classify_register

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

Annotations already indicate readOnlyHint and idempotentHint are true. The description adds valuable behavioral details: it is a coarse lexicon-based heuristic (not a trained model), has an input cap of 100,000 characters, and explains the output fields (tier, tier_estonian, score, markers) with a critical usage note about quoting tier_estonian verbatim. No contradictions with annotations.

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

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

The description is informative but somewhat lengthy. It is well-structured with clear sections (purpose, output details, limitations, usage tips). Every sentence adds value, but it could be slightly more concise without losing key information.

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

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

The description covers all relevant aspects: what the tool does, its output (with output schema existing but not shown), limitations, input constraints (100k characters), and a critical usage instruction. It provides sufficient context for an AI agent to use the tool correctly.

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

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

There is only one parameter 'text', and the input schema provides a description: 'Estonian text to classify by register (formal vs colloquial).' The tool description adds no further parameter-specific information beyond the schema. Given 100% schema coverage, a score of 3 is appropriate as the description does not significantly enhance parameter understanding.

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

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

The description clearly identifies the tool as a heuristic register classifier for Estonian (formal vs colloquial), specifying its output: tier labels (English and Estonian), a normalized score, and markers. It distinguishes itself from sibling tools (e.g., analyze_morphology, spell_check) by focusing specifically on register classification.

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

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

The description provides concrete use cases (sanity-checking marketing copy, contract draft) and explicitly states limitations (coarse heuristic, not a model, neutral for most newsletter prose). It advises using the result as a directional hint. However, it does not explicitly compare with alternatives or state when not to use this tool, though the context is clear.

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