chat_configure

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. However, it only describes parameters and their values; it does not mention any behavioral traits such as side effects, authorization requirements, rate limits, or what happens to existing settings. The description is silent on behavioral aspects beyond the parameter semantics.

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 concise (4 lines) and structured with a clear list of parameters. Every sentence serves a purpose. It avoids unnecessary fluff. The use of a Python docstring format is clear but could be slightly more polished for an MCP description.

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 has 4 parameters, no annotations, and an output schema that exists but isn't utilized in the description, the description is somewhat complete for parameter semantics but lacks behavioral context. The agent knows how to invoke it but not what to expect in terms of side effects or return values. The output schema might cover the return, but the description doesn't reference it.

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 significant meaning beyond the schema, which has 0% description coverage. It explains each parameter: notebook_id is a 'Notebook UUID', goal accepts 'default|learning_guide|custom', custom_prompt is 'Required when goal=custom (max 10000 chars)', and response_length is 'default|longer|shorter'. This provides clarity on allowed values and constraints, making it easier for the agent to use 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 the tool's purpose: 'Configure notebook chat settings.' This is a specific verb+resource combination. While it doesn't explicitly differentiate from sibling tools, the function is distinct enough that it stands out among tools like notebook_create or notebook_rename.

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 does not mention prerequisites, context, or exclusions. The agent is left to infer that it should be used when wanting to change chat settings for a notebook, but no explicit 'when to use' or 'when not to use' is provided.

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