MCP Datadog Server

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 effectively describes key traits: the destructive nature ('Delete all custom lists'), the bulk operation scope, the email notification capability, and the specific permission requirement. However, it lacks details on error handling, confirmation prompts, or rate limits, which would enhance transparency for a destructive operation.

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 efficiently structured in three sentences: the first states the core purpose, the second adds operational details (selection and notification), and the third specifies permissions. Each sentence adds critical information without redundancy, making it front-loaded and waste-free.

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 (destructive bulk operation), no annotations, and no output schema, the description is largely complete. It covers purpose, usage, behavioral traits, and permissions. However, it lacks details on the return value or confirmation process, which would be helpful for an agent invoking a destructive tool with no output schema.

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 input schema has 0 parameters with 100% description coverage, so the schema fully documents the lack of parameters. The description adds value by explaining the selection mechanism ('by passing a metric name prefix') and the email notification feature, which are not captured in the schema. This compensates well, though it doesn't detail how the prefix is specified without parameters.

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 specific action ('Delete all custom lists of queryable tag keys'), the target resources ('for a set of existing count, gauge, rate, and distribution metrics'), and the selection mechanism ('by passing a metric name prefix'). It distinguishes itself from sibling tools by focusing on bulk tag deletion for metrics configuration, which is not covered by other delete operations like delete_metric_tags.

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 clear context for when to use this tool: for bulk deletion of custom tag lists for metrics selected by name prefix, with results sent via email. It mentions the permission requirement ('Manage Tags for Metrics') but does not explicitly state when NOT to use it or name specific alternatives among siblings, such as delete_metric_tags for non-bulk operations.

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