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 techysy/10router --skill 10router-imagegit clone --depth 1 https://github.com/techysy/10routerWrote 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/techysy/10router/10router-image)<a href="https://agentmods.dev/skills/techysy/10router/10router-image"><img src="https://agentmods.dev/badge/skills/techysy/10router/10router-image/github.svg" alt="Measured on agentmods" height="20"></a>Or the 80×15 button, for a site that already has a row of RSS and ATOM ones. Only the verdict fits; the numbers stay here.
<a href="https://agentmods.dev/skills/techysy/10router/10router-image"><img src="https://agentmods.dev/badge/skills/techysy/10router/10router-image.svg" alt="Reviewed on agentmods" width="80" 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 | $0.00074 | $0.01034 |
| Opus 5.5 | $0.00030 | $0.00414 |
| Sonnet 5.5 | $0.00015 | $0.00207 |
| Haiku 4.5 | $0.00007 | $0.00103 |
Grade A, and why
10router-image 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 24d 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 $TENROUTER_URL/v1/models/image | jq '.data[].id' This is a copy
80% identical to 9router-image — 24 lines differ, which has more behind it and is treated as the original. This page carries a canonical link to it rather than competing with it.
How it starts
The opening of the file, as written. The whole thing — 87 lines — stays where its author put it; the contents beside it link to each section on GitHub.
10Router — Image Generation
Requires TENROUTER_URL (and TENROUTER_KEY if auth enabled). See https://raw.githubusercontent.com/techysy/10router/main/skills/10router/SKILL.md for setup.
Discover
curl $TENROUTER_URL/v1/models/image | jq '.data[].id'
# Per-model params/options (size enum, quality enum, capabilities like edit)
curl "$TENROUTER_URL/v1/models/info?id=openai/dall-e-3"
Endpoint
POST $TENROUTER_URL/v1/images/generations
| Field | Required | Notes |
|---|---|---|
model |
yes | from /v1/models/image |
prompt |
yes | image description |
n |
no | count (provider-dependent) |
size |
no | 1024x1024, 1792x1024, ... |
quality |
no | standard / hd (OpenAI) |
response_format |
no | url (default) or b64_json |
Add query ?response_format=binary to receive raw image bytes (handy for saving file).
Examples
Save to file (binary):
curl -X POST "$TENROUTER_URL/v1/images/generations?response_format=binary" \
-H "Authorization: Bearer $TENROUTER_KEY" \
-H "Content-Type: application/json" \
-d '{"model":"gemini/gemini-3-pro-image-preview","prompt":"watercolor mountains at sunrise","size":"1024x1024"}' \
--output out.png
JS (URL response):
const r = await fetch(`${process.env.TENROUTER_URL}/v1/images/generations`, {
method: "POST",
headers: { "Authorization": `Bearer ${process.env.TENROUTER_KEY}`, "Content-Type": "application/json" },
body: JSON.stringify({ model: "gemini/gemini-3-pro-image-preview", prompt: "neon city", size: "1024x1024" }),
});
const { data } = await r.json();
console.log(data[0].url || data[0].b64_json.slice(0, 40));
Response shape
JSON (default response_format=url):
{ "created": 1735000000, "data": [{ "url": "https://..." }] }
response_format=b64_json:
{ "created": 1735000000, "data": [{ "b64_json": "iVBORw0KGgo..." }] }
Query ?response_format=binary returns raw image bytes (Content-Type image/png or image/jpeg).
What ships with it
1 file beside SKILL.md in the same directory: the scripts, references and assets a skill reads on demand. Not counted in the per-session cost; read them before you install if any of them is executable.
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.
- 24d ago Changed fc658b03ddfc
- 1mo ago First seen · 87 lines · 74 tokens per session scan A 5d378b678e57
10router-image is a skill published in the GitHub repository techysy/10router (93 stars, last pushed today), licensed MIT. It adds 74 tokens to every session and 1,034 once invoked, about $0.0003 per session on Opus 5.5. A static security scan graded it A with 1 finding (makes network calls). It is 80% identical to 9router-image, differing in 24 lines, and is treated as a copy.
Other skills, from other repositories
keirouter
Entry point for KeiRouter — local/remote AI gateway with OpenAI-compatible REST for chat, image, TTS, embeddings, web search, web fetch. Use when the user mentions KeiRouter, KEIROUTERURL, or wants AI without writing provider boilerplate. This skill covers setup + indexes capability skills; fetch the relevant…
keirouter-chat
Chat / code generation via KeiRouter using OpenAI /v1/chat/completions or Anthropic /v1/messages format with streaming + auto-fallback combos. Use when the user wants to ask an LLM, generate code, summarize text, or run prompts through KeiRouter.
keirouter-image
Generate images via KeiRouter /v1/images/generations using OpenAI (DALL-E, gpt-image), xAI, Venice or Recraft models, or any OpenAI-compatible image server. Use when the user wants to create, generate, draw, or render an image, picture, or text-to-image (txt2img).
keirouter-stt
Speech-to-text via KeiRouter /v1/audio/transcriptions using OpenAI Whisper or Groq Whisper models (or any OpenAI-compatible transcription server). Use when the user wants to transcribe audio, convert speech to text, or get subtitles from audio files.
keirouter-embeddings
Generate vector embeddings via KeiRouter /v1/embeddings using OpenAI / Mistral / Cohere / Voyage / NVIDIA / AWS Bedrock and other embedding models for RAG, semantic search, similarity. Use when the user wants embeddings, vectors, RAG, semantic search, or to embed text.
keirouter-tts
Text-to-speech via KeiRouter /v1/audio/speech using OpenAI voices (or any OpenAI-compatible speech server added as a custom provider). Use when the user wants to convert text to speech, generate audio, voiceover, narrate, or read text aloud.