parse_natural_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. It discloses that the tool 'understands requests' and 'supports English and Turkish', which adds context about language capabilities. However, it lacks details on error handling, rate limits, or authentication needs, leaving behavioral gaps for a parsing tool.

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 front-loaded with the core purpose, followed by examples and usage guidelines in two efficient sentences. Every sentence adds value—no redundancy or wasted words—making it highly concise and well-structured.

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 moderate complexity (parsing natural language) and no annotations or output schema, the description is mostly complete. It covers purpose, usage, and examples, but lacks details on output format or error cases, which could be helpful for an AI agent invoking the tool.

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 description coverage is 100%, so the schema already documents both parameters fully. The description implies the 'text' parameter usage through examples but adds no additional syntax or format details beyond what the schema provides. Baseline 3 is appropriate when the schema does the heavy lifting.

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: 'Convert everyday language into a structured trading intent' with specific examples like 'sell 10 ETH for USDC above 4000'. It distinguishes from siblings by focusing on natural language parsing rather than intent creation, validation, explanation, or commitment.

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?

Explicit guidance is provided: 'Use this whenever a user describes a crypto trade, swap, exchange, or asset conversion in natural language.' It specifies supported languages (English and Turkish) and gives clear examples of when to apply the tool, with no contradictory or missing exclusion criteria.

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