MCP Datadog Server

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

No annotations are provided, so the description carries the full burden. It discloses key behavioral traits: it's a read operation ('List'), returns paginated results with a link to documentation, and matches a search query. However, it doesn't mention potential rate limits, authentication requirements, or error conditions, which are important for a tool with no 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 concise with three sentences: one states the purpose, one provides usage guidance, and one notes pagination with a link. It's front-loaded with the core functionality. However, the pagination note is in brackets and could be integrated more smoothly, slightly affecting structure.

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 no annotations, no output schema, and 0 parameters, the description is moderately complete. It covers purpose, usage, and pagination behavior, but lacks details on authentication, error handling, or response format. For a read tool with no structured data, more context on these aspects would improve completeness.

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 doesn't add parameter details, but since there are no parameters, this is acceptable. It implies the tool might accept a search query (from 'match a Audit Logs search query'), but doesn't specify how this is provided, keeping it from a perfect score.

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 events that match a Audit Logs search query.' It specifies the verb ('List'), resource ('Audit Logs events'), and scope ('search query'). However, it doesn't explicitly differentiate from sibling tools like 'search_audit_events', which might offer similar functionality, preventing 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 context: 'Use this endpoint to see your latest Audit Logs events.' This implies when to use it (for viewing recent audit events) but doesn't explicitly state when not to use it or mention alternatives like 'search_audit_events' from the sibling list. The guidance is present but lacks specificity about tool selection.

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