# Auto Router

> Auto-decide whether a task runs on a LOCAL model or a CLOUD model (DeepSeek, GLM, Nemotron, Grok, Gemma, …) from an automatic effort estimate, and run multi-model fusion (cascade, draft→refine, vote). Use when the user wants automatic local-vs-cloud routing, to add cloud LLM providers, to make local and cloud models collaborate, or mentions effort-based routing, model fusion/ensemble, OpenRouter,…

- **Type:** Skill
- **Install:** `agentstack add skill-zedarvates-botte-secrete-auto-router`
- **Verified:** Yes — security-reviewed for prompt injection and unsafe behavior
- **Seller:** [zedarvates](https://agentstack.voostack.com/s/zedarvates)
- **Installs:** 0
- **Category:** [AI & ML](https://agentstack.voostack.com/c/ai-and-ml)
- **Latest version:** 0.1.0
- **License:** MIT
- **Upstream author:** [zedarvates](https://github.com/zedarvates)
- **Source:** https://github.com/zedarvates/botte-secrete/tree/main/skills/auto_router
- **Website:** https://github.com/zedarvates/botte-secrete

## Install

```sh
agentstack add skill-zedarvates-botte-secrete-auto-router
```

Requires the [AgentStack CLI](https://agentstack.voostack.com/docs/cli). Works with Claude Code, Cursor, and any MCP-compatible agent.

## About

# auto_router — effort-based local↔cloud routing + fusion

Decides *for you* how much model muscle a task needs, then sends it to the
cheapest capable backend — local first, cloud when it's worth it. Extends
`tiered_router` (cost tiers) and `llm_backends` (local discovery) with a cloud
catalog and ensemble strategies.

## When to use

- "Pick local or cloud automatically based on how hard the task is."
- "Use DeepSeek / GLM / Nemotron / Grok / Gemma alongside my local models."
- "Have a local model draft and a stronger model refine" (fusion).
- The user mentions effort routing, model fusion/ensemble, OpenRouter, or any of
  the cloud providers above.

## Auto-decision

```bash
python -m skills.auto_router.cli route "classify: bug or feature?"   # → LOCAL
python -m skills.auto_router.cli route "design a distributed cache and prove correctness"
python -m skills.auto_router.cli run   "summarize this PR in 2 lines" --max-tokens 200
```

Effort is scored from prompt signals (length, code, stack traces, reasoning vs
trivial vocabulary, multi-file scope) → a `Tier`. `Tier ≤ LOCAL` with a local
backend runs local (0 cloud tokens); higher tiers pick the cheapest available
cloud model, budget-aware, and **fall back to local** when no cloud key is set.

## Cloud providers

```bash
python -m skills.auto_router.cli providers   # catalog + which are available now
```

Data-driven catalog in `providers.py` — DeepSeek (chat/reasoner), Zhipu GLM,
NVIDIA Nemotron, xAI Grok, Google Gemma. Reach them two ways:

- **OpenRouter** — set `OPENROUTER_API_KEY`, every model by slug, one endpoint.
- **Native** — set the provider's own key (`DEEPSEEK_API_KEY`, `XAI_API_KEY`,
  `ZHIPUAI_API_KEY`, `NVIDIA_API_KEY`), used in preference to OpenRouter.

A model is only routed to when its key is present. Add a row to `CATALOG` and it
routes — slugs/versions are editable defaults.

## Fusion (models collaborating)

```bash
python -m skills.auto_router.cli fusion cascade "is 17 prime?"            # cheap→escalate
python -m skills.auto_router.cli fusion draft   "explain the CAP theorem" # local drafts, cloud refines
python -m skills.auto_router.cli fusion vote    "capital of France, one word?"  # consensus
```

- **cascade** — local/cheap first; escalate to a stronger model only if the
  answer looks low-confidence.
- **draft_refine** — local model drafts (free), a stronger cloud model polishes.
  This is the "local + cloud together" mode.
- **vote** — several models answer; return the consensus (great for classification).

All fusion modes degrade gracefully with no cloud key (local-only).

## MCP

Exposed via [[llm_mcp]] as tools `auto_route` and `fusion`, so an agent can route
and fuse on its own. Related: `tiered_router`, `llm_backends`, `response_cache`.

## Source & license

This open-source skill is cataloged on AgentStack and links to its original source — we do not rehost the code.

- **Author:** [zedarvates](https://github.com/zedarvates)
- **Source:** [zedarvates/botte-secrete](https://github.com/zedarvates/botte-secrete)
- **License:** MIT
- **Homepage:** https://github.com/zedarvates/botte-secrete

Install and usage instructions live in the source repository linked above.

## Pricing

- **Free** — Free

## Security capabilities

Automated source analysis of v0.1.0 — what this tool can access:

- **Network access:** no
- **Filesystem access:** no
- **Shell / process execution:** no
- **Environment & secrets:** no
- **Dynamic code execution:** no

*"Yes" means the capability is present in the source — more access means more to trust, not that it is unsafe.*


## Versions

- **0.1.0** — security scan: passed — Imported from the upstream source.

## Links

- Listing page: https://agentstack.voostack.com/l/skill-zedarvates-botte-secrete-auto-router
- Seller: https://agentstack.voostack.com/s/zedarvates
- Browse the marketplace: https://agentstack.voostack.com/browse

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Listed on AgentStack — the marketplace for AI agent skills and MCP servers. Every listing is security-reviewed. Creators keep 70%.