e2e_tir_list_model_endpoints

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

With no annotations provided, the description carries the full burden of behavioral disclosure. It implies a read-only listing operation but does not state whether authentication is required, whether results are paginated, what the return format looks like, or any rate limits or side effects. The single sentence is insufficient for an agent to understand the tool's behavior beyond its basic purpose.

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 a single, front-loaded sentence with zero wasted words. It immediately states the action and resource, making it easy to parse. For a simple list tool, this length is appropriate and efficient.

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 low complexity (2 optional parameters, no output schema, no annotations), the description covers the core purpose but leaves gaps. It does not explain how the optional 'location' and 'project_id' parameters affect the listing, nor does it mention any behavioral traits like pagination. It is minimally adequate but not fully complete for an agent to invoke with confidence.

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%, so the input schema already documents both 'location' and 'project_id' with clear descriptions. The description adds no additional meaning about how these parameters filter the results or whether they are optional. The baseline of 3 is appropriate when the schema does the heavy lifting.

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 states a specific verb ('List') and resource ('deployed model inference endpoints') scoped to 'E2E TIR', and the example (vLLM/HuggingFace) further clarifies the resource type. It is clearly distinguishable from siblings that list notebooks, datasets, or GPU SKUs by the resource name alone, but it does not explicitly name an alternative or contrast itself with any sibling tool.

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 when-to-use guidance, no prerequisites, and no exclusions. It does not indicate when an agent should choose this tool over e2e_tir_list_notebooks, e2e_tir_list_training_clusters, or other list tools, leaving usage entirely to inference from the resource name.

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