Menú
Route a task to the best LLM based on task type and complexity
Instalar con Codex o Claude Copia este prompt, pégalo en Codex, Claude u otro asistente, y deja que revise la página de la skill y la instale por ti.
Basado en la clasificación ocupacional SOC
| name | route |
| description | Route a task to the best LLM based on task type and complexity |
| trigger | /route |
Route any task to the optimal LLM automatically.
/route <task description>
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:
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)
| Category | Tool | Signals |
|---|---|---|
| Research | llm_research | Current events, news, funding, trends, market data, rankings |
| Generate | llm_generate | Writing, drafting, brainstorming, emails, articles, translations |
| Analyze | llm_analyze | Evaluation, debugging, comparison, trade-offs, code review |
| Code | llm_code | Implementation, refactoring, building, bug fixes |
| Query | llm_query | Simple questions, definitions, explanations |
| Image | llm_image | Visual generation, design, artwork |
| 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 |
Every 5th routed task, the system shows estimated savings: Claude API costs avoided and rate limit capacity preserved. Run llm_usage for a detailed breakdown.
What are the top 3 AI startups that raised funding?
→ research (heuristic, score=8) → llm_research (budget) → Perplexity Sonar
Write me a blog post about productivity tips
→ generate (heuristic, score=5) → llm_generate (balanced) → Gemini 2.5 Pro
Compare React vs Vue for our new project
→ analyze (ollama, qwen3.5) → llm_analyze (balanced) → GPT-4o
Implement a rate limiter in Python using sliding window
→ code (heuristic, score=4) → llm_code (balanced) → GPT-4o
What is a monad?
→ query (ollama, qwen3.5) → llm_query (budget) → Gemini Flash
Environment variables:
LLM_ROUTER_OLLAMA_MODEL — Ollama model (default: qwen3.5:latest)LLM_ROUTER_OLLAMA_URL — Ollama server (default: http://localhost:11434)LLM_ROUTER_OLLAMA_TIMEOUT — Timeout in seconds (default: 5)LLM_ROUTER_CONFIDENCE_THRESHOLD — Heuristic score cutoff (default: 4)