get_data_model

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

Annotations already declare readOnlyHint=true, so the agent knows this is a safe read operation. The description adds useful context: it specifies the permissions required ('View Rules'), which isn't covered by annotations. However, it doesn't disclose other behavioral traits like rate limits, error conditions, or what 'complete' information entails beyond the schema. No contradiction with annotations exists.

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 appropriately sized with three sentences that are front-loaded: the first states the purpose, the second elaborates on returns, and the third adds permissions. There's minor redundancy between the first two sentences, but overall it's efficient with zero waste.

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's complexity (simple read operation), annotations cover safety, schema covers parameters fully, and an output schema exists (so return values are documented), the description is mostly complete. It adds permissions context, which is valuable. However, it lacks guidance on usage versus siblings, which is a minor gap in this context.

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 100%, with the parameter 'data_model_id' fully documented in the schema. The description adds no additional meaning about parameters beyond what the schema provides (e.g., no examples or usage notes). With high schema coverage, the baseline score of 3 is appropriate as the description doesn't compensate but doesn't need to.

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: 'Get detailed information about a Panther data model, including the mappings and body' and 'Returns complete data model information including Python body code and UDM mappings.' This specifies the verb ('Get'), resource ('Panther data model'), and scope of information returned. However, it doesn't explicitly differentiate from sibling tools like 'list_data_models' or 'get_detection' beyond the data model focus.

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 mentions permissions ('View Rules'), but this doesn't help choose between this and sibling tools like 'list_data_models' (for listing) or 'get_detection' (for other resources). There's no explicit when/when-not context or named alternatives.

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