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 bobmatnyc/claude-mpm-skills --skill openroutergit clone --depth 1 https://github.com/bobmatnyc/claude-mpm-skillsWrote 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/bobmatnyc/claude-mpm-skills/openrouter)<a href="https://agentmods.dev/skills/bobmatnyc/claude-mpm-skills/openrouter"><img src="https://agentmods.dev/badge/skills/bobmatnyc/claude-mpm-skills/openrouter/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/bobmatnyc/claude-mpm-skills/openrouter"><img src="https://agentmods.dev/badge/skills/bobmatnyc/claude-mpm-skills/openrouter.svg" alt="Reviewed on agentmods" width="80" height="20"></a>- Socket pass
- Snyk warn
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 | $0.00032 | $0.07130 |
| Opus 5 | $0.00016 | $0.03565 |
| Sonnet 5 | $0.00006 | $0.01426 |
| Haiku 4.5 | $0.00003 | $0.00713 |
Grade B, and why
openrouter scanned grade B 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 11d 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.
Sends data to an external URLmediumData exfiltration
A POST to an outside endpoint may be telemetry or may be exfiltration; either way the mod talks to somewhere, and you should know where.
const res = await fetch('https://openrouter.ai/api/v1/chat/completions', { method: 'POST', How it starts
The opening of the file, as written. The whole thing — 1,137 lines — stays where its author put it; the contents beside it link to each section on GitHub.
OpenRouter - Unified AI API Gateway
Overview
OpenRouter provides a single API to access 200+ language models from OpenAI, Anthropic, Google, Meta, Mistral, and more. It offers intelligent routing, streaming, cost optimization, and standardized OpenAI-compatible interface.
Key Features:
- Access 200+ models through one API
- OpenAI-compatible interface (drop-in replacement)
- Intelligent model routing and fallbacks
- Real-time streaming responses
- Cost tracking and optimization
- Model performance analytics
- Function calling support
- Vision model support
Pricing Model:
- Pay-per-token (no subscriptions)
- Volume discounts available
- Free tier with credits
- Per-model pricing varies
Installation:
npm install openai # Use OpenAI SDK
# or
pip install openai # Python
Quick Start
1. Get API Key
# Sign up at https://openrouter.ai/keys
export OPENROUTER_API_KEY="sk-or-v1-..."
2. Basic Chat Completion
import OpenAI from 'openai';
const client = new OpenAI({
baseURL: 'https://openrouter.ai/api/v1',
apiKey: process.env.OPENROUTER_API_KEY,
defaultHeaders: {
'HTTP-Referer': 'https://your-app.com', // Optional
'X-Title': 'Your App Name', // Optional
}
});
async function chat() {
const completion = await client.chat.completions.create({
model: 'anthropic/claude-3.5-sonnet',
messages: [
{ role: 'user', content: 'Explain quantum computing in simple terms' }
],
});
console.log(completion.choices[0].message.content);
}
3. Streaming Response
async function streamChat() {
const stream = await client.chat.completions.create({
model: 'openai/gpt-4-turbo',
messages: [
{ role: 'user', content: 'Write a short story about AI' }
],
stream: true,
});
for await (const chunk of stream) {
const content = chunk.choices[0]?.delta?.content || '';
process.stdout.write(content);
}
}
Model Selection Strategy
What ships with it
3 files 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.
- 11d ago First seen · 1,137 lines · 32 tokens per session scan B fd560f54a082
openrouter is a skill published in the GitHub repository bobmatnyc/claude-mpm-skills (74 stars, last pushed 1mo ago), licensed MIT. It adds 32 tokens to every session and 7,130 once invoked, about $0.0002 per session on Opus 5. A static security scan graded it B with 1 finding (sends data to an external url). No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
Other skills, from other repositories
llm-integration
Claude and OpenAI API patterns, prompt design, context management, streaming, tool use, cost control, multi-model routing.
groq-inference
Ultra-fast LLM inference on custom LPU hardware. OpenAI-compatible API at api.groq.com. Lowest latency in the industry (500-1000+ tok/s). Supports chat completions, vision, audio (Whisper STT + TTS), tool calling, JSON mode, and streaming. Free tier available. Inference only — no training.
grpc-expert
Expert-level gRPC, Protocol Buffers, microservices communication, and streaming. Use when the user mentions Protocol Buffers, microservices, RPC, or streaming, or when the task involves gRPC Fundamentals, Communication Patterns, or Production Features.
model-strategy
Multi-model orchestration and model-switching strategy. Score-based model selection, reasoning-effort routing, cross-agent delegation (Gemini, Codex, Ollama), advisor pairing, escalation triggers, permission matrix, and cost-efficiency optimization.
kimi-code-api
Integration guidance for Kimi Code, a coding model service, using its login flow, tokens, chat requests, and model-list requests.
serving-llms-vllm
Use when deploying production LLM APIs, optimizing inference latency/throughput, or serving models with limited GPU memory. Supports OpenAI-compatible endpoints, quantization (GPTQ/AWQ/FP8), and tensor parallelism.