List Ml Projects

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

Annotations already declare readOnlyHint, idempotentHint, and non-destructive behavior, so the description need not repeat them. The description adds no behavioral context beyond the resource type, such as default limit behavior or whether results are paged, but it aligns with the annotations.

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 focused sentence with no filler or repetition of the title. It could add slightly more context, but for a simple list tool it remains appropriately sized.

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 has one optional parameter documented in the schema, a rich output schema, and safety annotations, the description provides enough to invoke the tool. The only material gap is lack of usage context relative to sibling project/model tools.

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 single parameter 'limit' is fully described in the input schema, including its default value and meaning. The description adds no parameter information, but with 100% schema coverage the schema carries the burden sufficiently.

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 specifies the verb 'List' and a concrete resource, 'AutoML pipeline automation projects,' which distinguishes it from unrelated sibling list tools. It stops short of explicitly differentiating from similar ML-related tools like list_registered_models, but the resource is specific enough for basic selection.

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?

There is no guidance on when to use this tool or how it relates to alternatives. No mention of using it before create_ml_project or run_ml_project, nor any exclusion such as 'use list_registered_models for models.' The agent must infer usage from the name alone.

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