model_snapshot

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

No annotations exist, so the description must disclose behavior. It explains the content of summary and detail modes but does not state whether the operation is read-only, potential side effects, or error conditions. The reference to restricting table codes is not backed by a schema parameter, adding ambiguity.

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 and front-loaded, stating the core action ('Convert the model into compact JSON') first, then elaborating on modes. Every sentence adds value without 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?

For a tool with only two parameters and no output schema, the description covers the purpose and mode semantics adequately. However, the unresolved table-codes restriction and lack of behavioral notes (e.g., read-only guarantees) leave gaps that an agent may need to resolve.

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 enriches the mode parameter by explaining summary vs detail, but model_id is only self-evident from its name. More critically, it mentions an 'optionally restrict to given table codes' capability that has no corresponding parameter in the input schema, creating confusion about how to invoke that behavior.

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 converts the model into compact JSON, and specifies two modes (summary and detail) along with an optional restriction to table codes. This is a specific verb-resource pair, distinct from other model inspection tools like get_model_info or inspect_schema.

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 usage for obtaining a snapshot for reasoning but does not explicitly state when to use this tool versus alternatives such as inspect_schema or get_model_info. No exclusion criteria or conditional guidance is given.

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