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

With no annotations provided, the description carries the full burden of behavioral disclosure. It accurately describes the input and output (English and native names), and implicitly indicates a read-only, side-effect-free operation. It does not detail error handling or edge cases, but given the simple lookup nature, this is acceptable.

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 a concise opening purpose statement followed by bullet-style 'Use when' and 'Do not use when' sections. Every sentence earns its place, and there is no extraneous 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?

Given the tool's simplicity (one parameter, no annotations, no output schema), the description fully covers the needed context: what the tool does, when to use it, what input to provide, and what output to expect. It is complete enough for an AI agent to select and invoke it 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?

Schema coverage is 0%, so the description must define the parameter. It does so clearly: 'code' is an ISO 639-1 language code, with examples 'en, fr, or ja' and the constraint 'two-letter code'. This adds meaningful context beyond the raw schema, though it does not address the schema's maximum length of 3 characters.

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 the tool's function: resolving an ISO 639-1 language code to its English and native names. It distinguishes itself from siblings by explicitly listing 'do not use when' scenarios such as translation, language detection, and country language lookup, even naming country_lookup as the alternative.

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?

Provides explicit 'Use when' examples with concrete queries and 'Do not use when' exclusions, as well as naming the appropriate alternative tool for country-based lookups. This gives the AI agent clear decision criteria for when to invoke this tool.

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