tokenize

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 states the tool converts code to tokens but doesn't disclose behavioral traits such as error handling (e.g., invalid code), performance characteristics (e.g., speed, limits), or side effects. The description is minimal and lacks critical operational details beyond the basic function.

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 appropriately sized and front-loaded: the first sentence states the core purpose clearly. The 'Args' and 'Returns' sections are structured efficiently with no redundant information. Every sentence earns its place, making it concise and well-organized.

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 (tokenization task), no annotations, and an output schema present (which handles return values), the description is partially complete. It covers the basic purpose and parameters but lacks usage guidelines, behavioral details, and context for integration with siblings. It's adequate as a minimum viable description but has clear gaps in guidance and transparency.

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 description adds some meaning beyond the input schema: it specifies that the 'code' parameter must be 'Valid Pylpex source code', which clarifies the expected input format. However, with 0% schema description coverage and only one parameter, the description compensates partially but doesn't provide detailed semantics (e.g., code examples, tokenization rules). Baseline is 3 due to low parameter count and minimal added value.

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 Pylpex code into tokens for analysis.' It specifies the verb ('Convert'), resource ('Pylpex code'), and outcome ('tokens for analysis'), which distinguishes it from siblings like 'get_variables', 'reset', and 'run'. However, it doesn't explicitly differentiate from siblings beyond the basic function, missing a direct comparison.

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 prerequisites, context for tokenization (e.g., preprocessing steps), or comparisons to sibling tools. Usage is implied by the purpose but lacks explicit when/when-not instructions or alternatives.

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