Flagshiprouter Tts

Community

theRizwan

flagshiprouter-tts

Text-to-speech via FlagshipRouter /v1/audio/speech using OpenAI / ElevenLabs / Deepgram / Edge TTS / Google TTS / Hyperbolic / Inworld voices. Use when the user wants to convert text to speech, generate audio, voiceover, narrate, or read text aloud.

Overview

Publisher	theRizwan
Repository	`FlagshipRouter`
Skill name	`flagshiprouter-tts`
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 Tts 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-tts
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-tts .claude/skills/flagshiprouter-tts

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

Use it in TypingMind

Enable Flagshiprouter Tts 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 Tts 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 Tts 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 — Text-to-Speech

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
# 1) List models
curl $FLAGSHIPROUTER_URL/v1/models/tts | jq '.data[].id'
# 2) Per-model metadata (params, voicesUrl if voice-by-id)
curl "$FLAGSHIPROUTER_URL/v1/models/info?id=el/eleven_multilingual_v2"
# 3) List voices (elevenlabs, edge-tts, deepgram, inworld, local-device). Optional ?lang=vi
curl "$FLAGSHIPROUTER_URL/v1/audio/voices?provider=edge-tts&lang=vi" | jq '.data[].model'

model field in /v1/audio/speech = voice ID directly (e.g. edge-tts/vi-VN-HoaiMyNeural, el/<voice_id>, or openai/tts-1 model+default voice).

Endpoint

POST $FLAGSHIPROUTER_URL/v1/audio/speech

Field	Required	Notes
`model`	yes	voice ID from `/v1/models/tts`
`input`	yes	text to speak

Query ?response_format=mp3 (default, raw bytes) or ?response_format=json ({audio: base64, format}).

Examples

Save MP3:

bash
curl -X POST "$FLAGSHIPROUTER_URL/v1/audio/speech" \
  -H "Authorization: Bearer $FLAGSHIPROUTER_KEY" \
  -H "Content-Type: application/json" \
  -d '{"model":"openai/tts-1","input":"Hello world"}' \
  --output speech.mp3

JS (save file):

js
import { writeFile } from "node:fs/promises";
const r = await fetch(`${process.env.FLAGSHIPROUTER_URL}/v1/audio/speech`, {
  method: "POST",
  headers: { "Authorization": `Bearer ${process.env.FLAGSHIPROUTER_KEY}`, "Content-Type": "application/json" },
  body: JSON.stringify({ model: "el/eleven_multilingual_v2", input: "Xin chào" }),
});
await writeFile("speech.mp3", Buffer.from(await r.arrayBuffer()));

Response shape

Default → raw audio bytes (Content-Type audio/mp3).

?response_format=json:

json
{ "audio": "SUQzBAAAA...", "format": "mp3" }

Provider quirks (model format)

Provider	`model` format	Notes
`openai`	`tts-1/alloy` (model/voice) or just voice	Default model `gpt-4o-mini-tts`
`elevenlabs`	`<model_id>/<voice_id>` or `<voice_id>`	Default model `eleven_flash_v2_5`; list voices in Dashboard
`openrouter`	`openai/gpt-4o-mini-tts/alloy`	Streamed via chat-completions audio modality
`edge-tts`	voice id e.g. `vi-VN-HoaiMyNeural`	noAuth; default `vi-VN-HoaiMyNeural`
`google-tts`	language code e.g. `en`, `vi`	noAuth
`local-device`	OS voice name (`say -v ?` / SAPI)	noAuth; needs `ffmpeg`
`deepgram`	`aura-asteria-en` etc	Token auth
`nvidia`, `inworld`, `cartesia`, `playht`	`model/voice`	Provider-specific auth header
`coqui`, `tortoise`	speaker / voice id	Localhost noAuth
`hyperbolic`	model id	Body = `{text}` only

Frequently asked questions

What does the Flagshiprouter Tts AI skill do?

Why use Flagshiprouter Tts on TypingMind?

Because you install it once and use it with any model. Flagshiprouter Tts 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 Tts in TypingMind?

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

Which AI models can use Flagshiprouter Tts?

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 Tts?

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

Is the Flagshiprouter Tts 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

Brag

NousResearch

OrganizationPopular

Project launch video via Hyperframes, upstream-maintained.

Comfyui

Generate images, video, and audio via diffusion workflows.

Heartmula

HeartMuLa: Suno-like song generation from lyrics + tags.

Hyperframes

Render MP4/WebM videos from HTML compositions.

Overview

Installation

Install in TypingMind

Install in another agent

Use it in TypingMind

Works with any AI model

Skill instructions

FlagshipRouter — Text-to-Speech

Discover

Endpoint

Examples

Response shape

Provider quirks (model format)

Frequently asked questions

Related AI Skills

Set up your own AI workspace now