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 routegit 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/route)<a href="https://agentmods.dev/skills/ypollak2/llm-router/route"><img src="https://agentmods.dev/badge/skills/ypollak2/llm-router/route.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 | $0.00883 |
| Opus 5 | $0.00008 | $0.00441 |
| Sonnet 5 | $0.00003 | $0.00177 |
| Haiku 4.5 | $0.00002 | $0.00088 |
Grade A, and why
route 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 4d 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.
How it starts
The opening of the file, as written. The whole thing — 85 lines — stays where its author put it; the contents beside it link to each section on GitHub.
/route — Smart LLM Task Router
Route any task to the optimal LLM automatically.
Usage
/route <task description>
Auto-Classification
Most prompts are classified automatically by the UserPromptSubmit hook — no /route needed. The hook uses a multi-layer classification chain:
-
Heuristic scoring (instant, free) — Three signal layers accumulate evidence:
- Intent patterns (+3) — action verbs and task markers
- Topic patterns (+2) — domain-specific nouns
- Format patterns (+1) — structural and temporal cues
- High-confidence match (score >= 4) routes immediately
-
Ollama local LLM (~1s, free) — When heuristics are uncertain, qwen3.5 classifies locally via the chat API with thinking disabled
-
Cheap API model (~$0.0001) — If Ollama is unavailable, Gemini Flash or GPT-4o-mini classifies
-
Weak heuristic / auto fallback — Last resort: low-confidence heuristic match or
llm_route(full LLM classifier)
Task Categories
The consolidated llm(prompt=..., task=..., tier=...) tool is the front door for all of
these — task= picks the specialization, tier= (fast/balanced/best) picks the cost tier:
| Category | Call | Signals |
|---|---|---|
| Research | llm(task="research") |
Current events, news, funding, trends, market data, rankings |
| Generate | llm(task="generate") |
Writing, drafting, brainstorming, emails, articles, translations |
| Analyze | llm(task="analyze") |
Evaluation, debugging, comparison, trade-offs, code review |
| Code | llm(task="code") |
Implementation, refactoring, building, bug fixes |
| Query | llm(task="query") (or task="auto") |
Simple questions, definitions, explanations |
| Image | llm_image |
Visual generation, design, artwork |
Complexity & Profiles
| Complexity | Profile | Model Tier |
|---|---|---|
| Simple | budget |
Gemini Flash, GPT-4o-mini |
| Moderate | balanced |
GPT-4o, Gemini 2.5 Pro |
| Complex | premium |
o3, Gemini 2.5 Pro |
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.
- 4d ago Changed · +3 lines 56cc1cd82b07
- 8d ago First seen · 82 lines · 16 tokens per session scan A b85960235476
route 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 883 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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