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name: hermes-smart-router description: Use when switching models, saving costs, or routing queries. Automatically picks the cheapest model that can handle the job — "translate hello" routes to $0/M local, "design a database" routes to $3/M pro. 100% local classification, zero API calls for routing. version: 0.2.2 author: raydatalab license: MIT platforms: [linux, macos, wsl] triggers:

• model switch
• change model
• /model
• /tier
• switch to
• use local
• use flash
• use pro
• too slow
• wasting tokens
• cheaper model
• downgrade
• upgrade model
• routing
• tier selection
• local model
• what model
• which model
• speed up
• save cost
• 切换模型
• 太慢了
• 换模型
• 用什么模型 metadata: hermes: tags: [routing, model, cost-optimization, ollama] homepage: https://github.com/raydatalab/hermes-smart-router related_skills: [hermes-cost-optimization]

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Smart Router

Overview

"Translate hello to German"       → local   $0/M tok
"Explain how DNS works"           → flash   $0.15/M tok  (GPT-4o-mini)
"Design a distributed database"   → pro     $3/M tok  (Claude Sonnet)

Smart Router classifies every query locally (Ollama embeddings + semantic-router) and picks the cheapest tier that can handle it. Simple queries route to free local models. Complex reasoning routes to frontier models. You pay for what you need — not what your config happens to be set to.

Classification runs entirely on your machine. Zero API calls for routing decisions. Zero keys needed. ~3s on first call, <1ms after.

When to Use

Load this skill when:

• The user is toggling between models manually (wasting tokens on simple queries)
• The user asks about cost saving, model switching, or routing
• The user mentions /model, /tier, or switches models mid-session
• The agent is about to answer a complex question and should verify the current tier

Do NOT load for: greetings, one-liners, translations, queries under 20 characters.

CRITICAL — Agent Instructions

Call router.resolve() before answering any non-trivial query.

from smart_router.router import get_router

router = get_router()
decision = router.resolve(user_message, current_tier=ACTIVE_TIER)
# → {"tier": "pro", "model": {...}, "needs_switch": true,
#    "reason": "Upgrade from flash to pro — Complex code...",
#    "recommendation": "💡 Switch to pro: `/model anthropic claude-sonnet-4` — ..."}

If decision["recommendation"] is not None, paste it at the top of your response — it's ready to use, no formatting needed.

If decision["recommendation"] is None, just answer normally. If the call errors or times out, skip it and answer — never retry.

ACTIVE_TIER is your current tier (local/flash/pro). Check with /tier or ask.

When to Skip

Skip routing for: greetings ("hello", "thanks"), translations, one-liner facts, queries under 20 characters. Everything else — route.

When to Route

• Complex: 3+ tool calls, reasoning, architecture, multi-step code, debugging → route
• Unsure: If it takes more than a sentence to answer → route
• Default: If in doubt, route. Routing cost (~3s first call, <1ms after) is always less than answering from the wrong tier.

Tier Reference

Tier	Example Model	Input Price/1M tok	Use When
local	Ollama (llama3, qwen, etc.)	$0	Simple Q&A, translations, offline
flash	GPT-4o-mini, Gemini Flash, Claude Haiku	~$0.15–0.80	General knowledge, casual coding
pro	Claude Sonnet, GPT-4o, Gemini Pro	~$2.50–3	Complex reasoning, architecture

Pricing per official API pages (OpenAI, Anthropic, Google). See individual provider docs for exact rates. Per-token pricing means a single 1K-token question costs $0.003 on flash vs $0.003 on pro — but over thousands of queries per month, the difference compounds.

Prerequisites

• Hermes Agent v0.17+
• Ollama installed
• semantic-router[ollama] and smart_router

Configuration

smart_router:
  enabled: true
  default_tier: flash
  encoder_model: nomic-embed-text
  tiers:
    local:
      provider: custom
      model: llama3.2:3b
      base_url: http://localhost:11434/v1
    flash:
      provider: openai
      model: gpt-4o-mini
    pro:
      provider: anthropic
      model: claude-sonnet-4
  ollama:
    auto_start: true
    idle_timeout: 300

Slash Commands

Command	Description
/route <query>	Show tier selection (dry run)
/route-stats	Session routing statistics
/ollama start / stop / status	Ollama lifecycle
/tier	Show current tier and model

Common Pitfalls

1. Agent forgets to call router.resolve(). The most common failure mode. If the agent answers without routing, manually trigger with /route <query>.
2. Ollama not running. If decision["ollama_ready"] is false, start Ollama first (/ollama start) or skip routing for this query.
3. Slow first call. First router.resolve() pulls nomic-embed-text (~274MB). Subsequent calls are instant. Warm up with python3 -m smart_router route "test" before heavy sessions.
4. Fast-path false negatives. Queries under 20 chars skip embedding. If a short query needs pro-level reasoning, the router won't catch it — use /model manually.

Testing

bash scripts/install.sh
python3 -m smart_router route "What is the capital of France?"
python3 -m smart_router chat
python3 -m pytest tests/