analyze_language

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. It states what the tool does but doesn't describe how it behaves: it doesn't specify the output format (e.g., percentages, counts), whether it handles mixed-language text, error conditions, or performance characteristics. This is a significant gap for a tool with no annotation coverage.

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 a single, efficient sentence that front-loads the core purpose ('Analyze text for language distribution and character types') followed by a specific list. There's no wasted verbiage, though it could be slightly more structured (e.g., separating languages from character categories).

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 complexity of language analysis, lack of annotations, and no output schema, the description is incomplete. It doesn't explain what the tool returns (e.g., a breakdown by language, character counts), how it handles ambiguous cases, or any limitations (e.g., supported encodings). This leaves significant gaps for an agent to use the tool effectively.

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?

The input schema has 100% description coverage, with the 'text' parameter clearly documented. The description adds marginal value by implying the text should contain content relevant to the listed languages and character types, but doesn't provide additional syntax, format, or constraints beyond what the schema already states. This meets the baseline for high schema coverage.

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 purpose: 'Analyze text for language distribution and character types' followed by a specific list of languages and character categories. It uses a specific verb ('analyze') and resource ('text'), though it doesn't explicitly differentiate from sibling tools like 'format_text_case' or 'validate_data' which might also process text.

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 no guidance on when to use this tool versus alternatives. It doesn't mention when this analysis is appropriate (e.g., for multilingual content, character encoding checks) or when other tools like 'format_text_case' or 'validate_data' might be better suited. No exclusions or prerequisites are stated.

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