get_study_chunks

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

With no annotations, the description carries the full burden. It states the tool 'split[s] a document into numbered study-sized chunks' and lists default parameters, but omits behavioral traits like whether the document is read-only or if any side effects occur.

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 extremely concise: one sentence for purpose followed by a compact list of arguments. Every sentence adds value with no redundancy.

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 that the output schema exists and the parameter count is low (3), the description covers all necessary details: what the tool does, what each parameter means, and defaults. No missing context for a chunking 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 coverage is 0%, so the description must compensate. It describes all three parameters: 'relative_path' as path relative to docs root, 'chunk_chars' as target chunk size with default 3000, and 'overlap' as overlap with default 200. This adds meaning beyond the raw schema, though it could be more concise.

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 explicitly states the action ('Split a document') and the resource ('numbered study-sized chunks'). This clearly distinguishes it from siblings like 'read_document' or 'get_document_outline'.

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 implies the tool is for studying a document in pieces but does not explicitly state when to use it instead of alternatives like 'read_document' or 'get_quiz_source_material'. No exclusions or when-not guidance.

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