chunk_text

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 only states the core transformation ('Split text into overlapping chunks') without disclosing edge cases, side effects, output structure, or whether the input is modified. The agent is left unaware of what the result looks like or how overlap and max_chunk_size interact.

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 two sentences with no filler. The first sentence front-loads the core action, and the second adds a brief use case. Every word earns its place, making it appropriately 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?

The tool has no annotations and 0% schema coverage, while the description is minimal. Although an output schema exists, it is not included in the description, and the tool's behavior around overlap and max_chunk_size is not explained. The description is insufficient for an agent to reliably configure all parameters or anticipate results.

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 0%, so the description must compensate for explaining parameters. It only hints at 'overlapping chunks' and 'context limits,' which loosely maps to overlap and max_chunk_size, but it does not clarify units, defaults, or relationships between parameters. The text parameter is obvious, but the other two are inadequately explained.

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 a specific verb and resource: 'Split text into overlapping chunks for LLM processing.' This distinguishes it from sibling tools like truncate_text, which implies truncation rather than chunking, and get_token_count, which counts tokens. The purpose is immediately understandable and unambiguous.

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 clear usage context: 'Useful for processing content that exceeds context limits.' This tells the agent when to use the tool, but it does not explicitly mention alternatives or when not to use it. It is solid guidance, but falls short of the full 'when/when-not/alternatives' level.

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