list_dlp_patterns

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

No annotations are provided, so the description carries the full burden of behavioral disclosure. 'List' implies a read-only operation, but nothing is said about pagination, account scoping of results, response shape, or whether only 'available' patterns are returned and what 'available' means. This is minimal disclosure that adds little beyond the verb itself.

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?

A single sentence with zero filler, front-loaded with the action verb and resource. It is efficient and easy to parse. The terseness borders on under-specification, but as pure conciseness it scores well.

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 simple one-parameter list tool, the description is minimally viable: the required account_id is documented and the action is clear. However, with no output schema and no annotations, the agent receives no information about the return format, default ordering, or what constitutes a 'predefined DLP pattern,' leaving notable gaps.

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 coverage is 100% — account_id is already documented as 'The account ID.' The description adds no parameter-specific meaning or usage detail beyond the schema, so the baseline 3 applies.

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 uses a specific verb ('List') and resource ('predefined DLP patterns'), making the basic operation clear. It distinguishes itself from DLP siblings like list_dlp_profiles and list_dlp_datasets by naming a different resource type. However, it never explains what a 'pattern' is versus a 'profile' or 'dataset', so an agent selecting among DLP tools may still be uncertain.

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?

No guidance is given on when to use this tool versus alternatives. It doesn't reference any sibling tools, mention that patterns differ from profiles/datasets, or state any context in which a caller would prefer one over another. The agent is left to infer usage entirely from the tool name.

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