get_messages

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

In the absence of annotations, the description discloses that it includes 'recently captured evaluation and dispatch-level messages' and provides a concrete example of the output format. It does not detail all limitations (e.g., message retention limits), but it is sufficiently transparent for a simple read tool.

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, using a brief intro, an analogy, structured Args/Returns/Example sections, and no wasted words. Every sentence adds value.

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 only one parameter and the presence of an output schema, the description covers the essential information: what the tool returns (list with timestamps) and when to use it. The example solidifies understanding.

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 only parameter, 'count', is explained in the Args section as 'Number of recent messages to retrieve (default 10)', adding meaning beyond the schema (which lacks any description). This compensates for the 0% schema description coverage.

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?

Clearly states 'Get recent Mathematica messages/warnings from the session' with a specific verb and resource. The analogy to Python's exception traceback and the example further clarify its purpose, distinguishing it from sibling tools like get_symbol_info or get_variable.

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?

Provides context for when to use: 'Like Python's exception traceback - helps debug what went wrong' and includes an example after a failed computation. However, it does not explicitly state when not to use or mention alternative tools.

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