check_numbers

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

Annotations already declare readOnlyHint=true and idempotentHint=true. The description adds significant behavioral context: it is heuristic, flags only clear-cut cases, has phase-1 limitations, and caps input at 100,000 characters. 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 well-structured with bullet points and clear sections, each sentence adding value. It is appropriately sized for the complexity of the tool, though slightly verbose in explaining limitations.

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?

Given the presence of an output schema, the description provides complete context about input, checked cases, skipped cases, and input constraints, leaving no ambiguity for an AI agent.

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?

Schema coverage is 100% with a single 'text' parameter described. The description adds meaning beyond the schema by detailing what the tool checks within the text and its limitations, providing richer context for parameter usage.

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 states it is a heuristic Estonian number-writing check that flags two specific cases: decimal comma vs period and thousands space vs comma. It distinguishes itself from sibling tools like spell_check by focusing specifically on number formatting conventions.

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 explains when to use it (for Estonian text number formatting) and explicitly mentions what it intentionally does not handle (spell-out-vs-digits guidance) due to false positive concerns, providing helpful exclusion criteria. However, it does not explicitly contrast with sibling tools.

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