Get Model Check

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

No annotations are provided, so the description carries the full burden, and it does so well: it declares 'Read-only,' documents the full status state machine including 'terminal,' and explains the consequential semantics of an incomplete result ('reports no violation up to the depth reached and credits nothing'). It stops short of permissions, pagination, or what happens if no check exists beyond the 'none' status.

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?

Front-loaded with purpose and the read-only flag in the first two sentences, then a dense but non-redundant enumeration of status values. The long status list is verbose yet each entry earns its place by defining a distinct lifecycle state.

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?

An output schema exists, so the description is not obliged to explain return shape, yet it usefully supplies the semantic meaning of statuses that a schema cannot convey. Given a no-annotation read tool, the main residual gap is routing guidance relative to request_model_check and manage_model_check.

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 description coverage is 50%: model_id is documented but server_version is not. The description says nothing about either parameter — it is entirely devoted to return-value semantics, so it does not compensate for the undocumented half of the input.

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 first sentence states a specific verb and resource with disambiguation: 'Read a model's model check: the live one, else the latest.' The 'live one, else the latest' fallback rule is exactly the kind of scope detail that separates this from sibling readers like get_threat_model or get_control_generation_status.

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?

Usage is only implied: the 'differences' status routes the agent to answer_behavioural_questions, which is a useful conditional pointer. But there is no explicit statement of when to call this versus request_model_check, manage_model_check, or how it relates to polling after a check is requested.

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