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Routes tasks to the optimal LLM based on type and complexity, avoiding Claude API costs. Automatically classifies prompts using heuristics, local Ollama, or cheap API models.
How this skill is triggered — by the user, by Claude, or both
Slash command
/chuzom:routeThe summary Claude sees in its skill listing — used to decide when to auto-load this skill
Route any task to the optimal LLM automatically.
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)npx claudepluginhub chuzom/chuzom --plugin chuzomRoutes tasks to the optimal LLM based on type and complexity, avoiding Claude API costs. Automatically classifies prompts using heuristics, local Ollama, or cheap API models.
Routes AI tasks to optimal LLMs by analyzing budget, deployment (local/cloud), and modality (text/vision/coding). Fetches live model data via curl and runs Python router script.
Routes OpenRouter API calls to optimal models by task (e.g., code review to Claude-3.5-Sonnet) or prompt complexity for cost, quality, latency optimization in multi-model apps.