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 ypollak2/llm-router --skill routinggit clone --depth 1 https://github.com/ypollak2/llm-routerWrote 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/ypollak2/llm-router/routing)<a href="https://agentmods.dev/skills/ypollak2/llm-router/routing"><img src="https://agentmods.dev/badge/skills/ypollak2/llm-router/routing.svg" alt="Measured on agentmods" height="20"></a>- NVIDIA SkillSpector pass
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 | $0.00016 | $0.00431 |
| Opus 5 | $0.00008 | $0.00216 |
| Sonnet 5 | $0.00003 | $0.00086 |
| Haiku 4.5 | $0.00002 | $0.00043 |
Grade A, and why
routing scanned grade A with 0 findings 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.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
What it actually says
LLM Router — Smart Routing Skill
Route tasks to the cheapest capable model automatically using llm_router MCP tools.
When to Use This Skill
Before answering research, code, writing, or analysis tasks — call the appropriate llm_router tool instead of answering directly. The router picks the cheapest model that can handle the task (Ollama → Codex → paid APIs in free-first order).
Task → Tool Mapping
| Task type | Tool to call | Why |
|---|---|---|
| Simple factual question | llm_query |
Gemini Flash / Groq — 50× cheaper than o3 |
| Research / current events | llm_research |
Perplexity (web-grounded, not stale) |
| Writing / summaries / brainstorm | llm_generate |
Gemini Flash / Haiku |
| Deep analysis / debugging | llm_analyze |
GPT-4o / Gemini Pro |
| Code generation / refactoring | llm_code |
Ollama → Codex built-in → o3 |
| Don't know which type | llm_auto |
Auto-classifies + routes, tracks savings |
How to Call
llm_query(prompt="What is the capital of France?")
llm_code(prompt="Refactor this function to use async/await", complexity="moderate")
llm_research(prompt="What changed in Python 3.13?")
llm_auto(prompt="<the full user request>") # safest default
When NOT to Route
- File read/write/edit operations — execute directly
- Inline tool calls where you have the answer already
- Tasks under 5 words (likely follow-ups, not standalone requests)
Cost Impact
Routing simple tasks to Gemini Flash instead of o3 saves ~50–100×.
llm_auto shows cumulative savings every 5 calls automatically.
Run llm_savings anytime to see your totals.
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 Changed · +6 lines · +16 tokens per session c181d0d11b11
- 8d ago First seen · 42 lines · 0 tokens per session scan A 3e54d58fc3b3
routing is a skill published in the GitHub repository ypollak2/llm-router (77 stars, last pushed 3d ago), licensed MIT. It adds 16 tokens to every session and 431 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-08-30.
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