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 behaviors: it's a read-only list operation (implied by 'List endpoint'), supports search queries via a specific syntax (linked), and results are paginated (linked to logs pagination). This covers essential traits like functionality, input constraints, and output handling, though it could mention rate limits or authentication needs.

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 front-loaded with the core purpose in the first sentence, followed by two concise sentences that add critical behavioral details (search syntax and pagination) and usage guidance. Every sentence earns its place with no wasted words, making it highly efficient and well-structured.

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 (search and pagination), no annotations, no output schema, and 0 parameters, the description does a good job of providing necessary context. It explains the search query mechanism and pagination behavior, which are crucial for correct usage. However, it doesn't detail the output format or error handling, leaving some gaps for a tool with no structured output documentation.

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% coverage, so no parameters are documented in the schema. The description compensates by explaining that the tool uses a search query (via a linked syntax guide) and pagination (via a linked guide), which effectively describes the implicit parameters or usage context. This adds meaningful semantics beyond the empty schema.

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: 'List endpoint returns CI Visibility test events that match a search query.' It specifies the verb ('list'), resource ('CI Visibility test events'), and scope ('match a search query'), making it easy to understand what the tool does. However, it doesn't explicitly differentiate from sibling tools like 'search_ci_pipelines_events' or 'search_events', which prevents a perfect score.

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 some usage guidance: 'Use this endpoint to build complex events filtering and search.' This implies the tool is for complex queries, but it doesn't explicitly state when to use this tool versus alternatives like 'get_ci_tests_events' (which appears to be a simpler getter) or other search tools. The guidance is present but not comprehensive.

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