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 agentmods add skills/rsalmn/extremerouter/extremerouternpx skills add rsalmn/ExtremeRouter --skill extremeroutergit clone --depth 1 https://github.com/rsalmn/ExtremeRouterWrote 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/rsalmn/extremerouter/extremerouter)<a href="https://agentmods.dev/skills/rsalmn/extremerouter/extremerouter"><img src="https://agentmods.dev/badge/skills/rsalmn/extremerouter/extremerouter.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 | $0.00084 | $0.00855 |
| Opus 5 | $0.00042 | $0.00428 |
| Sonnet 5 | $0.00017 | $0.00171 |
| Haiku 4.5 | $0.00008 | $0.00085 |
Grade A, and why
extremerouter 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 5d 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.
Verify: `curl $NINEROUTER_URL/api/health` → `{"ok":true}` How it starts
The opening of the file, as written. The whole thing — 62 lines — stays where its author put it; the contents beside it link to each section on GitHub.
ExtremeRouter
Local/remote AI gateway exposing OpenAI-compatible REST. One key, many providers, auto-fallback.
Setup
export NINEROUTER_URL="http://localhost:20128" # or VPS / tunnel URL
export NINEROUTER_KEY="sk-..." # from Dashboard → Keys (only if requireApiKey=true)
All requests: ${NINEROUTER_URL}/v1/... with header Authorization: Bearer ${NINEROUTER_KEY} (omit if auth disabled).
Verify: curl $NINEROUTER_URL/api/health → {"ok":true}
Discover models
curl $NINEROUTER_URL/v1/models # chat/LLM (default)
curl $NINEROUTER_URL/v1/models/image # image-gen
curl $NINEROUTER_URL/v1/models/tts # text-to-speech
curl $NINEROUTER_URL/v1/models/embedding # embeddings
curl $NINEROUTER_URL/v1/models/web # web search + fetch (entries have `kind` field)
curl $NINEROUTER_URL/v1/models/stt # speech-to-text
curl $NINEROUTER_URL/v1/models/image-to-text # vision
Use data[].id as model field in requests. Combos appear with owned_by:"combo".
Response shape:
{ "object": "list", "data": [
{ "id": "openai/gpt-5", "object": "model", "owned_by": "openai", "created": 1735000000 },
{ "id": "tavily/search", "object": "model", "kind": "webSearch", "owned_by": "tavily", "created": 1735000000 }
]}
Capability skills
When the user needs a specific capability, fetch that skill's SKILL.md from its raw URL:
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.
- 5d ago First seen · 62 lines · 84 tokens per session scan A 7e915ab5fd53
extremerouter is a skill published in the GitHub repository rsalmn/ExtremeRouter (30 stars, last pushed today), licensed MIT. It adds 84 tokens to every session and 855 once invoked, about $0.0004 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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ml-pipeline
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model-evaluator
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pandas-helper
Master pandas operations — DataFrames, Series, groupby, merge, time-series resampling, and memory optimization.