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aistupidlevel-mcp

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TypeScript
Remote

Preview Smart Router choice

preview_route
Read-onlyIdempotent

Determine which model the Smart Router would send a prompt to, including strategy, provider, benchmark score, cost, and fallback chain—without calling or counting a request. Requires a router key.

Instructions

Which model the AI Stupid Level Smart Router would send a prompt to, and why: the routing strategy, the chosen model and provider with its benchmark score and estimated cost, and the fallback chain. Nothing is sent to a model and nothing is counted. Needs a router key (ASL_ROUTER_KEY).

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeNoRouting mode (default auto = the strategy saved in the account): auto-best (highest combined score), auto-coding, auto-reasoning, auto-tooling (top model on that benchmark), auto-task (reads the prompt and picks the benchmark), auto-value, auto-value-coding, auto-value-reasoning, auto-value-tooling (most points per measured dollar among models within 5 points of the best), auto-fastest-quality, auto-consistent (fastest or steadiest near-top model), auto-fastest, auto-cheapest (no quality bar).
promptYesThe prompt to route (the decision can depend on it, for example with auto-task).
systemNoAn optional system message.
sandboxNoSandbox: run the real routing as if the account had a key for every provider and return a mock answer. Nothing is called, spent or counted.
pin_modelNoPin a specific model id (for example gpt-6-sol) instead of a routing mode.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observedv0.1.0

TDQS

A4.2/5.0
Behavior4/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

Annotations already declare readOnly/idempotent/non-destructive, and the description reinforces this by confirming no model is called and nothing is counted or billed. It also surfaces the auth requirement (ASL_ROUTER_KEY), which annotations cannot express. It doesn't elaborate on failure modes (e.g. missing key behavior) beyond the sandbox note.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

Front-loads the outcome (which model and why) before the safety constraint and key requirement. The opening sentence is dense but every clause maps to a distinct return field; the two short follow-up sentences are pure value.

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness5/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

There is no output schema, so the description compensates by enumerating the returned decision details, and it covers the no-side-effect guarantee and the credential prerequisite. An agent has everything needed to call this correctly and interpret the result.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, including a fully enumerated mode list, so the schema carries parameter meaning. The description adds no per-parameter syntax or defaults beyond what the schema already documents, so baseline 3 applies.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose5/5

Does the description clearly state what the tool does and how it differs from similar tools?

States a specific verb-scope (preview the routing decision) and enumerates the exact outputs: strategy, chosen model/provider with benchmark and estimated cost, and fallback chain. This clearly separates it from ask_router, which actually dispatches the prompt.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines4/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

"Nothing is sent to a model and nothing is counted" clearly frames it as the safe dry-run alternative to actually asking the router, and the router-key prerequisite is stated. It stops short of naming ask_router explicitly as the contrasting sibling, so the routing choice is implied rather than spelled out.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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