kaiten_update_document

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

With no annotations provided, the description carries the burden of behavioral disclosure. It does reveal important behavior: text content is auto-converted to ProseMirror, raw JSON is accepted, and text takes precedence if both are supplied. However, it does not describe side effects like whether unspecified fields are left unchanged, whether this is a partial or full update, or any permission requirements.

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?

Two sentences with zero waste. The core action is front-loaded, and the key content-format guidance is delivered immediately. The precedence rule is stated in a compact, direct way.

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 description is brief but supplemented by a rich input schema that documents all parameters, including the required document_uid and conversion caveats. The main omission is the absence of explicit update semantics (e.g., partial vs full replacement) and return-value expectations, but the schema and name cover most practical needs.

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 100%, so the baseline is 3. The description adds meaningful value beyond the schema by explicitly stating the precedence rule ('If both provided, 'text' wins'), which is not present in any parameter description. This is an important semantic for agents to choose between text and data correctly.

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 action ('Update a Kaiten document') and identifies the resource type. It does not explicitly differentiate from sibling tools like create or get, but the verb 'Update' combined with the resource makes the purpose 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 guidance on choosing between the 'text' and 'data' parameters, which is useful internal usage guidance. However, it does not explicitly state when to use this tool versus alternatives (e.g., create_document for new documents, or get_document for reading), leaving the usage context to be inferred from the tool name.

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