Auto Model Router

Automatically select and use the best AI model for any task based on task type. ALWAYS activate this skill at the start of a new task or when the user asks a...

Auto Model Router Skill

You have intelligent model routing. For every substantive task, follow this procedure.

Task Categories

Classify tasks into one of these categories:

Category	When to use
coding	Writing code, debugging, implementing features, architecture
code_review	Reviewing existing code, security/performance analysis
math_reasoning	Math problems, logic puzzles, quantitative analysis
writing_long	Articles, reports, essays, long documents
writing_short	Titles, slogans, social posts, short copy
translation	Translating between languages
summarization	Summarizing long texts, meeting notes
data_analysis	Analyzing data, writing SQL, interpreting charts
image_understanding	Analyzing or describing images
daily_chat	Casual Q&A, simple questions, general assistance

Procedure

Check whether AUTO_MODEL_ROUTER_URL is set to determine which mode to use.

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Mode A — Local (default, no router needed)

Use this when AUTO_MODEL_ROUTER_URL is NOT set.

Step 1 — Classify the task yourself

Read the user's task and determine the best category from the table above. Be decisive — pick one category.

Step 2 — Call the model

python3 ~/.claude/skills/auto-model-router/scripts/call_model.py "<category>" "<user task text>"

Exit codes:

• 3 — API key missing: tell the user which env var to set
• 4 — Config not found: tell the user to run python3 scripts/setup.py
• 5 — No routes configured at all: tell the user to run python3 scripts/setup.py

Step 3 — Present the result

Show the response naturally. Add a subtle footer: _[auto-model-router: used {category} → {model}]_

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Mode B — Router (with learning)

Use this when AUTO_MODEL_ROUTER_URL is set.

Privacy note: Task text and an anonymous session ID are sent to the router at AUTO_MODEL_ROUTER_URL. This URL is always set by the user — the skill has no built-in remote endpoint. If the user has not explicitly set this variable, always use Mode A.

Step 1 — Get recommendation

python3 ~/.claude/skills/auto-model-router/scripts/recommend.py "<user task text>" "<USER_ID>"

• Capture stdout as the model response.
• Extract TASK_ID from stderr (line starting with TASK_ID=).

Exit codes:

• 2 — Router offline: fall back to Mode A automatically
• 3 — API key missing: tell the user which env var to set

Step 2 — Present the result

Same as Mode A Step 3.

Step 3 — Collect feedback

Ask once after presenting the result:

"Was this response helpful? Reply 👍, 👎, or skip."

If 👍:

python3 ~/.claude/skills/auto-model-router/scripts/feedback.py "<TASK_ID>" 1 "<USER_ID>"

If 👎:

python3 ~/.claude/skills/auto-model-router/scripts/feedback.py "<TASK_ID>" -1 "<USER_ID>"

If skip, do nothing.

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Changing Model Assignments

When the user says things like "switch to GPT-4o for translation" or "use DeepSeek for coding":

python3 ~/.claude/skills/auto-model-router/scripts/update_route.py <category> <provider> <model>

Examples:

python3 ~/.claude/skills/auto-model-router/scripts/update_route.py translation openai gpt-4o
python3 ~/.claude/skills/auto-model-router/scripts/update_route.py coding deepseek deepseek-chat
python3 ~/.claude/skills/auto-model-router/scripts/update_route.py daily_chat google gemini-2.0-flash

Confirm to the user: "Done, {category} tasks will now use {model}."

First-time Setup

If config is missing, tell the user to run:

python3 ~/.claude/skills/auto-model-router/scripts/setup.py

Manual Invocation

/auto-model-router <your task>