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route_intent

Converts plain-English queries into typed IDs for your tasks. Use natural language to get the exact module identifiers you need.

Instructions

Return typed IDs matching the plain-English intent.

Example: route_intent("parse JSON in M") returns ["module:m-stdlib#STDJSON"]. Results are [primary, *see_also] from the matched task_index row.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
queryYes

Output Schema

TableJSON Schema
NameRequiredDescriptionDefault
resultYes
Behavior4/5

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

The description discloses the return format (typed IDs, primary, see_also) and gives an example. It does not mention error handling or edge cases, but for a simple lookup tool, this is acceptable given no annotations.

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?

The description is remarkably concise: two sentences and one example. Every sentence adds value, and the example is placed immediately after the purpose statement, aiding quick comprehension.

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

Completeness4/5

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

Given the single parameter and the presence of an output description (though not a formal schema), the description covers the essential behavior. Lacks details on no-match scenarios but is otherwise complete for its complexity.

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

Parameters5/5

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

The input schema provides only a parameter name; the description fully compensates by explaining 'query' as a plain-English intent and illustrating with an example. This adds critical meaning beyond the schema.

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 clearly states the tool returns typed IDs matching plain-English intent. The example reinforces the purpose, and the sibling tools (describe, verify) have distinct purposes, making this tool's role unambiguous.

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?

While no explicit when-to-use or when-not-to-use is given, the description's clarity and the distinct sibling names make the tool's usage intuitive. The example provides concrete usage context.

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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