Auto Router

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

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

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)

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
• Source: zedarvates/botte-secrete
• License: MIT
• Homepage: https://github.com/zedarvates/botte-secrete

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