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

With no annotations provided, the description carries the full burden of disclosing behavior. It fails to mention that chunks are sized and overlapped via configurable parameters, nor does it specify the chunking strategy (e.g., character vs. token-based). The minimal phrasing leaves user expectations unclear.

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, front-loaded sentence with zero waste. It efficiently conveys the core function without redundant phrasing.

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 3 parameters and no annotations or output schema. The description is too minimal to fully specify behavior: it does not explain chunk semantics, parameter effects, or use context. Users would likely need additional documentation to configure the tool 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 description coverage is 0%, and the description adds no information about the three parameters. The names 'text', 'overlap', and 'chunk_size' suggest their roles, but the description does not explain how overlap or chunk_size affect output, which is essential for correct invocation.

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 'Split text into RAG chunks' uses a specific verb ('split'), resource ('text'), and outcome ('RAG chunks') that clearly differentiates it from sibling tools like line_split or generic split. The acronym 'RAG' provides immediate context for retrieval-augmented generation use cases.

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?

No guidance is provided about when to use this tool versus alternatives. The description implies RAG-related usage but does not mention alternatives like line_split or specify exclusions, leaving the agent to infer appropriate contexts.

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