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route.classify

Read-only

Classify a freeform request into the right mode (research, news, finance, astrology, …) before spending a run. Never charged.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
promptYesThe freeform request to classify, e.g. 'compare the best espresso grinders under $300'.

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
modeYesThe chosen mode id — pass it to runs.launch.
fieldsNoFields the router extracted from the prompt (mode-specific).
from_llmNoTrue when the LLM router answered, false for the offline heuristic.
rationaleNoWhy this mode was picked.
alternatesNoOther plausible modes, best first.
confidenceYesRouter confidence, 0–1.

Schema Changelog

Changes observed during successful MCP inspections.

  1. First observed

TDQS

A4.3/5.0
Behavior4/5

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

Annotations already declare this a safe read-only operation, so the description need not repeat that. It adds value by disclosing the workflow timing ('before spending a run') and the cost behavior ('Never charged'), which are behavioral traits beyond the annotations. No contradiction with the read-only hint exists.

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

Conciseness5/5

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

Two short sentences deliver the core purpose, workflow context, and cost implication without any filler. The operational guidance is front-loaded, and every word earns its place.

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?

For a one-parameter, read-only classifier with a full output schema, the description covers the essential facts: what it classifies, when to call it, and that it is free. Nothing an agent needs to invoke it correctly is missing.

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% and the single parameter includes a helpful example. The description does not add parameter-level detail beyond the schema, but the baseline of 3 applies because the schema already fully documents the prompt parameter.

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?

The description uses a specific verb ('Classify') and resource ('freeform request') and names the classification output categories (research, news, finance, astrology). It also frames the tool's role in the workflow, distinguishing it from launching a run.

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?

The description clearly states when to use the tool: before spending a run, to determine the right mode. It also adds a key practical qualifier, 'Never charged', which helps an agent decide to call it without cost concern. It does not name sibling alternatives explicitly, but the 'before spending a run' context is sufficient for this simple tool.

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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