Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx skills add mydisha/keirouter --skill keirouter-sttgit clone --depth 1 https://github.com/mydisha/keirouterWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/mydisha/keirouter/keirouter-stt)<a href="https://agentmods.dev/skills/mydisha/keirouter/keirouter-stt"><img src="https://agentmods.dev/badge/skills/mydisha/keirouter/keirouter-stt.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00057 | $0.00848 |
| Opus 5 | $0.00028 | $0.00424 |
| Sonnet 5 | $0.00011 | $0.00170 |
| Haiku 4.5 | $0.00006 | $0.00085 |
Grade A, and why
keirouter-stt scanned grade A with 1 finding against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 7d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Makes network callslowCapability
Not a fault in itself. Listed so you know the mod talks to something, and to what.
curl $KEIROUTER_URL/v1/models/stt | jq '.data[].id' How it starts
The opening of the file, as written. The whole thing — 78 lines — stays where its author put it; the contents beside it link to each section on GitHub.
KeiRouter — Speech-to-Text
Requires KEIROUTER_URL (and KEIROUTER_KEY if auth enabled). See https://raw.githubusercontent.com/mydisha/keirouter/main/skills/keirouter/SKILL.md for setup.
Discover
curl $KEIROUTER_URL/v1/models/stt | jq '.data[].id'
# Per-model params (language, response_format, prompt, temperature support)
curl "$KEIROUTER_URL/v1/models/info?id=openai/whisper-1"
model = STT model ID (e.g. openai/whisper-1, groq/whisper-large-v3, deepgram/nova-3, gemini/gemini-2.5-flash).
Endpoint
POST $KEIROUTER_URL/v1/audio/transcriptions (OpenAI Whisper compatible, multipart/form-data)
| Field | Required | Notes |
|---|---|---|
model |
yes | from /v1/models/stt |
file |
yes | audio file (mp3, wav, m4a, webm, ogg, flac) |
language |
no | ISO-639-1 (e.g. en, vi) |
prompt |
no | hint text to guide transcription |
response_format |
no | json (default) / text / verbose_json / srt / vtt |
temperature |
no | 0–1 |
Examples
curl -X POST "$KEIROUTER_URL/v1/audio/transcriptions" \
-H "Authorization: Bearer $KEIROUTER_KEY" \
-F "model=openai/whisper-1" \
-F "[email protected]" \
-F "language=en"
JS (Node):
import { createReadStream } from "node:fs";
const form = new FormData();
form.append("model", "groq/whisper-large-v3-turbo");
form.append("file", new Blob([await (await import("node:fs/promises")).readFile("audio.mp3")]), "audio.mp3");
const r = await fetch(`${process.env.KEIROUTER_URL}/v1/audio/transcriptions`, {
method: "POST",
headers: { "Authorization": `Bearer ${process.env.KEIROUTER_KEY}` },
body: form,
});
const { text } = await r.json();
console.log(text);
Response shape
Default (response_format=json):
{ "text": "Hello, this is the transcription." }
verbose_json adds language, duration, segments[] with timestamps.
srt / vtt return subtitle text.
Provider quick reference
| Provider | model format |
Notes |
|---|---|---|
| OpenAI | whisper-1, gpt-4o-transcribe, gpt-4o-mini-transcribe |
Native OpenAI shape |
| Groq | whisper-large-v3, whisper-large-v3-turbo |
Fastest; OpenAI shape |
| Gemini | gemini-2.5-flash, gemini-2.5-pro |
Server converts to generateContent with audio |
| Deepgram | nova-3, nova-2 |
Token auth; server adapts response |
| AssemblyAI | universal-3-pro, universal-2 |
Async upload+poll handled server-side |
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 7d ago First seen · 78 lines · 57 tokens per session scan A 6831e22e41d1
keirouter-stt is a skill published in the GitHub repository mydisha/keirouter (130 stars, last pushed 9d ago), licensed MIT. It adds 57 tokens to every session and 848 once invoked, about $0.0003 per session on Opus 5. A static security scan graded it A with 1 finding (makes network calls). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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Use when the user wants to transcribe audio to text using OATDA's unified audio API. Supports speech-to-text (STT), meetings, podcasts, voice notes, Whisper-style transcription, and the transcribeaudio MCP capability.