

How do I install Flagshiprouter Embeddings in TypingMind?

Open Plugins → Skills → Install from GitHub in TypingMind and paste https://github.com/theRizwan/FlagshipRouter/tree/main/skills/flagshiprouter-embeddings. TypingMind reads its SKILL.md and installs it as a skill you can enable per chat.

Which AI models can use Flagshiprouter Embeddings?

Any model you connect in TypingMind. AI skills are plain Markdown instructions rather than provider-specific code, so GPT, Claude, Gemini, Grok, and local models can all load this skill when a request matches it.

How many AI models can I use with Flagshiprouter Embeddings?

As many as you like. As long as a model supports skills, you can use Flagshiprouter Embeddings with it — GPT, Claude, Gemini, Grok, DeepSeek, Mistral, Llama and more — all on TypingMind with your own API keys.

Is the Flagshiprouter Embeddings AI skill free?

Yes. It is published on GitHub by theRizwan under the MIT license. You only pay your own AI provider for the tokens you use.

What are AI skills?

An AI skill is a reusable instruction bundle that teaches an AI model how to do one specific task. It follows the open Agent Skills format: a SKILL.md file with a name and description, plus any scripts, templates or reference files the model may need. The model reads the instructions only when your request matches the skill, so an installed skill costs nothing until it is used.

How are AI skills different from plugins or MCP servers?

A plugin or MCP server gives a model new tools to call — code that runs somewhere and returns a result. An AI skill gives the model knowledge and process instead: how to approach a task, which steps to follow, what good output looks like. Skills are plain Markdown, so they need no server, no API key and no runtime, and they work with any model.

View all

Graincrawl

openclaw

OrganizationPopular

Granola archive: search, sync freshness, notes, transcripts, panels, SQL counts, and Graincrawl repo work.

Notcrawl

Notion archive: search, sync freshness, pages/databases, Markdown exports, SQL counts, and Notcrawl repo work.

Openclaw Changelog Update

openclaw

OrganizationPopular

Regenerate OpenClaw release changelog sections from git history before beta, stable, or extended-stable releases.

Openclaw Ci Limits

Manage OpenClaw GitHub Actions and Blacksmith CI capacity, runner-registration budgets, fanout caps, main-push single-flight, shard sizing, hosted-runner offload, queue health, and safe…

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

FlagshipRouter — Embeddings

Discover

Endpoint

Examples

Response shape

Provider quirks

Frequently asked questions

Related AI Skills

Set up your own AI workspace now